diff --git a/.editorconfig b/.editorconfig index 0779e8ad978e..dab5d2a638dd 100644 --- a/.editorconfig +++ b/.editorconfig @@ -86,7 +86,6 @@ indent_style = tab [*.{f,f.txt}] indent_style = space indent_size = 2 -insert_final_newline = false # Set properties for shell files: [*.{sh,sh.txt}] diff --git a/.github/workflows/good_first_issue.yml b/.github/workflows/good_first_issue.yml index 730799067755..abe24145bf83 100644 --- a/.github/workflows/good_first_issue.yml +++ b/.github/workflows/good_first_issue.yml @@ -56,7 +56,7 @@ jobs: GH_REPO: ${{ github.repository }} NUMBER: ${{ github.event.issue.number }} BODY: | - # :rotating_light: Important: PLEASE READ :rotating_light: + # :wave: Important: PLEASE READ :wave: This issue has been labeled as a **good first issue** and is available for anyone to work on. diff --git a/.github/workflows/labeler.yml b/.github/workflows/labeler.yml index 62a1404a32bd..bc2ef3f71b37 100644 --- a/.github/workflows/labeler.yml +++ b/.github/workflows/labeler.yml @@ -24,6 +24,7 @@ on: pull_request_target: types: - opened + - closed - synchronize - reopened - edited @@ -64,6 +65,31 @@ jobs: configuration-path: .github/labeler.yml repo-token: ${{ secrets.CHATBOT_GITHUB_TOKEN }} + # Add "First-time Contributor" label if PR is from a first-time contributor: + - name: 'Add "First-time Contributor" label if PR is from a first-time contributor' + if: ${{ github.event.action == 'opened' || github.event.action == 'reopened' }} + # Pin action to full-length commit SHA + uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7.0.1 + with: + github-token: ${{ secrets.CHATBOT_GITHUB_TOKEN }} + script: | + const { data: pr } = await github.rest.pulls.get({ + 'owner': context.repo.owner, + 'repo': context.repo.repo, + 'pull_number': context.payload.pull_request.number + }); + if ( pr.author_association === 'FIRST_TIME_CONTRIBUTOR' ) { + const labels = context.payload.pull_request.labels.map( label => label.name ); + if ( !labels.includes( 'First-time Contributor' ) ) { + await github.rest.issues.addLabels({ + 'owner': context.repo.owner, + 'repo': context.repo.repo, + 'issue_number': context.payload.pull_request.number, + 'labels': [ 'First-time Contributor' ] + }); + } + } + # Add "Needs Review" label when PR is opened and not a draft: - name: 'Add "Needs Review" label if PR is opened and not draft' if: ${{ github.event.action == 'opened' && github.event.pull_request.draft == false }} @@ -133,3 +159,37 @@ jobs: console.log( 'Error removing label %s: %s', label, error.message ); } } + + # Remove "First-time Contributor" label from other open PRs of same author if PR is merged: + - name: 'Remove "First-time Contributor" label from other open PRs of same author if PR is merged' + if: ${{ github.event.action == 'closed' && github.event.pull_request.merged == true }} + # Pin action to full length commit SHA + uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7.0.1 + with: + github-token: ${{ secrets.CHATBOT_GITHUB_TOKEN }} + script: | + const prAuthor = context.payload.pull_request.user.login; + const { owner, repo } = context.repo; + + // Search for all open PRs from the PR author: + const query = `repo:${owner}/${repo} type:pr state:open author:${prAuthor}`; + const response = await github.rest.search.issuesAndPullRequests({ + 'q': query, + 'per_page': 100 + }); + + const pullRequests = response.data.items; + for ( const pull of pullRequests ) { + if ( pull.user.login === prAuthor ) { + try { + await github.rest.issues.removeLabel({ + 'owner': context.repo.owner, + 'repo': context.repo.repo, + 'issue_number': pull.number, + 'name': 'First-time Contributor' + }); + } catch ( error ) { + console.log( 'Error removing "First-time Contributor" label from PR #%d: %s', pull.number, error.message ); + } + } + } diff --git a/.github/workflows/labeler_needs_changes.yml b/.github/workflows/labeler_needs_changes.yml index f9d1f055af0f..5f92960a9441 100644 --- a/.github/workflows/labeler_needs_changes.yml +++ b/.github/workflows/labeler_needs_changes.yml @@ -52,7 +52,6 @@ jobs: # Pin action to a known commit SHA for reproducibility: uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7.0.1 with: - github-token: ${{ secrets.CHATBOT_GITHUB_TOKEN }} script: | await github.rest.issues.addLabels({ 'owner': context.repo.owner, diff --git a/.github/workflows/lint_changed_files.yml b/.github/workflows/lint_changed_files.yml index 2872118bcba9..bc91909c277b 100644 --- a/.github/workflows/lint_changed_files.yml +++ b/.github/workflows/lint_changed_files.yml @@ -72,8 +72,21 @@ jobs: node-version: '20' # 'lts/*' timeout-minutes: 5 + # Cache dependencies: + - name: 'Cache dependencies' + # Pin action to full length commit SHA + uses: actions/cache@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0 + id: cache + with: + path: | + ${{ github.workspace }}/node_modules + key: ${{ runner.os }}-node-${{ hashFiles('**/package.json') }} + restore-keys: | + ${{ runner.os }}-node- + # Install dependencies (accounting for possible network failures, etc, when installing node module dependencies): - name: 'Install dependencies' + if: steps.cache.outputs.cache-hit != 'true' run: | make install-node-modules || make install-node-modules || make install-node-modules timeout-minutes: 15 @@ -120,7 +133,7 @@ jobs: - name: 'Lint against EditorConfig' if: success() || failure() run: | - make lint-editorconfig-files FILES="${{ steps.changed-files.outputs.files }}" + make lint-editorconfig-files EDITORCONFIG_FORMAT=github-actions FILES="${{ steps.changed-files.outputs.files }}" # Lint Markdown files: - name: 'Lint Markdown files' diff --git a/.github/workflows/namespace_declarations.yml b/.github/workflows/namespace_declarations.yml index 3a0ee65dfc57..0da71e94c179 100644 --- a/.github/workflows/namespace_declarations.yml +++ b/.github/workflows/namespace_declarations.yml @@ -112,6 +112,15 @@ jobs: - updates namespace TypeScript declarations + ## Reviewer Checklist + + - [ ] **Check the scope of the changes** (following [Conventional Commits](https://www.conventionalcommits.org)): + - Are these **new APIs**? Then this is a `feat`. + - Are these **changes to existing APIs** that could break compatibility? Then this is a `feat!` (i.e., a breaking change). + - Are these **only documentation** changes to existing APIs? Then this is `docs`. + - [ ] Update the PR title to align with the change type (`feat`, `feat!`, or `docs`). + - [ ] Approve the PR once you are confident about the classification and changes made. + commit-message: 'feat: update namespace TypeScript declarations' committer: 'stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>' signoff: true diff --git a/.github/workflows/run_affected_benchmarks.yml b/.github/workflows/run_affected_benchmarks.yml index 268d596f2e19..b2630bb72287 100644 --- a/.github/workflows/run_affected_benchmarks.yml +++ b/.github/workflows/run_affected_benchmarks.yml @@ -35,6 +35,11 @@ on: # List paths for which changes should trigger this workflow: - 'lib/**/benchmark/**' + workflow_dispatch: + inputs: + directories: + description: 'List of changed directories for which to run affected benchmarks (space-separated)' + # Global permissions: permissions: # Allow read-only access to the repository contents: @@ -78,8 +83,21 @@ jobs: node-version: '20' # 'lts/*' timeout-minutes: 5 + # Cache dependencies: + - name: 'Cache dependencies' + # Pin action to full length commit SHA + uses: actions/cache@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0 + id: cache + with: + path: | + ${{ github.workspace }}/node_modules + key: ${{ runner.os }}-node-${{ hashFiles('**/package.json') }} + restore-keys: | + ${{ runner.os }}-node- + # Install dependencies (accounting for possible network failures, etc, when installing node module dependencies): - name: 'Install dependencies' + if: steps.cache.outputs.cache-hit != 'true' run: | make install-node-modules || make install-node-modules || make install-node-modules timeout-minutes: 15 @@ -90,9 +108,10 @@ jobs: make init timeout-minutes: 5 - # Get list of changed files: - - name: 'Get list of changed files' - id: changed-files + # Get list of changed directories from PR and push events: + - name: 'Get list of changed directories' + if: github.event_name != 'workflow_dispatch' + id: changed-directories continue-on-error: true run: | if [ -n "${{ github.event.pull_request.number }}" ]; then @@ -107,24 +126,24 @@ jobs: files=$(git diff --diff-filter=AM --name-only ${{ github.event.before }} ${{ github.event.after }}) fi fi - # Keep only benchmark files: - files=$(echo "$files" | grep -E 'benchmark/' | tr '\n' ' ' | sed 's/ $//') - echo "files=${files}" >> $GITHUB_OUTPUT + directories=$(for file in $files; do dirname $file; done | uniq | tr '\n' ' ' | sed 's/ $//') + echo "directories=${directories}" >> $GITHUB_OUTPUT - # Run JavaScript benchmarks: - - name: 'Run JavaScript benchmarks' + # Get list of changed directories from workflow dispatch event: + - name: 'Get list of changed directories (from user input)' + if: github.event_name == 'workflow_dispatch' + id: changed-directories-user-input run: | - files=$(echo "${{ steps.changed-files.outputs.files }}" | tr ' ' '\n' | grep -E '\.js$' | tr '\n' ' ' | sed 's/ $//') - if [ -n "$files" ]; then - make benchmark-javascript-files FILES="${files}" - fi - timeout-minutes: 30 + echo "directories=${{ github.event.inputs.directories }}" >> $GITHUB_OUTPUT + timeout-minutes: 5 - # Run C benchmarks: - - name: 'Run C benchmarks' + # Run affected benchmarks: + - name: 'Run affected benchmarks' run: | - files=$(echo "${{ steps.changed-files.outputs.files }}" | tr ' ' '\n' | grep -E '\.c$' | sed "s|^|${GITHUB_WORKSPACE}/|" | tr '\n' ' ' | sed 's/ $//') - if [ -n "$files" ]; then - make benchmark-c-files FILES="${files}" + if [ "${{ github.event_name }}" == "workflow_dispatch" ]; then + directories="${{ steps.changed-directories-user-input.outputs.directories }}" + else + directories="${{ steps.changed-directories.outputs.directories }}" fi - timeout-minutes: 15 + . "$GITHUB_WORKSPACE/.github/workflows/scripts/run_affected_benchmarks" "$directories" + timeout-minutes: 30 diff --git a/.github/workflows/run_affected_examples.yml b/.github/workflows/run_affected_examples.yml index 9ac6777c0482..76faa9ad2889 100644 --- a/.github/workflows/run_affected_examples.yml +++ b/.github/workflows/run_affected_examples.yml @@ -79,8 +79,21 @@ jobs: node-version: '20' # 'lts/*' timeout-minutes: 5 + # Cache dependencies: + - name: 'Cache dependencies' + # Pin action to full length commit SHA + uses: actions/cache@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0 + id: cache + with: + path: | + ${{ github.workspace }}/node_modules + key: ${{ runner.os }}-node-${{ hashFiles('**/package.json') }} + restore-keys: | + ${{ runner.os }}-node- + # Install dependencies (accounting for possible network failures, etc, when installing node module dependencies): - name: 'Install dependencies' + if: steps.cache.outputs.cache-hit != 'true' run: | make install-node-modules || make install-node-modules || make install-node-modules timeout-minutes: 15 diff --git a/.github/workflows/run_affected_tests.yml b/.github/workflows/run_affected_tests.yml index 3ca2af62b6c1..0bde9d06f2ad 100644 --- a/.github/workflows/run_affected_tests.yml +++ b/.github/workflows/run_affected_tests.yml @@ -114,8 +114,21 @@ jobs: node-version: '20' # 'lts/*' timeout-minutes: 5 + # Cache dependencies: + - name: 'Cache dependencies' + # Pin action to full length commit SHA + uses: actions/cache@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0 + id: cache + with: + path: | + ${{ github.workspace }}/node_modules + key: ${{ runner.os }}-node-${{ hashFiles('**/package.json') }} + restore-keys: | + ${{ runner.os }}-node- + # Install dependencies (accounting for possible network failures, etc, when installing node module dependencies): - name: 'Install dependencies' + if: steps.cache.outputs.cache-hit != 'true' run: | make install-node-modules || make install-node-modules || make install-node-modules timeout-minutes: 15 diff --git a/.github/workflows/run_tests_coverage.yml b/.github/workflows/run_tests_coverage.yml index d1116c0eb449..de9e8031094d 100644 --- a/.github/workflows/run_tests_coverage.yml +++ b/.github/workflows/run_tests_coverage.yml @@ -120,8 +120,21 @@ jobs: node-version: 20 # 'lts/*' timeout-minutes: 5 + # Cache dependencies: + - name: 'Cache dependencies' + # Pin action to full length commit SHA + uses: actions/cache@1bd1e32a3bdc45362d1e726936510720a7c30a57 # v4.2.0 + id: cache + with: + path: | + ${{ github.workspace }}/node_modules + key: ${{ runner.os }}-node-${{ hashFiles('**/package.json') }} + restore-keys: | + ${{ runner.os }}-node- + # Install dependencies (accounting for possible network failures, etc, when installing node module dependencies): - name: 'Install dependencies' + if: steps.cache.outputs.cache-hit != 'true' run: | make install-node-modules || make install-node-modules || make install-node-modules timeout-minutes: 15 diff --git a/.github/workflows/scripts/run_affected_benchmarks b/.github/workflows/scripts/run_affected_benchmarks new file mode 100755 index 000000000000..acd3e36d88fb --- /dev/null +++ b/.github/workflows/scripts/run_affected_benchmarks @@ -0,0 +1,163 @@ +#!/usr/bin/env bash +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# Script to run affected benchmarks for a given list of changed paths. +# +# Usage: run_affected_benchmarks path1 [path2 path3 ...] +# +# Arguments: +# +# path1 File name or directory path. +# path2 File name or directory path. +# path3 File name or directory path. +# +# +# Environment variables: +# +# LOG_FILE Log file. +# + +# shellcheck disable=SC2034,SC2153,SC2317 + +# Ensure that the exit status of pipelines is non-zero in the event that at least one of the commands in a pipeline fails: +set -o pipefail + + +# VARIABLES # + +# Get the list of changed files: +changed="$*" + +# Get the path to a log file as the third argument to the build script: +log_file="${LOG_FILE}" + +# Define a heartbeat interval to periodically print messages in order to prevent CI from prematurely ending a build due to long-running commands: +heartbeat_interval='30s' + +# Declare a variable for storing the heartbeat process id: +heartbeat_pid="" + + +# FUNCTIONS # + +# Error handler. +# +# $1 - error status +on_error() { + echo 'ERROR: An error was encountered during execution.' >&2 + cleanup + exit "$1" +} + +# Runs clean-up tasks. +cleanup() { + stop_heartbeat +} + +# Starts a heartbeat. +# +# $1 - heartbeat interval +start_heartbeat() { + echo 'Starting heartbeat...' >&2 + + # Create a heartbeat and send to background: + heartbeat "$1" & + + # Capture the heartbeat pid: + heartbeat_pid=$! + echo "Heartbeat pid: ${heartbeat_pid}" >&2 +} + +# Runs an infinite print loop. +# +# $1 - heartbeat interval +heartbeat() { + while true; do + echo "$(date) - heartbeat..." >&2 + sleep "$1" + done +} + +# Stops the heartbeat print loop. +stop_heartbeat() { + echo 'Stopping heartbeat...' >&2 + kill "${heartbeat_pid}" +} + +# Prints a success message. +print_success() { + echo 'Success!' >&2 +} + +# Main execution sequence. +main() { + start_heartbeat "${heartbeat_interval}" + + # Only keep files which reside in package directories: + changed=$(echo "${changed}" | tr ' ' '\n' | grep '^lib/node_modules/@stdlib') || true + + # Find unique package directories: + directories=$(echo "${changed}" | tr ' ' '\n' | sed -E 's/\/(bin|data|etc|include|lib|src|test)\/?$//' | uniq) + + if [ -z "${directories}" ]; then + echo 'No packages to run benchmarks for.' >&2 + cleanup + print_success + exit 0 + fi + + # Extract package names from changed package directories (e.g., @stdlib/math/base/special/sin) by removing the leading 'lib/node_modules/': + packages=$(echo "${directories}" | sed -E 's/^lib\/node_modules\///') + + # Build native add-ons for packages (if applicable): + for pkg in ${packages}; do + if [ -f "lib/node_modules/${pkg}/binding.gyp" ]; then + NODE_ADDONS_PATTERN="${pkg}" make install-node-addons + fi + done + + # Find all benchmark files in package directories: + js_bench_files=$(find "${directories}" -maxdepth 3 -wholename '**/benchmark/benchmark*.js' | grep -v '/fixtures/' | sort -u | tr '\n' ' ') || true + + # Run JS benchmarks: + if [ -n "${js_bench_files}" ]; then + make benchmark-javascript-files FILES="${js_bench_files}" + else + echo 'No JavaScript benchmarks to run.' >&2 + fi + + # Run C benchmarks: + echo "Finding C benchmark files in ${directories}..." + c_bench_files=$(find "${directories}" -maxdepth 4 -wholename '**/benchmark/c/benchmark*.c' -exec realpath {} \; | grep -v '/fixtures/' | sort -u | tr '\n' ' ') || true + + if [ -n "${c_bench_files}" ]; then + make benchmark-c-files FILES="${c_bench_files}" + else + echo 'No C benchmarks to run.' >&2 + fi + + cleanup + print_success + exit 0 +} + +# Set an error handler to print captured output and perform any clean-up tasks: +trap 'on_error' ERR + +# Run main: +main diff --git a/.github/workflows/slash_commands.yml b/.github/workflows/slash_commands.yml index e6dfe14e1b18..258449d2a2a3 100644 --- a/.github/workflows/slash_commands.yml +++ b/.github/workflows/slash_commands.yml @@ -61,13 +61,7 @@ jobs: - name: 'Add initial reaction' run: | COMMENT="${{ github.event.comment.body }}" - if [[ $COMMENT == "/stdlib help" || \ - $COMMENT == "/stdlib check-files" || \ - $COMMENT == "/stdlib update-copyright-years" || \ - $COMMENT == "/stdlib lint-autofix" || \ - $COMMENT == "/stdlib merge" || \ - $COMMENT == "/stdlib rebase" - ]]; then + if [[ $COMMENT =~ ^/stdlib\ (help|check-files|update-copyright-years|lint-autofix|merge|rebase) ]]; then curl -X POST \ -H "Accept: application/vnd.github.v3+json" \ -H "Authorization: Bearer ${{ secrets.STDLIB_BOT_GITHUB_TOKEN }}" \ diff --git a/.github/workflows/update_contributors.yml b/.github/workflows/update_contributors.yml index 38a808dd44c2..e125883513c1 100644 --- a/.github/workflows/update_contributors.yml +++ b/.github/workflows/update_contributors.yml @@ -105,6 +105,13 @@ jobs: - updates the list of contributors + ## Reviewer Checklist + + - [ ] For any **new contributors**, check if their full names are listed on their GitHub profile or in social links. + - [ ] If so, on the PR branch **update** the `.mailmap` file accordingly to ensure proper attribution. + - [ ] If updating `.mailmap`, **regenerate** the contributors file by running `make update-contributors` on the PR branch afterward. + - [ ] Approve the PR after verifying the changes. + commit-message: 'docs: update list of contributors' committer: 'stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>' signoff: true diff --git a/.mailmap b/.mailmap index 3593db50775e..34b869cf2903 100644 --- a/.mailmap +++ b/.mailmap @@ -9,6 +9,7 @@ # A Aayush Khanna <96649223+aayush0325@users.noreply.github.com> +Aayush Khanna Aayush Khanna aayush0325 Abhijit Raut <121740684+AbhijitRaut04@users.noreply.github.com> @@ -52,6 +53,9 @@ Chinmay Joshi <86140365+JawHawk@users.noreply.github.com> Chinmay J Debashis Maharana <145602692+DevMhrn@users.noreply.github.com> Debashis Maharana DebashisMaharana +Dhruv Arvind Singh <154677013+DhruvArvindSingh@users.noreply.github.com> DhruvArvindSingh +Dhruv Arvind Singh <154677013+DhruvArvindSingh@users.noreply.github.com> Dhruv/ + Dorrin Sotoudeh <59933477+dorrin-sot@users.noreply.github.com> Dorrin Sotoudeh dorrin-sot @@ -216,6 +220,11 @@ Vaibhav Patel <98279986+noobCoderVP@users.noreply.github.com> ProCoderVP Varad Gupta <114755221+vr-varad@users.noreply.github.com> Varad Gupta vr-varad +Vinit Pandit <106718914+MeastroZI@users.noreply.github.com> <106718914+Vinit-Pandit@users.noreply.github.com> + +Vivek Maurya <155618190+vivekmaurya001@users.noreply.github.com> +Vivek Maurya vivekmaurya001 + # Y Yaswanth Kosuru <116426380+yaswanthkosuru@users.noreply.github.com> yaswanth diff --git a/CONTRIBUTORS b/CONTRIBUTORS index 173c07b086cb..aedb14802ac0 100644 --- a/CONTRIBUTORS +++ b/CONTRIBUTORS @@ -27,6 +27,8 @@ Daniel Killenberger Daniel Yu <40680511+Daniel777y@users.noreply.github.com> Debashis Maharana Desh Deepak Kant <118960904+DeshDeepakKant@users.noreply.github.com> +Dev Goel <135586571+corsairier@users.noreply.github.com> +Dhruv Arvind Singh <154677013+DhruvArvindSingh@users.noreply.github.com> Divyansh Seth <59174836+sethdivyansh@users.noreply.github.com> Dominic Lim <46486515+domlimm@users.noreply.github.com> Dominik Moritz @@ -49,6 +51,7 @@ Joey Reed Jordan Gallivan <115050475+Jordan-Gallivan@users.noreply.github.com> Joris Labie Justin Dennison +Karan Anand <119553199+anandkaranubc@users.noreply.github.com> Karthik Prakash <116057817+skoriop@users.noreply.github.com> Kohantika Nath <145763549+kohantikanath@users.noreply.github.com> Krishnendu Das <86651039+itskdhere@users.noreply.github.com> @@ -117,7 +120,7 @@ UtkershBasnet <119008923+UtkershBasnet@users.noreply.github.com> Vaibhav Patel <98279986+noobCoderVP@users.noreply.github.com> Varad Gupta Vinit Pandit <106718914+MeastroZI@users.noreply.github.com> -Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com> +Vivek Maurya Xiaochuan Ye Yaswanth Kosuru <116426380+yaswanthkosuru@users.noreply.github.com> Yernar Yergaziyev diff --git a/NOTICE b/NOTICE index e6e7482f21fd..cbd3a299d947 100644 --- a/NOTICE +++ b/NOTICE @@ -1 +1 @@ -Copyright (c) 2016-2024 The Stdlib Authors. +Copyright (c) 2016-2025 The Stdlib Authors. diff --git a/README.md b/README.md index 98d0d1ce7fa2..403bb4af67ef 100644 --- a/README.md +++ b/README.md @@ -77,9 +77,10 @@ Thank you for being a part of our community! Your support is invaluable to us! ### External Resources -- [**Open Collective**][open-collective-stdlib] -- [**Twitter**][stdlib-twitter] -- [**Gitter**][stdlib-gitter] +- [**Google Calendar**][stdlib-public-calendar]: calendar of public events, including [open office hours][stdlib-office-hours]. +- [**Open Collective**][open-collective-stdlib]: financially support the project. +- [**Twitter**][stdlib-twitter]: follow us on social media. +- [**Gitter**][stdlib-gitter]: chat with project maintainers and other community members. ## Features @@ -182,11 +183,11 @@ While this project's installation instructions defaults to using [npm][npm] for - I would like to include stdlib functionality by just using a `script` tag. - I would like to use ES Modules. - + - Use an individual package's ES Module [build](#install_env_builds_esm). - + - I would like to use a pre-built bundle (possibly via a CDN, such as [unpkg][unpkg] or [jsDelivr][jsdelivr]). - + - Install (or consume via a CDN) an individual package's pre-built UMD [browser bundle](#install_env_builds_umd). - I am interested in using a substantial amount of functionality found in a top-level stdlib namespace and don't want to separately install hundreds of individual packages (e.g., if building an on-line calculator application and wanting all of stdlib's math functionality). @@ -200,9 +201,9 @@ While this project's installation instructions defaults to using [npm][npm] for - I am interested in using various functionality found in stdlib. - Install [individual packages](#install_individual_packages). Installing the entire project is likely unnecessary and will lead to slower installation times. - + - I would like to **vendor** stdlib functionality and avoid dependency trees. - + - Install individual package UMD [bundles](#install_env_builds_nodejs). - I am interested in using a _substantial_ amount of functionality found in a top-level stdlib namespace and don't want to separately install hundreds of individual packages. @@ -611,7 +612,7 @@ See [LICENSE][stdlib-license]. ## Copyright -Copyright © 2016-2024. The Stdlib [Authors][stdlib-authors]. +Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors]. @@ -658,6 +659,10 @@ Copyright © 2016-2024. The Stdlib [Authors][stdlib-authors]. [![Chat][chat-image]][chat-url] +Have something you want to discuss? In addition to the community chat, we hold regular [office hours][stdlib-office-hours] over video conferencing, which is a great opportunity to ask questions, share ideas, and engage directly with the stdlib team. + +You can also subscribe to our [project calendar][stdlib-public-calendar] to stay informed about the latest public community events. + @@ -779,6 +784,10 @@ Test and build infrastructure is generously provided by the following services: [stdlib-code-coverage]: https://codecov.io/github/stdlib-js/stdlib/branch/develop +[stdlib-public-calendar]: https://calendar.google.com/calendar/embed?src=a72677fe2820c833714b8b9a2aa87393f742bcaf0d0f6c9499eee6661795eae0%40group.calendar.google.com + +[stdlib-office-hours]: https://github.com/stdlib-js/meetings/issues?q=sort%3Aupdated-desc%20is%3Aissue%20is%3Aopen%20label%3A%22Office%20Hours%22 + [open-collective-stdlib]: https://opencollective.com/stdlib [stdlib-twitter]: https://twitter.com/stdlibjs diff --git a/docs/git-notes/02cbff35d876dcea7efd41794f414c7df5eddca4.txt b/docs/git-notes/02cbff35d876dcea7efd41794f414c7df5eddca4.txt new file mode 100644 index 000000000000..ab61fda3aa91 --- /dev/null +++ b/docs/git-notes/02cbff35d876dcea7efd41794f414c7df5eddca4.txt @@ -0,0 +1,14 @@ +--- +type: amend-message +--- +refactor!: update `blas/ext/base/dapx` to follow current project conventions + +BREAKING CHANGE: + +- `c_dapx()` renamed to `stdlib_strided_dapx()` +- `c_dapx_ndarray()` renamed to `stdlib_strided_dapx_ndarray()` + +All downstream usage of the old `c_dapx*` symbols must be updated to use the new symbols. + +PR-URL: https://github.com/stdlib-js/stdlib/pull/4737 +Reviewed-by: Philipp Burckhardt diff --git a/docs/git-notes/133c5394889b68952968cd6f4ff192f9692deb9f.txt b/docs/git-notes/133c5394889b68952968cd6f4ff192f9692deb9f.txt new file mode 100644 index 000000000000..267d726a6755 --- /dev/null +++ b/docs/git-notes/133c5394889b68952968cd6f4ff192f9692deb9f.txt @@ -0,0 +1,10 @@ +--- +type: amend-message +--- +docs: update namespace TypeScript declaration comments + +PR-URL: https://github.com/stdlib-js/stdlib/pull/4487 + +Co-authored-by: Philipp Burckhardt +Reviewed-by: Philipp Burckhardt +Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> diff --git a/docs/git-notes/4b1f53de18bc03af6439de1e3797d9e222ecdf28.txt b/docs/git-notes/4b1f53de18bc03af6439de1e3797d9e222ecdf28.txt new file mode 100644 index 000000000000..6fcd733a66f1 --- /dev/null +++ b/docs/git-notes/4b1f53de18bc03af6439de1e3797d9e222ecdf28.txt @@ -0,0 +1,10 @@ +--- +type: amend-message +--- +docs: update namespace TypeScript declaration comments + +PR-URL: https://github.com/stdlib-js/stdlib/pull/4518 + +Co-authored-by: Philipp Burckhardt +Reviewed-by: Philipp Burckhardt +Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com> diff --git a/lib/node_modules/@stdlib/_tools/doctest/compare-values/lib/main.js b/lib/node_modules/@stdlib/_tools/doctest/compare-values/lib/main.js index 8fe537005181..997119c98666 100644 --- a/lib/node_modules/@stdlib/_tools/doctest/compare-values/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/doctest/compare-values/lib/main.js @@ -25,33 +25,57 @@ var epsdiff = require( '@stdlib/math/base/utils/float64-epsilon-difference' ); var indexOf = require( '@stdlib/utils/index-of' ); var typeOf = require( '@stdlib/utils/type-of' ); var deepEqual = require( '@stdlib/assert/deep-equal' ); -var isNull = require( '@stdlib/assert/is-null' ); + +// Note: keep in alphabetical order var isArray = require( '@stdlib/assert/is-array' ); -var isNumber = require( '@stdlib/assert/is-number' ); -var isObject = require( '@stdlib/assert/is-object' ); -var isSymbol = require( '@stdlib/assert/is-symbol' ); -var isUndefined = require( '@stdlib/assert/is-undefined' ); -var isObjectArray = require( '@stdlib/assert/is-object-array' ); +var isArrayBuffer = require( '@stdlib/assert/is-arraybuffer' ); +var isBigInt = require( '@stdlib/assert/is-bigint' ); +var isBigInt64Array = require( '@stdlib/assert/is-bigint64array' ); +var isBigUint64Array = require( '@stdlib/assert/is-biguint64array' ); var isBoolean = require( '@stdlib/assert/is-boolean' ); -var isString = require( '@stdlib/assert/is-string' ); -var isRegExp = require( '@stdlib/assert/is-regexp' ); -var isEmptyString = require( '@stdlib/assert/is-empty-string' ); +var isBooleanArray = require( '@stdlib/assert/is-booleanarray' ); +var isBoxedPrimitive = require( '@stdlib/assert/is-boxed-primitive' ); +var isBuffer = require( '@stdlib/assert/is-buffer' ); var isComplex64 = require( '@stdlib/assert/is-complex64' ); -var isComplex128 = require( '@stdlib/assert/is-complex128' ); var isComplex64Array = require( '@stdlib/assert/is-complex64array' ); +var isComplex128 = require( '@stdlib/assert/is-complex128' ); var isComplex128Array = require( '@stdlib/assert/is-complex128array' ); -var isBoxedPrimitive = require( '@stdlib/assert/is-boxed-primitive' ); -var isPrimitive = require( '@stdlib/assert/is-primitive' ); -var isObjectLike = require( '@stdlib/assert/is-object-like' ); +var isComplexTypedArray = require( '@stdlib/assert/is-complex-typed-array' ); +var isDataView = require( '@stdlib/assert/is-dataview' ); +var isDateObject = require( '@stdlib/assert/is-date-object' ); +var isEmptyString = require( '@stdlib/assert/is-empty-string' ); +var isError = require( '@stdlib/assert/is-error' ); +var isEvalError = require( '@stdlib/assert/is-eval-error' ); +var isFloat32Array = require( '@stdlib/assert/is-float32array' ); +var isFloat64Array = require( '@stdlib/assert/is-float64array' ); var isFunction = require( '@stdlib/assert/is-function' ); +var isInt8Array = require( '@stdlib/assert/is-int8array' ); +var isInt16Array = require( '@stdlib/assert/is-int16array' ); +var isInt32Array = require( '@stdlib/assert/is-int32array' ); +var isMultiSlice = require( '@stdlib/assert/is-multi-slice' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var isNull = require( '@stdlib/assert/is-null' ); +var isNumber = require( '@stdlib/assert/is-number' ); +var isObject = require( '@stdlib/assert/is-object' ); +var isObjectArray = require( '@stdlib/assert/is-object-array' ); +var isObjectLike = require( '@stdlib/assert/is-object-like' ); +var isPrimitive = require( '@stdlib/assert/is-primitive' ); +var isReferenceError = require( '@stdlib/assert/is-reference-error' ); +var isRangeError = require( '@stdlib/assert/is-range-error' ); +var isRegExp = require( '@stdlib/assert/is-regexp' ); +var isSlice = require( '@stdlib/assert/is-slice' ); +var isString = require( '@stdlib/assert/is-string' ); +var isSymbol = require( '@stdlib/assert/is-symbol' ); +var isSyntaxError = require( '@stdlib/assert/is-syntax-error' ); var isTypedArray = require( '@stdlib/assert/is-typed-array' ); -var isError = require( '@stdlib/assert/is-error' ); var isTypeError = require( '@stdlib/assert/is-type-error' ); -var isSyntaxError = require( '@stdlib/assert/is-syntax-error' ); -var isReferenceError = require( '@stdlib/assert/is-reference-error' ); +var isUint8Array = require( '@stdlib/assert/is-uint8array' ); +var isUint8ClampedArray = require( '@stdlib/assert/is-uint8clampedarray' ); +var isUint16Array = require( '@stdlib/assert/is-uint16array' ); +var isUint32Array = require( '@stdlib/assert/is-uint32array' ); +var isUndefined = require( '@stdlib/assert/is-undefined' ); var isURIError = require( '@stdlib/assert/is-uri-error' ); -var isEvalError = require( '@stdlib/assert/is-eval-error' ); -var isRangeError = require( '@stdlib/assert/is-range-error' ); + var startsWith = require( '@stdlib/string/starts-with' ); var contains = require( '@stdlib/assert/contains' ); var endsWith = require( '@stdlib/string/ends-with' ); @@ -61,6 +85,12 @@ var replace = require( '@stdlib/string/replace' ); var trim = require( '@stdlib/string/trim' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); +var reinterpretComplex = require( '@stdlib/strided/base/reinterpret-complex' ); +var copyArray = require( '@stdlib/array/base/copy' ); var createAnnotationValue = require( '@stdlib/_tools/doctest/create-annotation-value' ); var parse = require( './parse.js' ); @@ -159,82 +189,189 @@ function checkPrimitive( actual, expected ) { * @returns {boolean} boolean indicating whether type annotation matches the actual output */ function checkForPlaceholders( actual, expected ) { + // Note: keep in alphabetical order... switch ( expected ) { + case '': + return isArray( actual ); + case '': + return isArrayBuffer( actual ); + case '': + return isBigInt( actual ); + case '': + return isBigInt64Array( actual ); + case '': + return isBigUint64Array( actual ); case '': case '': return isBoolean( actual ); - case '': - case '': - return isString( actual ); - case '': - case '': - return isNumber( actual ); - case '': - case '': - return isSymbol( actual ); - case '': - return isObjectArray( actual ); - case '': - case '': - return isObject( actual ); - case '': - return isArray( actual ); + case '': + return isBooleanArray( actual ); + case '': + return isBuffer( actual ); case '': return isComplex64( actual ); - case '': - return isComplex128( actual ); case '': return isComplex64Array( actual ); + case '': + return isComplex128( actual ); case '': return isComplex128Array( actual ); + case '': + return isDataView( actual ); + case '': + return isDateObject( actual ); case '': return isError( actual ); - case '': - return isTypeError( actual ); - case '': - return isSyntaxError( actual ); - case '': - return isReferenceError( actual ); - case '': - return isURIError( actual ); case '': return isEvalError( actual ); + case '': + return isFloat32Array( actual ); + case '': + return isFloat64Array( actual ); + case '': + return isFunction( actual ); + case '': + return isInt8Array( actual ); + case '': + return isInt16Array( actual ); + case '': + return isInt32Array( actual ); + case '': + return isMultiSlice( actual ); + case '': + return isndarrayLike( actual ); + case '': + case '': + return isNumber( actual ); + case '': // note: exception to alphabetical rule + case '': + return isObject( actual ); + case '': + return isObjectArray( actual ); case '': return isRangeError( actual ); + case '': + return isRegExp( actual ); + case '': + return isReferenceError( actual ); + case '': + return isSlice( actual ); + case '': + case '': + return isString( actual ); + case '': + case '': + return isSymbol( actual ); + case '': + return isSyntaxError( actual ); + case '': + return isTypeError( actual ); + case '': + return isTypedArray( actual ); + case '': + return isUint8Array( actual ); + case '': + return isUint8ClampedArray( actual ); + case '': + return isUint16Array( actual ); + case '': + return isUint32Array( actual ); + case '': + return isURIError( actual ); default: - // Uknown type, let it slide... + // Unknown type, let it slide... + + // TODO: should we compare constructor names here at a minimum? or perhaps walk the prototype tree and compare constructor names to determine whether a value is an instance of? return true; } } /** -* For a typed array, if the return annotation asserts deep instance equality, check whether it corresponds to the actual value; otherwise, check whether the return annotation signals the correct type. +* Compares a list of expected entries with a list of actual values. +* +* @private +* @param {Collection} actual - list of actual values +* @param {Collection} expected - list of expected values +* @returns {(string|null)} result +*/ +function compareEntries( actual, expected ) { + var i; + if ( actual.length !== expected.length ) { + return 'Expected entries ['+expected+'], but observed ['+actual+']'; + } + for ( i = 0; i < expected.length; i++ ) { + if ( !checkPrimitive( actual[ i ], String( expected[ i ] ) ) ) { + return 'Expected entries ['+expected+'], but observed ['+actual+']'; + } + } + return null; +} + +/** +* Checks whether a complex number matches the expected return annotation. * * @private * @param {*} actual - actual return value * @param {string} expected - return value annotation -* @returns {(string|null)} error message in case the annotation and value do not match, `null` otherwise +* @returns {(string|null)} error message or null +*/ +function checkComplex( actual, expected ) { + var entries; + var match; + var type; + + match = RE_INSTANCE_ANNOTATION.exec( expected ); + if ( match ) { + type = match[ 1 ]; + entries = match[ 2 ]; + if ( actual.constructor.name !== type ) { + return 'Expected instance type <'+type+'>, but observed <'+actual.constructor.name+'>'; + } + if ( entries ) { + if ( isComplex128( actual ) ) { + actual = [ real( actual ), imag( actual ) ]; + } else if ( isComplex64( actual ) ) { + actual = [ realf( actual ), imagf( actual ) ]; + } + return compareEntries( actual, parse( entries ) ); + } + return null; + } + return 'Complex numbers should be documented using instance annotation'; +} + +/** +* Checks whether a typed array matches the expected return annotation. +* +* ## Notes +* +* - If the return annotation asserts deep instance equality, check whether it corresponds to the actual value. +* - Otherwise, check whether the return annotation signals the correct type. +* +* @private +* @param {*} actual - actual return value +* @param {string} expected - return value annotation +* @returns {(string|null)} error message or null */ function checkTypedArrays( actual, expected ) { var entries; var match; var type; - var i; match = RE_INSTANCE_ANNOTATION.exec( expected ); if ( match ) { type = match[ 1 ]; entries = match[ 2 ]; if ( actual.constructor.name !== type ) { - return 'Expected instance type <'+actual.constructor.name+'>, but observed <'+type+'>'; + return 'Expected instance type <'+type+'>, but observed <'+actual.constructor.name+'>'; } if ( entries ) { - entries = parse( entries ); - for ( i = 0; i < entries.length; i++ ) { - if ( !checkPrimitive( actual[ i ], String( entries[ i ] ) ) ) { - return 'Expected array entries ['+entries+'], but observed ['+actual+']'; - } + if ( isComplexTypedArray( actual ) ) { + actual = reinterpretComplex( actual, 0 ); + } else if ( isBooleanArray( actual ) ) { + actual = copyArray( actual ); } + return compareEntries( actual, parse( entries ) ); } return null; } @@ -353,7 +490,6 @@ function compareValues( actual, expected ) { // Early return since we cannot compare actual value to return annotation value: return null; } - if ( startsWith( expected, '<' ) && endsWith( expected, '>' ) ) { if ( !checkForPlaceholders( actual, expected ) ) { return 'Expected a '+expected+', but received: `'+actual+'`'; @@ -385,28 +521,35 @@ function compareValues( actual, expected ) { if ( !checkPrimitive( actual, expected ) ) { return 'Displayed return value is `'+expected+'`, but expected `'+actual+'` instead'; } + return null; } - else if ( isTypedArray( actual ) ) { + if ( isTypedArray( actual ) || isComplexTypedArray( actual ) || isBooleanArray( actual ) ) { return checkTypedArrays( actual, expected ); } if ( isArray( actual ) ) { if ( !checkArray( actual, expected ) ) { return 'Displayed return value is `'+expected+'`, but expected `'+createAnnotationValue( actual )+'` instead'; } + return null; } - else if ( isRegExp( actual ) ) { + if ( isComplex64( actual ) || isComplex128( actual ) ) { + return checkComplex( actual, expected ); + } + if ( isRegExp( actual ) ) { actual = actual.toString(); if ( actual !== expected ) { return 'Displayed return value is `'+expected+'`, but expected `'+actual+'` instead'; } + return null; } - else if ( isFunction( actual ) ) { + if ( isFunction( actual ) ) { actual = actual.toString(); if ( actual !== expected ) { return 'Displayed return value is `'+expected+'`, but expected `'+actual+'` instead'; } + return null; } - else if ( isObjectLike( actual ) ) { + if ( isObjectLike( actual ) ) { if ( !contains( expected, '...' ) ) { try { expectedValue = parse( expected ); @@ -419,6 +562,7 @@ function compareValues( actual, expected ) { return 'Displayed return value is `'+expected+'`, but expected `'+actualString+'` instead'; } } + return null; } return null; } diff --git a/lib/node_modules/@stdlib/_tools/doctest/compare-values/test/test.js b/lib/node_modules/@stdlib/_tools/doctest/compare-values/test/test.js index 99c125c0d734..8e0aff9d4741 100644 --- a/lib/node_modules/@stdlib/_tools/doctest/compare-values/test/test.js +++ b/lib/node_modules/@stdlib/_tools/doctest/compare-values/test/test.js @@ -29,6 +29,8 @@ var Complex64 = require( '@stdlib/complex/float32/ctor' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var BooleanArray = require( '@stdlib/array/bool' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); var compareValues = require( './../lib' ); @@ -42,6 +44,7 @@ function createErrorMessage( actual, expected ) { // TESTS // tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); t.strictEqual( typeof compareValues, 'function', 'main export is a function' ); t.end(); }); @@ -290,24 +293,78 @@ tape( 'the function compares a typed array and a corresponding return annotation actual = new Float64Array( [ 0, 2, 3 ] ); expected = '[ 0, 2, 2 ]'; - msg = 'Expected array entries [0,2,2], but observed [0,2,3]'; + msg = 'Expected entries [0,2,2], but observed [0,2,3]'; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); actual = new Float64Array( [ 0, 2, 3 ] ); expected = '[ 0, 2, 2 ]'; - msg = 'Expected instance type , but observed '; + msg = 'Expected instance type , but observed '; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] ); actual = new Complex64Array( buf ); - expected = ''; + expected = '[ 1.0, -1.0, 2.0, -2.0 ]'; t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] ); actual = new Complex128Array( buf ); - expected = ''; + expected = '[ 1.0, -1.0, 2.0, -2.0 ]'; t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); + buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] ); + actual = new Complex128Array( buf ); + expected = '[ 1.0, 1.0, 2.0, 2.0 ]'; + msg = 'Expected entries [1,1,2,2], but observed [1,-1,2,-2]'; + t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); + + actual = new BooleanArray( [ true, false, true, false ] ); + expected = '[ true, false, true, false ]'; + t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); + + actual = new BooleanArray( [ true, false, true, false ] ); + expected = '[ true, true, true, true ]'; + msg = 'Expected entries [true,true,true,true], but observed [true,false,true,false]'; + t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); + + t.end(); +}); + +tape( 'the function compares a complex number and a corresponding return annotation', function test( t ) { + var expected; + var actual; + var msg; + + actual = new Complex64( 2.0, 3.0 ); + expected = ''; + t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); + + actual = new Complex64( 2.0, 3.0 ); + expected = '[ 2.0, 3.0 ]'; + t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); + + actual = new Complex64( 2.0, 3.0 ); + expected = '[ 2.0, 4.0 ]'; + msg = 'Expected entries [2,4], but observed [2,3]'; + t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); + + actual = new Complex128( 2.0, 3.0 ); + expected = ''; + t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); + + actual = new Complex128( 2.0, 3.0 ); + expected = '[ 2.0, 3.0 ]'; + t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); + + actual = new Complex128( 2.0, 3.0 ); + expected = '[ 2.0, 4.0 ]'; + msg = 'Expected entries [2,4], but observed [2,3]'; + t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); + + actual = new Complex64( 2.0, 3.0 ); + expected = '[ 2.0, 3.0 ]'; + msg = 'Expected instance type , but observed '; + t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); + t.end(); }); @@ -344,12 +401,12 @@ tape( 'the function compares a value with a type equality return annotation', fu msg = 'Expected a , but received: `0`'; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); - actual = new Complex64( 2.0, 3.0 ); - expected = ''; + actual = new ArrayBuffer( 10 ); + expected = ''; t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); - actual = new Complex128( 2.0, 3.0 ); - expected = ''; + actual = compareValues; + expected = ''; t.strictEqual( compareValues( actual, expected ), null, 'returns null' ); t.end(); @@ -369,7 +426,7 @@ tape( 'the function differentiates between boxed and primitive values', function msg = 'Expected a , but received an unboxed primitive: `2.3`'; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); - actual = new Number( 2.3 ); // eslint-disable-line no-new-wrappers + actual = new Number( 2.3 ); expected = ''; msg = 'Expected a , but received a boxed primitive: `2.3`'; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); @@ -393,7 +450,7 @@ tape( 'the function differentiates between boxed and primitive values', function msg = 'Expected a , but received an unboxed primitive: `false`'; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); - actual = new Boolean( false ); // eslint-disable-line no-new-wrappers + actual = new Boolean( false ); expected = ''; msg = 'Expected a , but received a boxed primitive: `false`'; t.strictEqual( compareValues( actual, expected ), msg, 'returns expected message' ); diff --git a/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/lib/main.js b/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/lib/main.js index 8ba4676ad4b8..50d00828fab5 100644 --- a/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/lib/main.js @@ -20,27 +20,33 @@ // MODULES // +// Note: keep in alphabetical order +var isArray = require( '@stdlib/assert/is-array' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ); +var isBooleanArray = require( '@stdlib/assert/is-booleanarray' ); var isBoxedPrimitive = require( '@stdlib/assert/is-boxed-primitive' ); -var isTypedArray = require( '@stdlib/assert/is-typed-array' ); +var isComplexTypedArray = require( '@stdlib/assert/is-complex-typed-array' ); +var isError = require( '@stdlib/assert/is-error' ); var isInfinite = require( '@stdlib/assert/is-infinite' ); -var isPrimitive = require( '@stdlib/assert/is-primitive' ); -var isBoolean = require( '@stdlib/assert/is-boolean' ); var isInteger = require( '@stdlib/assert/is-integer' ); +var isnan = require( '@stdlib/assert/is-nan' ); +var isNull = require( '@stdlib/assert/is-null' ); var isNumber = require( '@stdlib/assert/is-number' ); -var isString = require( '@stdlib/assert/is-string' ); -var isArray = require( '@stdlib/assert/is-array' ); -var isError = require( '@stdlib/assert/is-error' ); var isObject = require( '@stdlib/assert/is-object' ); +var isPrimitive = require( '@stdlib/assert/is-primitive' ); var isRegExp = require( '@stdlib/assert/is-regexp' ); +var isString = require( '@stdlib/assert/is-string' ); +var isTypedArray = require( '@stdlib/assert/is-typed-array' ); var isUndefined = require( '@stdlib/assert/is-undefined' ); -var isNull = require( '@stdlib/assert/is-null' ); -var isnan = require( '@stdlib/assert/is-nan' ); + var capitalize = require( '@stdlib/string/capitalize' ); var roundn = require( '@stdlib/math/base/special/roundn' ); var floor = require( '@stdlib/math/base/special/floor' ); var constructorName = require( '@stdlib/utils/constructor-name' ); var objectKeys = require( '@stdlib/utils/keys' ); var typeOf = require( '@stdlib/utils/type-of' ); +var reinterpretComplex = require( '@stdlib/strided/base/reinterpret-complex' ); +var copyArray = require( '@stdlib/array/base/copy' ); var validate = require( './validate.js' ); @@ -131,35 +137,43 @@ function genericAnnotation( actual, opts ) { var keys; var out; var end; + var f; var i; if ( isPrimitive( actual ) ) { return primitiveAnnotation( actual, opts ); } - if ( isTypedArray( actual ) ) { + if ( isTypedArray( actual ) || isComplexTypedArray( actual ) || isBooleanArray( actual ) ) { out = '<'+actual.constructor.name+'>'; if ( actual.length === 0 ) { out += '[]'; return out; } + f = numberAnnotation; + if ( isComplexTypedArray( actual ) ) { + actual = reinterpretComplex( actual, 0 ); + } else if ( isBooleanArray( actual ) ) { + actual = copyArray( actual ); + f = genericAnnotation; + } out += '[ '; - out += numberAnnotation( actual[ 0 ], opts ); + out += f( actual[ 0 ], opts ); if ( actual.length > opts.numel ) { end = floor( opts.numel / 2 ); for ( i = 1; i < end; i++ ) { out += ', '; - out += numberAnnotation( actual[ i ], opts ); + out += f( actual[ i ], opts ); } out += ', ...'; for ( i = actual.length - end; i < actual.length; i++ ) { out += ', '; - out += numberAnnotation( actual[ i ], opts ); + out += f( actual[ i ], opts ); } } else { for ( i = 1; i < actual.length; i++ ) { out += ', '; - out += numberAnnotation( actual[ i ], opts ); + out += f( actual[ i ], opts ); } } out += ' ]'; diff --git a/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/test/test.js b/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/test/test.js index f57e20fa3471..0030afdb4f45 100644 --- a/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/test/test.js +++ b/lib/node_modules/@stdlib/_tools/doctest/create-annotation-value/test/test.js @@ -32,12 +32,14 @@ var Complex64 = require( '@stdlib/complex/float32/ctor' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); var Complex64Array = require( '@stdlib/array/complex64' ); var Complex128Array = require( '@stdlib/array/complex128' ); +var BooleanArray = require( '@stdlib/array/bool' ); var createAnnotationValue = require( './../lib' ); // TESTS // tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); t.strictEqual( typeof createAnnotationValue, 'function', 'main export is a function' ); t.end(); }); @@ -203,7 +205,7 @@ tape( 'the function creates a type annotation value for boxed primitives', funct 'type': true }; - val = new Number( 1/3 ); // eslint-disable-line no-new-wrappers + val = new Number( 1/3 ); expected = ''; t.strictEqual( createAnnotationValue( val, opts ), expected, 'returns expected value' ); @@ -211,7 +213,7 @@ tape( 'the function creates a type annotation value for boxed primitives', funct expected = ''; t.strictEqual( createAnnotationValue( val, opts ), expected, 'returns expected value' ); - val = new Boolean( false ); // eslint-disable-line no-new-wrappers + val = new Boolean( false ); expected = ''; t.strictEqual( createAnnotationValue( val, opts ), expected, 'returns expected value' ); @@ -307,6 +309,20 @@ tape( 'the function creates a deep instance equality annotation value for typed expected = '[ ~0.333, 0.5, 1 ]'; t.strictEqual( createAnnotationValue( val, opts ), expected, 'returns expected value' ); + val = new Complex64Array( [ 1, 2, 3, 4, 5, 6, 7, 8 ] ); + opts = { + 'numel': 6 + }; + expected = '[ 1, 2, 3, ..., 6, 7, 8 ]'; + t.strictEqual( createAnnotationValue( val, opts ), expected, 'returns expected value' ); + + val = new BooleanArray( [ true, false, true, false ] ); + opts = { + 'numel': 6 + }; + expected = '[ true, false, true, false ]'; + t.strictEqual( createAnnotationValue( val, opts ), expected, 'returns expected value' ); + t.end(); }); @@ -384,6 +400,10 @@ tape( 'the function creates a type annotation for class instances', function tes expected = ''; t.strictEqual( createAnnotationValue( actual, opts ), expected, 'returns expected value' ); + actual = new BooleanArray( [ true, false, true, false ] ); + expected = ''; + t.strictEqual( createAnnotationValue( actual, opts ), expected, 'returns expected value' ); + actual = noop; expected = ''; t.strictEqual( createAnnotationValue( actual, opts ), expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/_tools/eslint/rules/new-cap-error/test/fixtures/invalid.js b/lib/node_modules/@stdlib/_tools/eslint/rules/new-cap-error/test/fixtures/invalid.js index d0f73ad34ce0..8092a66b83e1 100644 --- a/lib/node_modules/@stdlib/_tools/eslint/rules/new-cap-error/test/fixtures/invalid.js +++ b/lib/node_modules/@stdlib/_tools/eslint/rules/new-cap-error/test/fixtures/invalid.js @@ -83,7 +83,7 @@ test = { '', 'function sqrt( x ) {', ' if ( x < 0 ) {', - ' throw TypeError( \'must provide a non-negative number\' );', + ' throw TypeError( \'must provide a nonnegative number\' );', ' }', ' return Math.sqrt( x );', '}' @@ -99,7 +99,7 @@ test = { '', 'function sqrt( x ) {', ' if ( x < 0 ) {', - ' throw new TypeError( \'must provide a non-negative number\' );', + ' throw new TypeError( \'must provide a nonnegative number\' );', ' }', ' return Math.sqrt( x );', '}' diff --git a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/README.md b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/README.md index c6bc1a2448a0..2d4de5d418cc 100644 --- a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/README.md +++ b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/README.md @@ -38,7 +38,7 @@ var rule = require( '@stdlib/_tools/eslint/rules/repl-namespace-order' ); #### rule -[ESLint rule][eslint-rules] to enforce that packages are added to a REPL namespace object in alphabetical order according to alias (namespace key). +[ESLint rule][eslint-rules] to enforce that packages are added to a REPL namespace object in alphabetical order according to alias (namespace key). **Bad**: @@ -117,8 +117,6 @@ var result; var code; code = [ - '/* eslint-enable stdlib/repl-namespace-order */', - '', '/* When adding names to the namespace, ensure that they are added in alphabetical order according to alias (namespace key). */', '', 'ns.push({', diff --git a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/examples/index.js b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/examples/index.js index 789d95dc36b9..fcff2649d875 100644 --- a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/examples/index.js +++ b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/examples/index.js @@ -26,8 +26,6 @@ var result; var code; code = [ - '/* eslint-enable stdlib/repl-namespace-order */', - '', '/* When adding names to the namespace, ensure that they are added in alphabetical order according to alias (namespace key). */', '', 'ns.push({', diff --git a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/lib/main.js b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/lib/main.js index f451656f02a5..a75bd4e8b64d 100644 --- a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/lib/main.js @@ -37,43 +37,81 @@ var OPTS_COMPARE = { * @returns {Object} validators */ function main( context ) { + var expressions; var prevAlias; - return { - 'ObjectExpression': validate - }; + expressions = []; /** - * Checks whether packages are added to a REPL namespace object in alphabetical order according to alias (namespace key). + * Extracts the alias value from a given node. * * @private - * @param {ASTNode} node - node to examine + * @param {ASTNode} node - node containing properties to search + * @returns {string} alias value */ - function validate( node ) { - var properties; + function getAlias( node ) { + var props; var alias; - var prop; var i; - properties = node.properties; - for ( i = 0; i < properties.length; i++ ) { - prop = properties[ i ]; - if ( prop.key.value === 'alias' ) { - alias = prop.value.value; + props = node.properties; + for ( i = 0; i < props.length; i++ ) { + if ( props[ i ].key.value === 'alias' ) { + alias = props[ i ].value.value; if ( alias ) { - if ( - prevAlias && - alias.localeCompare( prevAlias, 'en', OPTS_COMPARE ) < 0 ) - { - report( prevAlias, alias, node ); - } else { - prevAlias = alias; - } + return alias; } } } } + /** + * Compares two nodes and determines their order based on the alias property. + * + * @private + * @param {ASTNode} a - first node + * @param {ASTNode} b - second node + * @returns {number} number indicating sort order + */ + function sortExpressions( a, b ) { + var aliasA = getAlias( a.arguments[ 0 ] ); + var aliasB = getAlias( b.arguments[ 0 ] ); + return aliasA.localeCompare( aliasB, 'en', OPTS_COMPARE ); + } + + /** + * Fixes the lint error by reordering the packages. + * + * @private + * @param {Function} fixer - ESLint fixer + * @returns {(Object|null)} fix or null + */ + function fix( fixer ) { + var replacingText; + var startRange; + var endRange; + var sorted; + var source; + var txt; + var i; + + source = context.getSourceCode(); + replacingText = ''; + startRange = expressions[0].range[ 0 ]; + endRange = expressions[ expressions.length - 1 ].range[ 1 ]; + + sorted = expressions.slice().sort( sortExpressions ); + + for ( i = 0; i < sorted.length; i++ ) { + txt = source.getText( sorted[ i ] ); + replacingText += txt; + if ( i < sorted.length - 1 ) { + replacingText += ';\n\n'; + } + } + return fixer.replaceTextRange( [ startRange, endRange ], replacingText ); // eslint-disable-line max-len + } + /** * Reports the error message. * @@ -85,9 +123,62 @@ function main( context ) { function report( last, current, node ) { context.report({ 'node': node, - 'message': '"'+current+'" should come before "'+last+'"' + 'message': '"'+current+'" should come before "'+last+'"', + 'fix': fix }); } + + /** + * Checks whether the packages are added to a REPL namespace object in alphabetical order according to alias (namespace key). + * + * @private + */ + function validate() { + var alias; + var i; + + for ( i = 0; i < expressions.length; i++ ) { + alias = getAlias( expressions[ i ].arguments[ 0 ] ); + if ( + prevAlias && + alias.localeCompare( prevAlias, 'en', OPTS_COMPARE ) < 0 + ) { + report( prevAlias, alias, expressions[ i ].arguments[ 0 ] ); + } else { + prevAlias = alias; + } + } + } + + /** + * Collects all expressions which add a package to a REPL namespace. + * + * @private + * @param {ASTNode} node - node to examine + */ + function collectExpressions( node ) { + var object; + var alias; + + if ( + node.callee.type === 'MemberExpression' && + node.callee.object.name === 'ns' && + node.callee.property.name === 'push' + ) { + object = node.arguments[ 0 ]; + if ( object.type === 'ObjectExpression' ) { + alias = getAlias( object ); + if ( alias ) { + expressions.push( node ); + } + } + } + } + + return { + 'CallExpression': collectExpressions, + 'Program:exit': validate + }; } @@ -95,9 +186,11 @@ function main( context ) { rule = { 'meta': { + 'type': 'suggestion', 'docs': { 'description': 'enforce that packages are added to a REPL namespace object in alphabetical order according to alias (namespace key)' }, + 'fixable': 'code', 'schema': [] }, 'create': main diff --git a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/test/fixtures/invalid.js b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/test/fixtures/invalid.js index ca56212d2543..babaf0a3aad2 100644 --- a/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/test/fixtures/invalid.js +++ b/lib/node_modules/@stdlib/_tools/eslint/rules/repl-namespace-order/test/fixtures/invalid.js @@ -58,12 +58,67 @@ test = { 'message': '"hasInt8ArraySupport" should come before "hasMapSupport"', 'type': 'ObjectExpression' } - ] + ], + 'output': [ + 'ns.push({', + ' \'alias\': \'hasInt8ArraySupport\',', + ' \'path\': \'@stdlib/assert/has-int8array-support\',', + ' \'value\': require( \'@stdlib/assert/has-int8array-support\' ),', + ' \'type\': \'Function\',', + ' \'related\': []', + '});', + '', + 'ns.push({', + ' \'alias\': \'hasInt32ArraySupport\',', + ' \'path\': \'@stdlib/assert/has-int32array-support\',', + ' \'value\': require( \'@stdlib/assert/has-int32array-support\' ),', + ' \'type\': \'Function\',', + ' \'related\': []', + '});', + '', + 'ns.push({', + ' \'alias\': \'hasMapSupport\',', + ' \'path\': \'@stdlib/assert/has-map-support\',', + ' \'value\': require( \'@stdlib/assert/has-map-support\' ),', + ' \'type\': \'Function\',', + ' \'related\': []', + '});' + ].join( '\n' ) }; invalid.push( test ); test = { 'code': [ + 'ns.push({', + ' \'alias\': \'pop\',', + ' \'path\': \'@stdlib/utils/pop\',', + ' \'value\': require( \'@stdlib/utils/pop\' ),', + ' \'type\': \'Function\',', + ' \'related\': [', + ' \'@stdlib/utils/push\',', + ' \'@stdlib/utils/shift\',', + ' \'@stdlib/utils/unshift\'', + ' ]', + '});', + '', + 'ns.push({', + ' \'alias\': \'pluck\',', + ' \'path\': \'@stdlib/utils/pluck\',', + ' \'value\': require( \'@stdlib/utils/pluck\' ),', + ' \'type\': \'Function\',', + ' \'related\': [', + ' \'@stdlib/utils/deep-pluck\',', + ' \'@stdlib/utils/pick\'', + ' ]', + '});' + ].join( '\n' ), + 'errors': [ + { + 'message': '"pluck" should come before "pop"', + 'type': 'ObjectExpression' + } + ], + 'output': [ 'ns.push({', ' \'alias\': \'pluck\',', ' \'path\': \'@stdlib/utils/pluck\',', @@ -86,14 +141,9 @@ test = { ' \'@stdlib/utils/unshift\'', ' ]', '});' - ].join( '\n' ), - 'errors': [ - { - 'message': '"hasInt32ArraySupport" should come before "hasMapSupport"', - 'type': 'ObjectExpression' - } - ] + ].join( '\n' ) }; +invalid.push( test ); test = { 'code': [ @@ -122,7 +172,28 @@ test = { 'message': '"AFINN_96" should come before "AFINN_111"', 'type': 'ObjectExpression' } - ] + ], + 'output': [ + 'ns.push({', + ' \'alias\': \'AFINN_96\',', + ' \'path\': \'@stdlib/datasets/afinn-96\',', + ' \'value\': require( \'@stdlib/datasets/afinn-96\' ),', + ' \'type\': \'Function\',', + ' \'related\': [', + ' \'@stdlib/datasets/afinn-111\'', + ' ]', + '});', + '', + 'ns.push({', + ' \'alias\': \'AFINN_111\',', + ' \'path\': \'@stdlib/datasets/afinn-111\',', + ' \'value\': require( \'@stdlib/datasets/afinn-111\' ),', + ' \'type\': \'Function\',', + ' \'related\': [', + ' \'@stdlib/datasets/afinn-96\'', + ' ]', + '});' + ].join( '\n' ) }; invalid.push( test ); diff --git a/lib/node_modules/@stdlib/array/base/README.md b/lib/node_modules/@stdlib/array/base/README.md index f9ded497e442..197c6de8c5ff 100644 --- a/lib/node_modules/@stdlib/array/base/README.md +++ b/lib/node_modules/@stdlib/array/base/README.md @@ -77,8 +77,15 @@ The namespace exports the following: - [`bbinary4d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-binary4d]: apply a binary callback to elements in two broadcasted nested input arrays and assign results to elements in a four-dimensional nested output array. - [`bbinary5d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-binary5d]: apply a binary callback to elements in two broadcasted nested input arrays and assign results to elements in a five-dimensional nested output array. - [`bquaternary2d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-quaternary2d]: apply a quaternary callback to elements in four broadcasted nested input arrays and assign results to elements in a two-dimensional nested output array. +- [`bquaternary3d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-quaternary3d]: apply a quaternary callback to elements in four broadcasted input arrays and assign results to elements in a three-dimensional nested output array. +- [`bquaternary4d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-quaternary4d]: apply a quaternary callback to elements in four broadcasted input arrays and assign results to elements in a four-dimensional nested output array. +- [`bquaternary5d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-quaternary5d]: apply a quaternary callback to elements in four broadcasted input arrays and assign results to elements in a five-dimensional nested output array. - [`bquinary2d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-quinary2d]: apply a quinary callback to elements in five broadcasted nested input arrays and assign results to elements in a two-dimensional nested output array. +- [`bquinary4d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-quinary4d]: apply a quinary callback to elements in five broadcasted input arrays and assign results to elements in a four-dimensional nested output array. - [`bternary2d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-ternary2d]: apply a ternary callback to elements in three broadcasted nested input arrays and assign results to elements in a two-dimensional nested output array. +- [`bternary3d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-ternary3d]: apply a ternary callback to elements in three broadcasted nested input arrays and assign results to elements in a three-dimensional nested output array. +- [`bternary4d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-ternary4d]: apply a ternary callback to elements in three broadcasted nested input arrays and assign results to elements in a four-dimensional nested output array. +- [`bternary5d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-ternary5d]: apply a ternary callback to elements in three broadcasted nested input arrays and assign results to elements in a five-dimensional nested output array. - [`bunary2d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-unary2d]: apply a unary callback to elements in a broadcasted nested input array and assign results to elements in a two-dimensional nested output array. - [`bunary3d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-unary3d]: apply a unary callback to elements in a broadcasted nested input array and assign results to elements in a three-dimensional nested output array. - [`bunary4d( arrays, shapes, fcn )`][@stdlib/array/base/broadcasted-unary4d]: apply a unary callback to elements in a broadcasted nested input array and assign results to elements in a four-dimensional nested output array. @@ -102,6 +109,7 @@ The namespace exports the following: - [`every( x )`][@stdlib/array/base/every]: test whether all elements in an array are truthy. - [`fancySliceAssign( x, y, s, strict )`][@stdlib/array/base/fancy-slice-assign]: assign element values from a broadcasted input array to corresponding elements in an output array. - [`fancySlice( x, s, strict )`][@stdlib/array/base/fancy-slice]: return a shallow copy of a portion of an array. +- [`fill( x, value, start, end )`][@stdlib/array/base/fill]: fill all elements within a portion of an array with a specified value. - [`filledBy( len, clbk[, thisArg] )`][@stdlib/array/base/filled-by]: create a filled "generic" array according to a provided callback function. - [`filled( value, len )`][@stdlib/array/base/filled]: create a filled "generic" array. - [`filled2dBy( shape, clbk[, thisArg] )`][@stdlib/array/base/filled2d-by]: create a filled two-dimensional nested array according to a provided callback function. @@ -144,6 +152,7 @@ The namespace exports the following: - [`groupValues( x, groups )`][@stdlib/array/base/group-values]: group elements as arrays associated with distinct keys. - [`incrspace( start, stop, increment )`][@stdlib/array/base/incrspace]: generate a linearly spaced numeric array according to a provided increment. - [`indexOf( x, searchElement, fromIndex, equalNaNs )`][@stdlib/array/base/index-of]: return the index of the first element which equals a provided search element. +- [`indicesComplement( N, indices )`][@stdlib/array/base/indices-complement]: return the complement of a list of array indices. - [`join( x, separator )`][@stdlib/array/base/join]: return a string created by joining array elements using a specified separator. - [`lastIndexOf( x, searchElement, fromIndex, equalNaNs )`][@stdlib/array/base/last-index-of]: return the index of the last element which equals a provided search element. - [`last( x )`][@stdlib/array/base/last]: return the last element of an array-like object. @@ -156,11 +165,19 @@ The namespace exports the following: - [`minSignedIntegerDataType( value )`][@stdlib/array/base/min-signed-integer-dtype]: determine the minimum array data type for storing a provided signed integer value. - [`minUnsignedIntegerDataType( value )`][@stdlib/array/base/min-unsigned-integer-dtype]: determine the minimum array data type for storing a provided unsigned integer value. - [`mskbinary2d( arrays, shape, fcn )`][@stdlib/array/base/mskbinary2d]: apply a binary callback to elements in two two-dimensional nested input arrays according to elements in a two-dimensional nested mask array and assign results to elements in a two-dimensional nested output array. +- [`mskbinary3d( arrays, shape, fcn )`][@stdlib/array/base/mskbinary3d]: apply a binary callback to elements in two three-dimensional nested input arrays according to elements in a three-dimensional nested mask array and assign results to elements in a three-dimensional nested output array. +- [`mskbinary4d( arrays, shape, fcn )`][@stdlib/array/base/mskbinary4d]: apply a binary callback to elements in two four-dimensional nested input arrays according to elements in a four-dimensional nested mask array and assign results to elements in a four-dimensional nested output array. +- [`mskbinary5d( arrays, shape, fcn )`][@stdlib/array/base/mskbinary5d]: apply a binary callback to elements in two five-dimensional nested input arrays according to elements in a five-dimensional nested mask array and assign results to elements in a five-dimensional nested output array. +- [`mskfilterMap( x, mask, clbk[, thisArg] )`][@stdlib/array/base/mskfilter-map]: apply a mask and a callback function to a provided input array. - [`mskfilter( x, mask )`][@stdlib/array/base/mskfilter]: apply a mask to a provided input array. +- [`mskfilter2( x, y, mask )`][@stdlib/array/base/mskfilter2]: apply a mask to two provided input arrays in a single pass. +- [`mskfiltern( x, [...arrays,] mask )`][@stdlib/array/base/mskfiltern]: apply a mask to one or more provided input arrays in a single pass. - [`mskput( x, mask, values, mode )`][@stdlib/array/base/mskput]: replace elements of an array with provided values according to a provided mask array. - [`mskreject( x, mask )`][@stdlib/array/base/mskreject]: apply a mask to a provided input array. - [`mskunary2d( arrays, shape, fcn )`][@stdlib/array/base/mskunary2d]: apply a unary callback to elements in a two-dimensional nested input array according to elements in a two-dimensional nested mask array and assign results to elements in a two-dimensional nested output array. - [`mskunary3d( arrays, shape, fcn )`][@stdlib/array/base/mskunary3d]: apply a unary callback to elements in a three-dimensional nested input array according to elements in a three-dimensional nested mask array and assign results to elements in a three-dimensional nested output array. +- [`mskunary4d( arrays, shape, fcn )`][@stdlib/array/base/mskunary4d]: apply a unary callback to elements in a four-dimensional nested input array according to elements in a four-dimensional nested mask array and assign results to elements in a four-dimensional nested output array. +- [`mskunary5d( arrays, shape, fcn )`][@stdlib/array/base/mskunary5d]: apply a unary callback to elements in a five-dimensional nested input array according to elements in a five-dimensional nested mask array and assign results to elements in a five-dimensional nested output array. - [`nCartesianProduct( x1, x2[, ...xN] )`][@stdlib/array/base/n-cartesian-product]: return the n-fold Cartesian product. - [`noneByRight( x, predicate[, thisArg] )`][@stdlib/array/base/none-by-right]: test whether all elements in an array fail a test implemented by a predicate function, iterating from right to left. - [`noneBy( x, predicate[, thisArg] )`][@stdlib/array/base/none-by]: test whether all elements in an array fail a test implemented by a predicate function. @@ -188,6 +205,8 @@ The namespace exports the following: - [`resolveGetter( x )`][@stdlib/array/base/resolve-getter]: return an accessor function for retrieving an element from an array-like object. - [`resolveSetter( x )`][@stdlib/array/base/resolve-setter]: return an accessor function for setting an element in an array-like object. - [`reverse( x )`][@stdlib/array/base/reverse]: reverse an array in-place. +- [`scatterFilled( fill, len, indices, values, mode )`][@stdlib/array/base/scatter-filled]: scatter a list of provided values to specified indices in a new filled "generic" array. +- [`scattered( len, indices, values, mode )`][@stdlib/array/base/scattered]: scatter a list of provided values to specified indices in a new zero-filled "generic" array. - [`setter( dtype )`][@stdlib/array/base/setter]: return an accessor function for setting an element in an indexed array-like object. - [`slice( x, start, end )`][@stdlib/array/base/slice]: return a shallow copy of a portion of an array. - [`strided2array2d( x, shape, strides, offset )`][@stdlib/array/base/strided2array2d]: convert a strided array to a two-dimensional nested array. @@ -195,6 +214,7 @@ The namespace exports the following: - [`strided2array4d( x, shape, strides, offset )`][@stdlib/array/base/strided2array4d]: convert a strided array to a four-dimensional nested array. - [`strided2array5d( x, shape, strides, offset )`][@stdlib/array/base/strided2array5d]: convert a strided array to a five-dimensional nested array. - [`takeIndexed( x, indices )`][@stdlib/array/base/take-indexed]: take elements from an indexed array. +- [`takeIndexed2( x, y, indices )`][@stdlib/array/base/take-indexed2]: take elements from two indexed arrays in a single pass. - [`take( x, indices, mode )`][@stdlib/array/base/take]: take elements from an array. - [`take2d( x, indices, dimension, mode )`][@stdlib/array/base/take2d]: take elements from a two-dimensional nested array. - [`take3d( x, indices, dimension, mode )`][@stdlib/array/base/take3d]: take elements from a three-dimensional nested array. @@ -207,8 +227,11 @@ The namespace exports the following: - [`toReversed( x )`][@stdlib/array/base/to-reversed]: return a new array with elements in reverse order. - [`unary2dBy( arrays, shape, fcn, clbk[, thisArg] )`][@stdlib/array/base/unary2d-by]: apply a unary function to each element retrieved from a two-dimensional nested input array according to a callback function and assign results to elements in a two-dimensional nested output array. - [`unary2d( arrays, shape, fcn )`][@stdlib/array/base/unary2d]: apply a unary callback to elements in a two-dimensional nested input array and assign results to elements in a two-dimensional nested output array. +- [`unary3dBy( arrays, shape, fcn, clbk[, thisArg] )`][@stdlib/array/base/unary3d-by]: apply a unary function to each element retrieved from a three-dimensional nested input array according to a callback function and assign results to elements in a three-dimensional nested output array. - [`unary3d( arrays, shape, fcn )`][@stdlib/array/base/unary3d]: apply a unary callback to elements in a three-dimensional nested input array and assign results to elements in a three-dimensional nested output array. +- [`unary4dBy( arrays, shape, fcn, clbk[, thisArg] )`][@stdlib/array/base/unary4d-by]: apply a unary function to each element retrieved from a four-dimensional nested input array according to a callback function and assign results to elements in a four-dimensional nested output array. - [`unary4d( arrays, shape, fcn )`][@stdlib/array/base/unary4d]: apply a unary callback to elements in a four-dimensional nested input array and assign results to elements in a four-dimensional nested output array. +- [`unary5dBy( arrays, shape, fcn, clbk[, thisArg] )`][@stdlib/array/base/unary5d-by]: apply a unary function to each element retrieved from a five-dimensional nested input array according to a callback function and assign results to elements in a five-dimensional nested output array. - [`unary5d( arrays, shape, fcn )`][@stdlib/array/base/unary5d]: apply a unary callback to elements in a five-dimensional nested input array and assign results to elements in a five-dimensional nested output array. - [`unarynd( arrays, shape, fcn )`][@stdlib/array/base/unarynd]: apply a unary callback to elements in an n-dimensional nested input array and assign results to elements in an n-dimensional nested output array. - [`unitspace( start, stop )`][@stdlib/array/base/unitspace]: generate a linearly spaced numeric array whose elements increment by 1. @@ -344,10 +367,24 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/broadcasted-quaternary2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-quaternary2d +[@stdlib/array/base/broadcasted-quaternary3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-quaternary3d + +[@stdlib/array/base/broadcasted-quaternary4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-quaternary4d + +[@stdlib/array/base/broadcasted-quaternary5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-quaternary5d + [@stdlib/array/base/broadcasted-quinary2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-quinary2d +[@stdlib/array/base/broadcasted-quinary4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-quinary4d + [@stdlib/array/base/broadcasted-ternary2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-ternary2d +[@stdlib/array/base/broadcasted-ternary3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-ternary3d + +[@stdlib/array/base/broadcasted-ternary4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-ternary4d + +[@stdlib/array/base/broadcasted-ternary5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-ternary5d + [@stdlib/array/base/broadcasted-unary2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-unary2d [@stdlib/array/base/broadcasted-unary3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/broadcasted-unary3d @@ -394,6 +431,8 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/fancy-slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/fancy-slice +[@stdlib/array/base/fill]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/fill + [@stdlib/array/base/filled-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/filled-by [@stdlib/array/base/filled]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/filled @@ -478,6 +517,8 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/index-of +[@stdlib/array/base/indices-complement]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/indices-complement + [@stdlib/array/base/join]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/join [@stdlib/array/base/last-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/last-index-of @@ -502,8 +543,20 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/mskbinary2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskbinary2d +[@stdlib/array/base/mskbinary3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskbinary3d + +[@stdlib/array/base/mskbinary4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskbinary4d + +[@stdlib/array/base/mskbinary5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskbinary5d + +[@stdlib/array/base/mskfilter-map]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskfilter-map + [@stdlib/array/base/mskfilter]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskfilter +[@stdlib/array/base/mskfilter2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskfilter2 + +[@stdlib/array/base/mskfiltern]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskfiltern + [@stdlib/array/base/mskput]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskput [@stdlib/array/base/mskreject]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskreject @@ -512,6 +565,10 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/mskunary3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskunary3d +[@stdlib/array/base/mskunary4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskunary4d + +[@stdlib/array/base/mskunary5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/mskunary5d + [@stdlib/array/base/n-cartesian-product]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/n-cartesian-product [@stdlib/array/base/none-by-right]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/none-by-right @@ -566,6 +623,10 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/reverse]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/reverse +[@stdlib/array/base/scatter-filled]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/scatter-filled + +[@stdlib/array/base/scattered]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/scattered + [@stdlib/array/base/setter]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/setter [@stdlib/array/base/slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/slice @@ -580,6 +641,8 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/take-indexed]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/take-indexed +[@stdlib/array/base/take-indexed2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/take-indexed2 + [@stdlib/array/base/take]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/take [@stdlib/array/base/take2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/take2d @@ -604,10 +667,16 @@ var squared = ns.map2d( arr2d, [ 2, 3 ], randu ); [@stdlib/array/base/unary2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary2d +[@stdlib/array/base/unary3d-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary3d-by + [@stdlib/array/base/unary3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary3d +[@stdlib/array/base/unary4d-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary4d-by + [@stdlib/array/base/unary4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary4d +[@stdlib/array/base/unary5d-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary5d-by + [@stdlib/array/base/unary5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unary5d [@stdlib/array/base/unarynd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/unarynd diff --git a/lib/node_modules/@stdlib/array/base/assert/README.md b/lib/node_modules/@stdlib/array/base/assert/README.md index a5407b5b4ae1..3b38be66f5c6 100644 --- a/lib/node_modules/@stdlib/array/base/assert/README.md +++ b/lib/node_modules/@stdlib/array/base/assert/README.md @@ -67,6 +67,7 @@ The namespace exports the following: - [`isSafeDataTypeCast( from, to )`][@stdlib/array/base/assert/is-safe-data-type-cast]: determine whether an array data type can be safely cast to another array data type. - [`isSameKindDataTypeCast( from, to )`][@stdlib/array/base/assert/is-same-kind-data-type-cast]: determine whether an array data type can be safely cast to, or is of the same "kind" as, another array data type. - [`isSignedIntegerDataType( value )`][@stdlib/array/base/assert/is-signed-integer-data-type]: test if an input value is a supported array signed integer data type. +- [`isSortedAscending( x )`][@stdlib/array/base/assert/is-sorted-ascending]: test if an array is sorted in ascending order. - [`isUnsignedIntegerDataType( value )`][@stdlib/array/base/assert/is-unsigned-integer-data-type]: test if an input value is a supported array unsigned integer data type. @@ -218,6 +219,8 @@ console.log( 'arr4 is complex typed array: ' + ns.isComplexTypedArray( arr4 ) ); [@stdlib/array/base/assert/is-signed-integer-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/assert/is-signed-integer-data-type +[@stdlib/array/base/assert/is-sorted-ascending]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/assert/is-sorted-ascending + [@stdlib/array/base/assert/is-unsigned-integer-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/assert/is-unsigned-integer-data-type diff --git a/lib/node_modules/@stdlib/array/base/assert/contains/lib/index.js b/lib/node_modules/@stdlib/array/base/assert/contains/lib/index.js index 6c6862997d16..4ef6bd9590a3 100644 --- a/lib/node_modules/@stdlib/array/base/assert/contains/lib/index.js +++ b/lib/node_modules/@stdlib/array/base/assert/contains/lib/index.js @@ -30,6 +30,8 @@ * // returns true */ +// MODULES // + var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); var main = require( './main.js' ); var factory = require( './factory.js' ); diff --git a/lib/node_modules/@stdlib/array/base/assert/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/assert/docs/types/index.d.ts index 3bf8ec2445c0..8a8285f76340 100644 --- a/lib/node_modules/@stdlib/array/base/assert/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/base/assert/docs/types/index.d.ts @@ -42,6 +42,7 @@ import isRealFloatingPointDataType = require( '@stdlib/array/base/assert/is-real import isSafeDataTypeCast = require( '@stdlib/array/base/assert/is-safe-data-type-cast' ); import isSameKindDataTypeCast = require( '@stdlib/array/base/assert/is-same-kind-data-type-cast' ); import isSignedIntegerDataType = require( '@stdlib/array/base/assert/is-signed-integer-data-type' ); +import isSortedAscending = require( '@stdlib/array/base/assert/is-sorted-ascending' ); import isUnsignedIntegerDataType = require( '@stdlib/array/base/assert/is-unsigned-integer-data-type' ); /** @@ -689,6 +690,38 @@ interface Namespace { */ isSignedIntegerDataType: typeof isSignedIntegerDataType; + /** + * Tests if an array is sorted in ascending order. + * + * @param x - input array + * @returns boolean indicating if an array is sorted in ascending order + * + * @example + * var out = ns.isSortedAscending( [ 1, 2, 3 ] ); + * // returns true + * + * @example + * var out = ns.isSortedAscending( [ 3, 2, 1 ] ); + * // returns false + * + * @example + * var out = ns.isSortedAscending( [ 3, 3, 3 ] ); + * // returns true + * + * @example + * var out = ns.isSortedAscending( [ 3 ] ); + * // returns true + * + * @example + * var out = ns.isSortedAscending( [] ); + * // returns false + * + * @example + * var out = ns.isSortedAscending( [ 1, 3, 2 ] ); + * // returns false + */ + isSortedAscending: typeof isSortedAscending; + /** * Tests whether an input value is a supported array unsigned integer data type. * diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/README.md b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/README.md new file mode 100644 index 000000000000..797c484f80d4 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/README.md @@ -0,0 +1,133 @@ + + +# isSortedAscending + +> Test if an array is sorted in ascending order. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var isSortedAscending = require( '@stdlib/array/base/assert/is-sorted-ascending' ); +``` + +#### isSortedAscending( x ) + +Tests if an array is sorted in ascending order. + +```javascript +var out = isSortedAscending( [ 1, 2, 3 ] ); +// returns true + +out = isSortedAscending( [ 3, 2, 1 ] ); +// returns false +``` + +If provided an empty array, the function returns `false`. + +```javascript +var out = isSortedAscending( [] ); +// returns false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var AccessorArray = require( '@stdlib/array/base/accessor' ); +var isSortedAscending = require( '@stdlib/array/base/assert/is-sorted-ascending' ); + +var x = new AccessorArray( [ 1, 2, 3, 4 ] ); +var bool = isSortedAscending( x ); +// returns true + +x = new AccessorArray( [ 1, 1, 1, 1 ] ); +bool = isSortedAscending( x ); +// returns true + +x = new AccessorArray( [ 1 ] ); +bool = isSortedAscending( x ); +// returns true + +x = new AccessorArray( [ 1, 3, 2, 4 ] ); +bool = isSortedAscending( x ); +// returns false + +x = new AccessorArray( [ 4, 3, 2, 1 ] ); +bool = isSortedAscending( x ); +// returns false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js new file mode 100644 index 000000000000..7d45939737c9 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.accessors.length.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var AccessorArray = require( '@stdlib/array/base/accessor' ); +var pkg = require( './../package.json' ).name; +var isSortedAscending = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = new AccessorArray( zeroTo( len ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = isSortedAscending( x ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( out ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( pkg+'::accessors:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js new file mode 100644 index 000000000000..d09cc387375c --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/benchmark/benchmark.length.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var pkg = require( './../package.json' ).name; +var isSortedAscending = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeroTo( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = isSortedAscending( x ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( out ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/repl.txt b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/repl.txt new file mode 100644 index 000000000000..4a0363b93571 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/repl.txt @@ -0,0 +1,26 @@ + +{{alias}}( x ) + Tests if an array is sorted in ascending order. + + The function returns `false` if provided an empty array. + + Parameters + ---------- + x: ArrayLikeObject + Input array. + + Returns + ------- + out: boolean + Boolean indicating if an array is sorted in ascending order. + + Examples + -------- + > var out = {{alias}}( [ 1, 2, 3 ] ) + true + > out = {{alias}}( [ 3, 2, 1 ] ) + false + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/types/index.d.ts new file mode 100644 index 000000000000..f5bcfeadf160 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/types/index.d.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Tests if an array is sorted in ascending order. +* +* @param x - input array +* @returns boolean indicating if an array is sorted in ascending order +* +* @example +* var out = isSortedAscending( [ 1, 2, 3 ] ); +* // returns true +* +* @example +* var out = isSortedAscending( [ 3, 2, 1 ] ); +* // returns false +* +* @example +* var out = isSortedAscending( [ 3, 3, 3 ] ); +* // returns true +* +* @example +* var out = isSortedAscending( [ 3 ] ); +* // returns true +* +* @example +* var out = isSortedAscending( [] ); +* // returns false +* +* @example +* var out = isSortedAscending( [ 1, 3, 2 ] ); +* // returns false +*/ +declare function isSortedAscending( x: Collection | AccessorArrayLike ): boolean; + + +// EXPORTS // + +export = isSortedAscending; diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/types/test.ts new file mode 100644 index 000000000000..65843227bcc4 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/docs/types/test.ts @@ -0,0 +1,42 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isSortedAscending = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isSortedAscending( [ 1, 2, 3 ] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided a first argument which is not a collection... +{ + isSortedAscending( 5 ); // $ExpectError + isSortedAscending( true ); // $ExpectError + isSortedAscending( false ); // $ExpectError + isSortedAscending( null ); // $ExpectError + isSortedAscending( {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isSortedAscending(); // $ExpectError + isSortedAscending( [ 1, 2, 3 ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/examples/index.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/examples/index.js new file mode 100644 index 000000000000..af19eb395396 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/examples/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var AccessorArray = require( '@stdlib/array/base/accessor' ); +var isSortedAscending = require( './../lib' ); + +var x = new AccessorArray( [ 1, 2, 3, 4 ] ); +var bool = isSortedAscending( x ); +console.log( bool ); +// => true + +x = new AccessorArray( [ 1, 1, 1, 1 ] ); +bool = isSortedAscending( x ); +console.log( bool ); +// => true + +x = new AccessorArray( [ 1 ] ); +bool = isSortedAscending( x ); +console.log( bool ); +// => true + +x = new AccessorArray( [ 1, 3, 2, 4 ] ); +bool = isSortedAscending( x ); +console.log( bool ); +// => false + +x = new AccessorArray( [ 4, 3, 2, 1 ] ); +bool = isSortedAscending( x ); +console.log( bool ); +// => false diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/lib/index.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/lib/index.js new file mode 100644 index 000000000000..e1b44b005936 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test if an array is sorted in ascending order. +* +* @module @stdlib/array/base/assert/is-sorted-ascending +* +* @example +* var isSortedAscending = require( '@stdlib/array/base/assert/is-sorted-ascending' ); +* +* var out = isSortedAscending( [ 1, 2, 3 ] ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/lib/main.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/lib/main.js new file mode 100644 index 000000000000..af37cfde0b79 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/lib/main.js @@ -0,0 +1,100 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isAccessorArray = require( '@stdlib/array/base/assert/is-accessor-array' ); +var accessorGetter = require( '@stdlib/array/base/accessor-getter' ); +var getter = require( '@stdlib/array/base/getter' ); +var dtype = require( '@stdlib/array/dtype' ); + + +// MAIN // + +/** +* Tests if an array is sorted in ascending order. +* +* @param {Collection} x - input array +* @returns {boolean} boolean indicating if an array is sorted in ascending order +* +* @example +* var out = isSortedAscending( [ 1, 2, 3 ] ); +* // returns true +* +* @example +* var out = isSortedAscending( [ 3, 2, 1 ] ); +* // returns false +* +* @example +* var out = isSortedAscending( [ 3, 3, 3 ] ); +* // returns true +* +* @example +* var out = isSortedAscending( [ 3 ] ); +* // returns true +* +* @example +* var out = isSortedAscending( [] ); +* // returns false +* +* @example +* var out = isSortedAscending( [ 1, 3, 2 ] ); +* // returns false +*/ +function isSortedAscending( x ) { + var len; + var get; + var dt; + var v1; + var v2; + var i; + + // Resolve the input array data type: + dt = dtype( x ); + + // Resolve an accessor for retrieving input array elements: + if ( isAccessorArray( x ) ) { + get = accessorGetter( dt ); + } else { + get = getter( dt ); + } + // Get the number of elements over which to iterate: + len = x.length; + + // Check for an empty array: + if ( len === 0 ) { + return false; + } + // Loop over the elements... + v1 = get( x, 0 ); + for ( i = 1; i < len; i++ ) { + v2 = get( x, i ); + if ( v1 > v2 ) { + return false; + } + v1 = v2; + } + return true; +} + + +// EXPORTS // + +module.exports = isSortedAscending; diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json new file mode 100644 index 000000000000..7fe5f635babb --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json @@ -0,0 +1,64 @@ +{ + "name": "@stdlib/array/base/assert/is-sorted-ascending", + "version": "0.0.0", + "description": "Test if an array is sorted in ascending order.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "data", + "structure", + "array", + "generic", + "sorted", + "ascending", + "ordered", + "assert" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/test/test.js b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/test/test.js new file mode 100644 index 000000000000..5aca2515c895 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/test/test.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var AccessorArray = require( '@stdlib/array/base/accessor' ); +var isSortedAscending = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof isSortedAscending, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function tests whether an array is sorted in ascending order', function test( t ) { + var actual; + var x; + + x = [ 1, 2, 3 ]; + actual = isSortedAscending( x ); + t.strictEqual( actual, true, 'returns expected value' ); + + x = [ 1, 1, 1 ]; + actual = isSortedAscending( x ); + t.strictEqual( actual, true, 'returns expected value' ); + + x = [ 1 ]; + actual = isSortedAscending( x ); + t.strictEqual( actual, true, 'returns expected value' ); + + x = [ 3, 2, 1 ]; + actual = isSortedAscending( x ); + t.strictEqual( actual, false, 'returns expected value' ); + + x = []; + actual = isSortedAscending( x ); + t.strictEqual( actual, false, 'returns expected value' ); + + x = [ 2, 1, 3 ]; + actual = isSortedAscending( x ); + t.strictEqual( actual, false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function tests whether an array is sorted in ascending order (accessors)', function test( t ) { + var actual; + var x; + + x = new AccessorArray( [ 1, 2, 3 ] ); + actual = isSortedAscending( x ); + t.strictEqual( actual, true, 'returns expected value' ); + + x = new AccessorArray( [ 1, 1, 1 ] ); + actual = isSortedAscending( x ); + t.strictEqual( actual, true, 'returns expected value' ); + + x = new AccessorArray( [ 1 ] ); + actual = isSortedAscending( x ); + t.strictEqual( actual, true, 'returns expected value' ); + + x = new AccessorArray( [ 3, 2, 1 ] ); + actual = isSortedAscending( x ); + t.strictEqual( actual, false, 'returns expected value' ); + + x = new AccessorArray( [] ); + actual = isSortedAscending( x ); + t.strictEqual( actual, false, 'returns expected value' ); + + x = new AccessorArray( [ 2, 1, 3 ] ); + actual = isSortedAscending( x ); + t.strictEqual( actual, false, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/assert/lib/index.js b/lib/node_modules/@stdlib/array/base/assert/lib/index.js index 149c00d7cb19..cde6bf937a63 100644 --- a/lib/node_modules/@stdlib/array/base/assert/lib/index.js +++ b/lib/node_modules/@stdlib/array/base/assert/lib/index.js @@ -234,6 +234,15 @@ setReadOnly( ns, 'isSameKindDataTypeCast', require( '@stdlib/array/base/assert/i */ setReadOnly( ns, 'isSignedIntegerDataType', require( '@stdlib/array/base/assert/is-signed-integer-data-type' ) ); +/** +* @name isSortedAscending +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/assert/is-sorted-ascending} +*/ +setReadOnly( ns, 'isSortedAscending', require( '@stdlib/array/base/assert/is-sorted-ascending' ) ); + /** * @name isUnsignedIntegerDataType * @memberof ns diff --git a/lib/node_modules/@stdlib/array/base/cuevery-by-right/README.md b/lib/node_modules/@stdlib/array/base/cuevery-by-right/README.md index 17dca3bf05b6..d0a0268f9ce3 100644 --- a/lib/node_modules/@stdlib/array/base/cuevery-by-right/README.md +++ b/lib/node_modules/@stdlib/array/base/cuevery-by-right/README.md @@ -66,9 +66,9 @@ var bool = ( out === y ); The invoked `predicate` function is provided three arguments: -- **value**: collection element, -- **index**: collection index, -- **collection**: input collection, +- **value**: collection element. +- **index**: collection index. +- **collection**: input collection. To set the function execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/base/cuevery-by/lib/assign.js b/lib/node_modules/@stdlib/array/base/cuevery-by/lib/assign.js index 365ef9412513..49f64922c962 100644 --- a/lib/node_modules/@stdlib/array/base/cuevery-by/lib/assign.js +++ b/lib/node_modules/@stdlib/array/base/cuevery-by/lib/assign.js @@ -146,7 +146,7 @@ function accessors( x, out, stride, offset, predicate, thisArg ) { * * @example * function isPositive( value ) { -* return ( value > 0 ); +* return ( value > 0 ); * } * * var x = [ 1, 1, 1, 0, 1 ]; diff --git a/lib/node_modules/@stdlib/array/base/cunone-by-right/lib/assign.js b/lib/node_modules/@stdlib/array/base/cunone-by-right/lib/assign.js index 12cf3a4cf878..8614414ccc7f 100644 --- a/lib/node_modules/@stdlib/array/base/cunone-by-right/lib/assign.js +++ b/lib/node_modules/@stdlib/array/base/cunone-by-right/lib/assign.js @@ -136,7 +136,7 @@ function accessors( x, out, stride, offset, predicate, thisArg ) { * * @example * function fcn( value ) { -* return ( value > 0 ); +* return ( value > 0 ); * } * * var x = [ 1, 1, 0, 0 ]; diff --git a/lib/node_modules/@stdlib/array/base/cusome-by-right/lib/index.js b/lib/node_modules/@stdlib/array/base/cusome-by-right/lib/index.js index 7d0e5b424cbe..e6fb3441cbb7 100644 --- a/lib/node_modules/@stdlib/array/base/cusome-by-right/lib/index.js +++ b/lib/node_modules/@stdlib/array/base/cusome-by-right/lib/index.js @@ -39,7 +39,7 @@ * var cusomeByRight = require( '@stdlib/array/base/cusome-by-right' ); * * function fcn( value ) { -* return ( value > 0 ); +* return ( value > 0 ); * } * * var x = [ 1, 1, 0, 0, 0 ]; diff --git a/lib/node_modules/@stdlib/array/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/docs/types/index.d.ts index 5008dcd1a3cf..512946c21756 100644 --- a/lib/node_modules/@stdlib/array/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/base/docs/types/index.d.ts @@ -52,8 +52,15 @@ import bbinary3d = require( '@stdlib/array/base/broadcasted-binary3d' ); import bbinary4d = require( '@stdlib/array/base/broadcasted-binary4d' ); import bbinary5d = require( '@stdlib/array/base/broadcasted-binary5d' ); import bquaternary2d = require( '@stdlib/array/base/broadcasted-quaternary2d' ); +import bquaternary3d = require( '@stdlib/array/base/broadcasted-quaternary3d' ); +import bquaternary4d = require( '@stdlib/array/base/broadcasted-quaternary4d' ); +import bquaternary5d = require( '@stdlib/array/base/broadcasted-quaternary5d' ); import bquinary2d = require( '@stdlib/array/base/broadcasted-quinary2d' ); +import bquinary4d = require( '@stdlib/array/base/broadcasted-quinary4d' ); import bternary2d = require( '@stdlib/array/base/broadcasted-ternary2d' ); +import bternary3d = require( '@stdlib/array/base/broadcasted-ternary3d' ); +import bternary4d = require( '@stdlib/array/base/broadcasted-ternary4d' ); +import bternary5d = require( '@stdlib/array/base/broadcasted-ternary5d' ); import bunary2d = require( '@stdlib/array/base/broadcasted-unary2d' ); import bunary3d = require( '@stdlib/array/base/broadcasted-unary3d' ); import bunary4d = require( '@stdlib/array/base/broadcasted-unary4d' ); @@ -77,6 +84,7 @@ import everyBy = require( '@stdlib/array/base/every-by' ); import everyByRight = require( '@stdlib/array/base/every-by-right' ); import fancySlice = require( '@stdlib/array/base/fancy-slice' ); import fancySliceAssign = require( '@stdlib/array/base/fancy-slice-assign' ); +import fill = require( '@stdlib/array/base/fill' ); import filled = require( '@stdlib/array/base/filled' ); import filledBy = require( '@stdlib/array/base/filled-by' ); import filled2d = require( '@stdlib/array/base/filled2d' ); @@ -119,6 +127,7 @@ import groupValues = require( '@stdlib/array/base/group-values' ); import groupValuesBy = require( '@stdlib/array/base/group-values-by' ); import incrspace = require( '@stdlib/array/base/incrspace' ); import indexOf = require( '@stdlib/array/base/index-of' ); +import indicesComplement = require( '@stdlib/array/base/indices-complement' ); import join = require( '@stdlib/array/base/join' ); import last = require( '@stdlib/array/base/last' ); import lastIndexOf = require( '@stdlib/array/base/last-index-of' ); @@ -131,11 +140,19 @@ import map5d = require( '@stdlib/array/base/map5d' ); import minSignedIntegerDataType = require( '@stdlib/array/base/min-signed-integer-dtype' ); import minUnsignedIntegerDataType = require( '@stdlib/array/base/min-unsigned-integer-dtype' ); import mskbinary2d = require( '@stdlib/array/base/mskbinary2d' ); +import mskbinary3d = require( '@stdlib/array/base/mskbinary3d' ); +import mskbinary4d = require( '@stdlib/array/base/mskbinary4d' ); +import mskbinary5d = require( '@stdlib/array/base/mskbinary5d' ); import mskfilter = require( '@stdlib/array/base/mskfilter' ); +import mskfilterMap = require( '@stdlib/array/base/mskfilter-map' ); +import mskfilter2 = require( '@stdlib/array/base/mskfilter2' ); +import mskfiltern = require( '@stdlib/array/base/mskfiltern' ); import mskput = require( '@stdlib/array/base/mskput' ); import mskreject = require( '@stdlib/array/base/mskreject' ); import mskunary2d = require( '@stdlib/array/base/mskunary2d' ); import mskunary3d = require( '@stdlib/array/base/mskunary3d' ); +import mskunary4d = require( '@stdlib/array/base/mskunary4d' ); +import mskunary5d = require( '@stdlib/array/base/mskunary5d' ); import nCartesianProduct = require( '@stdlib/array/base/n-cartesian-product' ); import none = require( '@stdlib/array/base/none' ); import noneBy = require( '@stdlib/array/base/none-by' ); @@ -163,6 +180,8 @@ import removeAt = require( '@stdlib/array/base/remove-at' ); import resolveGetter = require( '@stdlib/array/base/resolve-getter' ); import resolveSetter = require( '@stdlib/array/base/resolve-setter' ); import reverse = require( '@stdlib/array/base/reverse' ); +import scatterFilled = require( '@stdlib/array/base/scatter-filled' ); +import scattered = require( '@stdlib/array/base/scattered' ); import setter = require( '@stdlib/array/base/setter' ); import slice = require( '@stdlib/array/base/slice' ); import strided2array2d = require( '@stdlib/array/base/strided2array2d' ); @@ -171,6 +190,7 @@ import strided2array4d = require( '@stdlib/array/base/strided2array4d' ); import strided2array5d = require( '@stdlib/array/base/strided2array5d' ); import take = require( '@stdlib/array/base/take' ); import takeIndexed = require( '@stdlib/array/base/take-indexed' ); +import takeIndexed2 = require( '@stdlib/array/base/take-indexed2' ); import take2d = require( '@stdlib/array/base/take2d' ); import take3d = require( '@stdlib/array/base/take3d' ); import ternary2d = require( '@stdlib/array/base/ternary2d' ); @@ -183,8 +203,11 @@ import toReversed = require( '@stdlib/array/base/to-reversed' ); import unary2d = require( '@stdlib/array/base/unary2d' ); import unary2dBy = require( '@stdlib/array/base/unary2d-by' ); import unary3d = require( '@stdlib/array/base/unary3d' ); +import unary3dBy = require( '@stdlib/array/base/unary3d-by' ); import unary4d = require( '@stdlib/array/base/unary4d' ); +import unary4dBy = require( '@stdlib/array/base/unary4d-by' ); import unary5d = require( '@stdlib/array/base/unary5d' ); +import unary5dBy = require( '@stdlib/array/base/unary5d-by' ); import unarynd = require( '@stdlib/array/base/unarynd' ); import unitspace = require( '@stdlib/array/base/unitspace' ); import where = require( '@stdlib/array/base/where' ); @@ -1042,6 +1065,117 @@ interface Namespace { */ bquaternary2d: typeof bquaternary2d; + /** + * Applies a quaternary callback to elements in four broadcasted input arrays and assigns results to elements in a three-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing four input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - quaternary callback + * + * @example + * var add = require( '@stdlib/math/base/ops/add4' ); + * var ones3d = require( '@stdlib/array/base/ones3d' ); + * var zeros3d = require( '@stdlib/array/base/zeros3d' ); + * + * var shapes = [ + * [ 1, 1, 3 ], + * [ 3, 1, 1 ], + * [ 1, 3, 1 ], + * [ 3, 3, 3 ], + * [ 3, 3, 3 ] + * ]; + * + * var x = ones3d( shapes[ 0 ] ); + * var y = ones3d( shapes[ 1 ] ); + * var z = ones3d( shapes[ 2 ] ); + * var w = ones3d( shapes[ 3 ] ); + * var out = zeros3d( shapes[ 4 ] ); + * + * ns.bquaternary3d( [ x, y, z, w, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ], [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ], [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ] ] + */ + bquaternary3d: typeof bquaternary3d; + + /** + * Applies a quaternary callback to elements in four broadcasted input arrays and assigns results to elements in a four-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing four input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - quaternary callback + * + * @example + * var add = require( '@stdlib/math/base/ops/add4' ); + * var ones4d = require( '@stdlib/array/base/ones4d' ); + * var zeros4d = require( '@stdlib/array/base/zeros4d' ); + * + * var shapes = [ + * [ 1, 3, 1, 1 ], + * [ 1, 1, 3, 1 ], + * [ 1, 1, 1, 3 ], + * [ 1, 1, 1, 1 ], + * [ 1, 3, 3, 3 ] + * ]; + * + * var x = ones4d( shapes[ 0 ] ); + * var y = ones4d( shapes[ 1 ] ); + * var z = ones4d( shapes[ 2 ] ); + * var w = ones4d( shapes[ 3 ] ); + * var out = zeros4d( shapes[ 4 ] ); + * + * ns.bquaternary4d( [ x, y, z, w, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ], [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ], [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ] ] ] + */ + bquaternary4d: typeof bquaternary4d; + + /** + * Applies a quaternary callback to elements in four broadcasted input arrays and assigns results to elements in a five-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing four input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - quaternary callback + * + * @example + * var add = require( '@stdlib/math/base/ops/add4' ); + * var ones5d = require( '@stdlib/array/base/ones5d' ); + * var zeros5d = require( '@stdlib/array/base/zeros5d' ); + * + * var shapes = [ + * [ 1, 1, 3, 1, 1 ], + * [ 1, 1, 1, 3, 1 ], + * [ 1, 1, 1, 1, 3 ], + * [ 1, 1, 1, 1, 1 ], + * [ 1, 1, 3, 3, 3 ] + * ]; + * + * var x = ones5d( shapes[ 0 ] ); + * var y = ones5d( shapes[ 1 ] ); + * var z = ones5d( shapes[ 2 ] ); + * var w = ones5d( shapes[ 3 ] ); + * var out = zeros5d( shapes[ 4 ] ); + * + * ns.bquaternary5d( [ x, y, z, w, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ], [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ], [ [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ], [ 4.0, 4.0, 4.0 ] ] ] ] ] + */ + bquaternary5d: typeof bquaternary5d; + /** * Applies a quinary callback to elements in five broadcasted input arrays and assigns results to elements in a two-dimensional nested output array. * @@ -1084,6 +1218,48 @@ interface Namespace { */ bquinary2d: typeof bquinary2d; + /** + * Applies a quinary callback to elements in five broadcasted input arrays and assigns results to elements in a four-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing five input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - quinary callback + * + * @example + * var ones4d = require( '@stdlib/array/base/ones4d' ); + * var zeros4d = require( '@stdlib/array/base/zeros4d' ); + * + * function add( x, y, z, w, v ) { + * return x + y + z + w + v; + * } + * + * var shapes = [ + * [ 1, 1, 1, 2 ], + * [ 1, 1, 2, 1 ], + * [ 1, 1, 2, 2 ], + * [ 1, 2, 1, 1 ], + * [ 2, 2, 2, 2 ], + * [ 2, 2, 2, 2 ] + * ]; + * + * var x = ones4d( shapes[ 0 ] ); + * var y = ones4d( shapes[ 1 ] ); + * var z = ones4d( shapes[ 2 ] ); + * var w = ones4d( shapes[ 3 ] ); + * var v = ones4d( shapes[ 4 ] ); + * var out = zeros4d( shapes[ 5 ] ); + * + * ns.bquinary4d( [ x, y, z, w, v, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ [ 5.0, 5.0 ], [ 5.0, 5.0 ] ], [ [ 5.0, 5.0 ], [ 5.0, 5.0 ] ] ], [ [ [ 5.0, 5.0 ], [ 5.0, 5.0 ] ], [ [ 5.0, 5.0 ], [ 5.0, 5.0 ] ] ] ] + */ + bquinary4d: typeof bquinary4d; + /** * Applies a ternary callback to elements in three broadcasted input arrays and assigns results to elements in a two-dimensional nested output array. * @@ -1119,6 +1295,111 @@ interface Namespace { */ bternary2d: typeof bternary2d; + /** + * Applies a ternary callback to elements in three broadcasted input arrays and assigns results to elements in a three-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing three input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - ternary callback + * + * @example + * var ones3d = require( '@stdlib/array/base/ones3d' ); + * var zeros3d = require( '@stdlib/array/base/zeros3d' ); + * var add = require( '@stdlib/math/base/ops/add3' ); + * + * var shapes = [ + * [ 1, 2, 1 ], + * [ 2, 1, 1 ], + * [ 1, 1, 2 ], + * [ 2, 2, 2 ] + * ]; + * + * var x = ones3d( shapes[ 0 ] ); + * var y = ones3d( shapes[ 1 ] ); + * var z = ones3d( shapes[ 2 ] ); + * var out = zeros3d( shapes[ 3 ] ); + * + * ns.bternary3d( [ x, y, z, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ 3.0, 3.0 ], [ 3.0, 3.0 ] ], [ [ 3.0, 3.0 ], [ 3.0, 3.0 ] ] ] + */ + bternary3d: typeof bternary3d; + + /** + * Applies a ternary callback to elements in three broadcasted input arrays and assigns results to elements in a four-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing three input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - ternary callback + * + * @example + * var ones4d = require( '@stdlib/array/base/ones4d' ); + * var zeros4d = require( '@stdlib/array/base/zeros4d' ); + * var add = require( '@stdlib/math/base/ops/add3' ); + * + * var shapes = [ + * [ 1, 2, 1, 1 ], + * [ 2, 1, 1, 1 ], + * [ 1, 1, 2, 1 ], + * [ 2, 2, 2, 2 ] + * ]; + * + * var x = ones4d( shapes[ 0 ] ); + * var y = ones4d( shapes[ 1 ] ); + * var z = ones4d( shapes[ 2 ] ); + * var out = zeros4d( shapes[ 3 ] ); + * + * ns.bternary4d( [ x, y, z, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ 3.0, 3.0 ], [ 3.0, 3.0 ] ], [ [ 3.0, 3.0 ], [ 3.0, 3.0 ] ], [ [ 3.0, 3.0 ], [ 3.0, 3.0 ] ], [ [ 3.0, 3.0 ], [ 3.0, 3.0 ] ] ] + */ + bternary4d: typeof bternary4d; + + /** + * Applies a ternary callback to elements in three broadcasted input arrays and assigns results to elements in a five-dimensional nested output array. + * + * ## Notes + * + * - The input array shapes must be broadcast compatible with the output array shape. + * + * @param arrays - array containing three input nested arrays and one output nested array + * @param shapes - array shapes + * @param fcn - ternary callback + * + * @example + * var ones5d = require( '@stdlib/array/base/ones5d' ); + * var zeros5d = require( '@stdlib/array/base/zeros5d' ); + * var add = require( '@stdlib/math/base/ops/add3' ); + * var ns.bternary5d = require( '@stdlib/array/base/broadcasted-ternary5d' ); + * var shapes = [ + * [ 1, 2, 1, 1, 1 ], + * [ 2, 1, 1, 1, 1 ], + * [ 1, 1, 1, 1, 1 ], + * [ 2, 2, 1, 1, 1 ] + * ]; + * + * var x = ones5d( shapes[ 0 ] ); + * var y = ones5d( shapes[ 1 ] ); + * var z = ones5d( shapes[ 2 ] ); + * var out = zeros5d( shapes[ 3 ] ); + * + * ns.bternary5d( [ x, y, z, out ], shapes, add ); + * + * console.log( out ); + * // => [ [ [ [ [ 3 ] ] ], [ [ [ 3 ] ] ] ], [ [ [ 3 ] ] ], [ [ [ 3 ] ] ] ] ] + */ + bternary5d: typeof bternary5d; + /** * Applies a unary callback to elements in a broadcasted nested input array and assigns results to elements in a two-dimensional nested output array. * @@ -1643,6 +1924,29 @@ interface Namespace { */ fancySliceAssign: typeof fancySliceAssign; + /** + * Fills all elements within a portion of an array with a specified value. + * + * @param x - input array + * @param value - fill value + * @param start - starting index (inclusive) + * @param end - ending index (exclusive) + * @returns modified input array + * + * @example + * var x = [ 1, 2, 3 ]; + * + * var out = ns.fill( x, 4, 0, 3 ); + * // returns [ 4, 4, 4 ] + * + * @example + * var x = [ 1, 2, 3, 4, 5, 6 ]; + * + * var out = ns.fill( x, 8, 0, 3 ); + * // returns [ 8, 8, 8, 4, 5, 6 ] + */ + fill: typeof fill; + /** * Returns a filled "generic" array. * @@ -2513,6 +2817,19 @@ interface Namespace { */ indexOf: typeof indexOf; + /** + * Returns the complement of a list of array indices. + * + * @param N - array length + * @param indices - list of indices + * @returns indices complement + * + * @example + * var idx = ns.indicesComplement( 5, [ 1, 3 ] ); + * // returns [ 0, 2, 4 ] + */ + indicesComplement: typeof indicesComplement; + /** * Returns a string created by joining array elements using a specified separator. * @@ -2888,54 +3205,226 @@ interface Namespace { mskbinary2d: typeof mskbinary2d; /** - * Returns a new array by applying a mask to a provided input array. - * - * @param x - input array - * @param mask - mask array - * @returns output array + * Applies a binary callback to elements in two three-dimensional nested input arrays according to elements in a three-dimensional nested mask array and assigns results to elements in a three-dimensional nested output array. * - * @example - * var x = [ 1, 2, 3, 4 ]; + * ## Notes * - * var y = ns.mskfilter( x, [ 0, 1, 0, 1 ] ); - * // returns [ 2, 4 ] - */ - mskfilter: typeof mskfilter; - - /** - * Replaces elements of an array with provided values according to a provided mask array. + * - The function assumes that the input and output arrays have the same shape. + * - An element in an input array is "masked" if the corresponding element in the mask array is non-zero. * - * @param x - input array - * @param mask - mask array - * @param values - values to set - * @param mode - string specifying behavior when the number of values does not equal the number of falsy values in the mask array - * @returns input array + * @param arrays - array containing two input nested arrays, an input nested mask array, and one output nested array + * @param shape - array shape + * @param fcn - binary callback * * @example - * var x = [ 1, 2, 3, 4 ]; - * - * var mask = [ 1, 0, 0, 1 ]; - * var values = [ 20, 30 ]; + * var ones3d = require( '@stdlib/array/base/ones3d' ); + * var zeros3d = require( '@stdlib/array/base/zeros3d' ); + * var add = require( '@stdlib/math/base/ops/add' ); * - * var out = ns.mskput( x, mask, values, 'strict' ); - * // returns [ 1, 20, 30, 4 ] + * var shape = [ 2, 2, 2 ]; * - * var bool = ( out === x ); - * // returns true + * var x = ones3d( shape ); + * var y = ones3d( shape ); + * var z = zeros3d( shape ); * - * @example - * var x = [ 1, 2, 3, 4 ]; + * var mask = [ + * [ [ 0, 1 ], [ 0, 0 ] ], + * [ [ 1, 0 ], [ 0, 1 ] ] + * ]; * - * var out = ns.mskput( x, [ 1, 0, 0, 1 ], [ 30 ], 'strict_broadcast' ); - * // returns [ 1, 30, 30, 4 ] + * ns.mskbinary3d( [ x, y, mask, z ], shape, add ); * - * var bool = ( out === x ); - * // returns true + * console.log( z ); + * // => [ [ [ 2.0, 0.0 ], [ 2.0, 2.0 ] ], [ [ 0.0, 2.0 ], [ 2.0, 0.0 ] ] ] */ - mskput: typeof mskput; + mskbinary3d: typeof mskbinary3d; /** - * Returns a new array by applying a mask to a provided input array. + * Applies a binary callback to elements in two four-dimensional nested input arrays according to elements in a four-dimensional nested mask array and assigns results to elements in a four-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * - An element in an input array is "masked" if the corresponding element in the mask array is non-zero. + * + * @param arrays - array containing two input nested arrays, an input nested mask array, and one output nested array + * @param shape - array shape + * @param fcn - binary callback + * + * @example + * var ones4d = require( '@stdlib/array/base/ones4d' ); + * var zeros4d = require( '@stdlib/array/base/zeros4d' ); + * var add = require( '@stdlib/math/base/ops/add' ); + * + * var shape = [ 1, 1, 2, 2 ]; + * + * var x = ones4d( shape ); + * var y = ones4d( shape ); + * var z = zeros4d( shape ); + * + * var mask = [ [ [ [ 0, 1 ], [ 0, 0 ] ] ] ]; + * + * mskbinary2d( [ x, y, mask, z ], shape, add ); + * + * console.log( z ); + * // => [ [ [ [ 2.0, 0.0 ], [ 2.0, 2.0 ] ] ] ] + */ + mskbinary4d: typeof mskbinary4d; + + /** + * Applies a binary callback to elements in two five-dimensional nested input arrays according to elements in a five-dimensional nested mask array and assigns results to elements in a five-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * - An element in an input array is "masked" if the corresponding element in the mask array is non-zero. + * + * @param arrays - array containing two input nested arrays, an input nested mask array, and one output nested array + * @param shape - array shape + * @param fcn - binary callback + * + * @example + * var ones5d = require( '@stdlib/array/base/ones5d' ); + * var zeros5d = require( '@stdlib/array/base/zeros5d' ); + * var add = require( '@stdlib/math/base/ops/add' ); + * + * var shape = [ 1, 1, 1, 2, 2 ]; + * + * var x = ones5d( shape ); + * var y = ones5d( shape ); + * var z = zeros5d( shape ); + * + * var mask = [ [ [ [ [ 0, 1 ], [ 0, 0 ] ] ] ] ]; + * + * ns.mskbinary5d( [ x, y, mask, z ], shape, add ); + * + * console.log( z ); + * // => [ [ [ [ [ 2.0, 0.0 ], [ 2.0, 2.0 ] ] ] ] ] + */ + mskbinary5d: typeof mskbinary5d; + + /** + * Returns a new array by applying a mask to a provided input array. + * + * @param x - input array + * @param mask - mask array + * @returns output array + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * + * var y = ns.mskfilter( x, [ 0, 1, 0, 1 ] ); + * // returns [ 2, 4 ] + */ + mskfilter: typeof mskfilter; + + /** + * Returns a new array after applying a mask and a callback function to a provided input array. + * + * @param x - input array + * @param mask - mask array + * @param clbk - callback function + * @param thisArg - callback execution context + * @returns output array + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * + * function scale( val ) { + * return 10 * val; + * } + * + * var y = ns.mskfilterMap( x, [ 0, 1, 0, 1 ], scale ); + * // returns [ 20, 40 ] + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * var mask = [ 0, 1, 0, 1 ]; + * + * var out = [ 0, 0, 0, 0 ]; + * + * function scale( x ) { + * return x * 10; + * } + * + * var arr = ns.mskfilterMap.assign( x, mask, out, 1, 0, scale ); + * // returns [ 20, 40, 0, 0 ] + * + * var bool = ( arr === out ); + * // returns true + */ + mskfilterMap: typeof mskfilterMap; + + /** + * Returns new arrays by applying a mask to two provided input arrays in a single pass. + * + * @param x - first input array + * @param y - second input array + * @param mask - mask array + * @returns output arrays + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * var y = [ 5, 6, 7, 8 ]; + * var mask = [ 0, 1, 0, 1 ]; + * + * var out = ns.mskfilter2( x, y, mask ); + * // returns [ [ 2, 4 ], [ 6, 8 ] ] + */ + mskfilter2: typeof mskfilter2; + + /** + * Returns new arrays by applying a mask to one or more provided input arrays in a single pass. + * + * @param x - first input array + * @param y - second input array (or mask) + * @param arrays - additional input arrays and mask + * @returns output arrays + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * var y = [ 5, 6, 7, 8 ]; + * var mask = [ 0, 1, 0, 1 ]; + * + * var out = ns.mskfiltern( x, y, mask ); + * // returns [ [ 2, 4 ], [ 6, 8 ] ] + */ + mskfiltern: typeof mskfiltern; + + /** + * Replaces elements of an array with provided values according to a provided mask array. + * + * @param x - input array + * @param mask - mask array + * @param values - values to set + * @param mode - string specifying behavior when the number of values does not equal the number of falsy values in the mask array + * @returns input array + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * + * var mask = [ 1, 0, 0, 1 ]; + * var values = [ 20, 30 ]; + * + * var out = ns.mskput( x, mask, values, 'strict' ); + * // returns [ 1, 20, 30, 4 ] + * + * var bool = ( out === x ); + * // returns true + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * + * var out = ns.mskput( x, [ 1, 0, 0, 1 ], [ 30 ], 'strict_broadcast' ); + * // returns [ 1, 30, 30, 4 ] + * + * var bool = ( out === x ); + * // returns true + */ + mskput: typeof mskput; + + /** + * Returns a new array by applying a mask to a provided input array. * * @param x - input array * @param mask - mask array @@ -3017,6 +3506,74 @@ interface Namespace { */ mskunary3d: typeof mskunary3d; + /** + * Applies a unary callback to elements in a four-dimensional nested input array according to elements in a four-dimensional nested mask array and assigns results to elements in a four-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * - An element in an input array is "masked" if the corresponding element in the mask array is non-zero. + * + * @param arrays - array containing one input nested array, an input nested mask array, and one output nested array + * @param shape - array shape + * @param fcn - unary callback + * + * @example + * var ones4d = require( '@stdlib/array/base/ones4d' ); + * var zeros4d = require( '@stdlib/array/base/zeros4d' ); + * + * function scale( x ) { + * return x * 10.0; + * } + * + * var shape = [ 1, 1, 2, 2 ]; + * + * var x = ones4d( shape ); + * var y = zeros4d( shape ); + * + * var mask = [ [ [ [ 0, 1 ], [ 0, 0 ] ] ] ]; + * + * ns.mskunary4d( [ x, mask, y ], shape, scale ); + * + * console.log( y ); + * // => [ [ [ [ 10.0, 0.0 ], [ 10.0, 10.0 ] ] ] ] + */ + mskunary4d: typeof mskunary4d; + + /** + * Applies a unary callback to elements in a five-dimensional nested input array according to elements in a five-dimensional nested mask array and assigns results to elements in a five-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * - An element in an input array is "masked" if the corresponding element in the mask array is non-zero. + * + * @param arrays - array containing one input nested array, an input nested mask array, and one output nested array + * @param shape - array shape + * @param fcn - unary callback + * + * @example + * var ones5d = require( '@stdlib/array/base/ones5d' ); + * var zeros5d = require( '@stdlib/array/base/zeros5d' ); + * + * function scale( x ) { + * return x * 10.0; + * } + * + * var shape = [ 1, 1, 1, 2, 2 ]; + * + * var x = ones5d( shape ); + * var y = zeros5d( shape ); + * + * var mask = [ [ [ [ [ 0, 1 ], [ 0, 0 ] ] ] ] ]; + * + * ns.mskunary5d( [ x, mask, y ], shape, scale ); + * + * console.log( y ); + * // => [ [ [ [ [ 10.0, 0.0 ], [ 10.0, 10.0 ] ] ] ] ] + */ + mskunary5d: typeof mskunary5d; + /** * Returns the n-fold Cartesian product. * @@ -3618,6 +4175,51 @@ interface Namespace { */ reverse: typeof reverse; + /** + * Scatters a list of provided values to specified indices in a new filled "generic" array. + * + * @param fill - fill value + * @param len - output array length + * @param indices - list of element indices + * @param values - values to scatter + * @param mode - index mode + * @returns output array + * + * @example + * var indices = [ 1, 2 ]; + * var values = [ 20, 30 ]; + * + * var out = ns.scatterFilled( null, 4, indices, values, 'throw' ); + * // returns [ null, 20, 30, null ] + * + * @example + * var out = ns.scatterFilled( null, 4, [ 1, 2 ], [ 30 ], 'throw' ); + * // returns [ null, 30, 30, null ] + */ + scatterFilled: typeof scatterFilled; + + /** + * Scatters a list of provided values to specified indices in a new zero-filled "generic" array. + * + * @param len - output array length + * @param indices - list of element indices + * @param values - values to scatter + * @param mode - index mode + * @returns output array + * + * @example + * var indices = [ 1, 2 ]; + * var values = [ 20, 30 ]; + * + * var out = ns.scattered( 4, indices, values, 'throw' ); + * // returns [ 0, 20, 30, 0 ] + * + * @example + * var out = ns.scattered( 4, [ 1, 2 ], [ 30 ], 'throw' ); + * // returns [ 0, 30, 30, 0 ] + */ + scattered: typeof scattered; + /** * Returns an accessor function for setting an element in an indexed array-like object. * @@ -3794,7 +4396,7 @@ interface Namespace { take: typeof take; /** - * Takes element from an indexed array. + * Takes elements from an indexed array. * * ## Notes * @@ -3812,6 +4414,28 @@ interface Namespace { */ takeIndexed: typeof takeIndexed; + /** + * Takes elements from two indexed arrays in a single pass. + * + * ## Notes + * + * - The function does **not** perform bounds checking. If an index is less than zero or greater than the maximum index of `x` or `y`, the value of the corresponding element in the respective output array is undefined. + * + * @param x - first input array + * @param y - second input array + * @param indices - list of element indices + * @returns output arrays + * + * @example + * var x = [ 1, 2, 3, 4 ]; + * var y = [ 5, 6, 7, 8 ]; + * var indices = [ 3, 1, 2, 0 ]; + * + * var out = ns.takeIndexed2( x, y, indices ); + * // returns [ [ 4, 2, 3, 1 ], [ 8, 6, 7, 5 ] ] + */ + takeIndexed2: typeof takeIndexed2; + /** * Takes elements from a two-dimensional nested array. * @@ -4153,6 +4777,43 @@ interface Namespace { */ unary3d: typeof unary3d; + /** + * Applies a unary function to each element retrieved from a three-dimensional nested input array according to a callback function and assigns results to elements in a three-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * + * @param arrays - array containing one input nested array and one output nested array + * @param shape - array shape + * @param fcn - unary function to apply to callback return values + * @param clbk - callback function + * @param thisArg - callback execution context + * + * @example + * var ones3d = require( '@stdlib/array/base/ones3d' ); + * var zeros3d = require( '@stdlib/array/base/zeros3d' ); + * + * function accessor( v ) { + * return v - 2.0; + * } + * + * function scale( x ) { + * return x * 10.0; + * } + * + * var shape = [ 1, 2, 2 ]; + * + * var x = ones3d( shape ); + * var y = zeros3d( shape ); + * + * ns.unary3dBy( [ x, y ], shape, scale ); + * + * console.log( y ); + * // => [ [ [ -10.0, -10.0 ], [ -10.0, -10.0 ] ] ] + */ + unary3dBy: typeof unary3dBy; + /** * Applies a unary callback to elements in a four-dimensional nested input array and assigns results to elements in a four-dimensional nested output array. * @@ -4184,6 +4845,43 @@ interface Namespace { */ unary4d: typeof unary4d; + /** + * Applies a unary function to each element retrieved from a four-dimensional nested input array according to a callback function and assigns results to elements in a four-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * + * @param arrays - array containing one input nested array and one output nested array + * @param shape - array shape + * @param fcn - unary function to apply to callback return values + * @param clbk - callback function + * @param thisArg - callback execution context + * + * @example + * var ones4d = require( '@stdlib/array/base/ones4d' ); + * var zeros4d = require( '@stdlib/array/base/zeros4d' ); + * + * function accessor( v ) { + * return v - 2.0; + * } + * + * function scale( x ) { + * return x * 10.0; + * } + * + * var shape = [ 1, 1, 2, 2 ]; + * + * var x = ones4d( shape ); + * var y = zeros4d( shape ); + * + * ns.unary4dBy( [ x, y ], shape, scale ); + * + * console.log( y ); + * // => [ [ [ [ -10.0, -10.0 ], [ -10.0, -10.0 ] ] ] ] + */ + unary4dBy: typeof unary4dBy; + /** * Applies a unary callback to elements in a five-dimensional nested input array and assigns results to elements in a five-dimensional nested output array. * @@ -4215,6 +4913,43 @@ interface Namespace { */ unary5d: typeof unary5d; + /** + * Applies a unary function to each element retrieved from a five-dimensional nested input array according to a callback function and assigns results to elements in a five-dimensional nested output array. + * + * ## Notes + * + * - The function assumes that the input and output arrays have the same shape. + * + * @param arrays - array containing one input nested array and one output nested array + * @param shape - array shape + * @param fcn - unary function to apply to callback return values + * @param clbk - callback function + * @param thisArg - callback execution context + * + * @example + * var ones5d = require( '@stdlib/array/base/ones5d' ); + * var zeros5d = require( '@stdlib/array/base/zeros5d' ); + * + * function accessor( v ) { + * return v - 2.0; + * } + * + * function scale( x ) { + * return x * 10.0; + * } + * + * var shape = [ 1, 1, 1, 2, 2 ]; + * + * var x = ones5d( shape ); + * var y = zeros5d( shape ); + * + * unary2dBy( [ x, y ], shape, scale ); + * + * console.log( y ); + * // => [ [ [ [ [ -10.0, -10.0 ], [ -10.0, -10.0 ] ] ] ] ] + */ + unary5dBy: typeof unary5dBy; + /** * Applies a unary callback to elements in an n-dimensional nested input array and assigns results to elements in an n-dimensional nested output array. * diff --git a/lib/node_modules/@stdlib/array/base/fill/README.md b/lib/node_modules/@stdlib/array/base/fill/README.md new file mode 100644 index 000000000000..ed7a77844aa1 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/README.md @@ -0,0 +1,136 @@ + + +# fill + +> Fill all elements within a portion of an array with a specified value. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var fill = require( '@stdlib/array/base/fill' ); +``` + +#### fill( x, value, start, end ) + +Fills all elements within a portion of an array from an inclusive `start` index to an exclusive `end` index with a specified `value`. + +```javascript +var x = [ 1, 2, 3, 4, 5, 6 ]; + +var out = fill( x, 10, 1, 4 ); +// returns [ 1, 10, 10, 10, 5, 6 ] + +var bool = ( out === x ); +// returns true +``` + +
+ + + + + +
+ +## Notes + +- If provided an array-like object having a `fill` method, the function defers execution to that method and assumes that the method API has the following signature: + + ```text + x.fill( value, start, end ) + ``` + +- If provided an array-like object without a `fill` method, the function manually sets input array elements to a provided fill value. + +- The function **mutates** the input array. + +
+ + + + + +
+ +## Examples + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var fill = require( '@stdlib/array/base/fill' ); + +var x = new Float64Array( zeroTo( 6 ) ); +// returns [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0 ] + +var y = fill( x, 10.0, 0, 6 ); +// returns [ 10.0, 10.0, 10.0, 10.0, 10.0, 10.0 ] + +y = fill( x, 0.0, 0, 4 ); +// returns [ 0.0, 0.0, 0.0, 0.0, 10.0, 10.0 ] + +y = fill( x, 20.0, 2, 6 ); +// returns [ 0.0, 0.0, 20.0, 20.0, 20.0, 20.0 ] + +y = fill( x, 30.0, 2, 4 ); +// returns [ 0.0, 0.0, 30.0, 30.0, 20.0, 20.0 ] +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/array/base/fill/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/fill/benchmark/benchmark.length.js new file mode 100644 index 000000000000..a13928d65ad7 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/benchmark/benchmark.length.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isArray = require( '@stdlib/assert/is-array' ); +var ones = require( '@stdlib/array/base/ones' ); +var pkg = require( './../package.json' ).name; +var fill = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = fill( x, i, 0, len ); + if ( out.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isArray( out ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( pkg+':dtype=generic,len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/fill/docs/repl.txt b/lib/node_modules/@stdlib/array/base/fill/docs/repl.txt new file mode 100644 index 000000000000..0ee0419524ad --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/docs/repl.txt @@ -0,0 +1,40 @@ + +{{alias}}( x, value, start, end ) + Fills all elements within a portion of an array with a specified value. + + If provided an array-like object having a `fill` method, the function + defers execution to that method and assumes that the method has the + following signature: + + x.fill( value, start, end ) + + If provided an array-like object without a `value` method, the function + manually sets input array elements to the specified value. + + Parameters + ---------- + x: ArrayLikeObject + Input array. + + value: any + Fill value. + + start: integer + Starting index (inclusive). + + end: integer + Ending index (exclusive). + + Returns + ------- + out: ArrayLikeObject + Modified input array. + + Examples + -------- + > var out = {{alias}}( [ 1, 2, 3, 4 ], 5, 1, 3 ) + [ 1, 5, 5, 4 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/fill/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/fill/docs/types/index.d.ts new file mode 100644 index 000000000000..f9027b5d1b02 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/docs/types/index.d.ts @@ -0,0 +1,133 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, TypedArray, ComplexTypedArray, BooleanTypedArray } from '@stdlib/types/array'; +import { ComplexLike } from '@stdlib/types/complex'; + +/** +* Fills all elements within a portion of an array with a specified value. +* +* @param x - input array +* @param value - fill value +* @param start - starting index (inclusive) +* @param end - ending index (exclusive) +* @returns modified input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* +* var out = fill( x, 4.0, 0, 3 ); +* // returns [ 4.0, 4.0, 4.0 ] +*/ +declare function fill( x: T, value: number, start: number, end: number ): T; + +/** +* Fills all elements within a portion of an array with a specified value. +* +* @param x - input array +* @param value - fill value +* @param start - starting index (inclusive) +* @param end - ending index (exclusive) +* @returns modified input array +* +* @example +* var BooleanArray = require( '@stdlib/array/bool' ); +* +* var x = new BooleanArray( [ false, false, false ] ); +* +* var out = fill( x, true, 0, 3 ); +* // returns [ true, true, true ] +*/ +declare function fill( x: T, value: boolean, start: number, end: number ): T; // eslint-disable-line @typescript-eslint/unified-signatures + +/** +* Fills all elements within a portion of an array with a specified value. +* +* @param x - input array +* @param value - fill value +* @param start - starting index (inclusive) +* @param end - ending index (exclusive) +* @returns modified input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = fill( x, new Complex128( 7.0, 8.0 ), 0, 3 ); +* // returns [ 7.0, 8.0, 7.0, 8.0, 7.0, 8.0 ] +*/ +declare function fill( x: T, value: ComplexLike, start: number, end: number ): T; // eslint-disable-line @typescript-eslint/unified-signatures + +/** +* Fills all elements within a portion of an array with a specified value. +* +* @param x - input array +* @param value - fill value +* @param start - starting index (inclusive) +* @param end - ending index (exclusive) +* @returns modified input array +* +* @example +* var x = [ 1, 2, 3 ]; +* +* var out = fill( x, 4, 0, 3 ); +* // returns [ 4, 4, 4 ] +* +* @example +* var x = [ 1, 2, 3, 4, 5, 6 ]; +* +* var out = fill( x, 8, 0, 3 ); +* // returns [ 8, 8, 8, 4, 5, 6 ] +*/ +declare function fill( x: Array, value: U, start: number, end: number ): Array; + +/** +* Fills all elements within a portion of an array with a specified value. +* +* @param x - input array +* @param value - fill value +* @param start - starting index (inclusive) +* @param end - ending index (exclusive) +* @returns modified input array +* +* @example +* var x = [ 1, 2, 3 ]; +* +* var out = fill( x, 4, 0, 3 ); +* // returns [ 4, 4, 4 ] +* +* @example +* var x = [ 1, 2, 3, 4, 5, 6 ]; +* +* var out = fill( x, 8, 0, 3 ); +* // returns [ 8, 8, 8, 4, 5, 6 ] +*/ +declare function fill( x: Collection, value: U, start: number, end: number ): Collection; + + +// EXPORTS // + +export = fill; diff --git a/lib/node_modules/@stdlib/array/base/fill/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/fill/docs/types/test.ts new file mode 100644 index 000000000000..e2f69df9c908 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/docs/types/test.ts @@ -0,0 +1,90 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import Complex64Array = require( '@stdlib/array/complex64' ); +import BooleanArray = require( '@stdlib/array/bool' ); +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import fill = require( './index' ); + + +// TESTS // + +// The function returns an array... +{ + const z = new Complex128( 3.0, 5.0 ); + + fill( [ 1, 2, 3 ], 5, 0, 3 ); // $ExpectType number[] + fill( new Float64Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Float64Array + fill( new Float32Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Float32Array + fill( new Int32Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Int32Array + fill( new Int16Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Int16Array + fill( new Int8Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Int8Array + fill( new Uint32Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Uint32Array + fill( new Uint16Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Uint16Array + fill( new Uint8Array( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Uint8Array + fill( new Uint8ClampedArray( [ 1, 2, 3 ] ), 5, 0, 3 ); // $ExpectType Uint8ClampedArray + fill( new Complex128Array( [ 1, 2, 3, 4, 5, 6 ] ), z, 0, 3 ); // $ExpectType Complex128Array + fill( new Complex64Array( [ 1, 2, 3, 4, 5, 6 ] ), z, 0, 3 ); // $ExpectType Complex64Array + fill( new BooleanArray( [ true, false, true, false ] ), false, 0, 3 ); // $ExpectType BooleanArray +} + +// The compiler throws an error if the function is provided a first argument which is not a collection... +{ + fill( 5, 5, 0, 3 ); // $ExpectError + fill( true, 5, 0, 3 ); // $ExpectError + fill( false, 5, 0, 3 ); // $ExpectError + fill( null, 5, 0, 3 ); // $ExpectError + fill( void 0, 5, 0, 3 ); // $ExpectError + fill( {}, 5, 0, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = [ 1, 2, 3 ]; + + fill( x, 5, '5', 3 ); // $ExpectError + fill( x, 5, true, 3 ); // $ExpectError + fill( x, 5, false, 3 ); // $ExpectError + fill( x, 5, null, 3 ); // $ExpectError + fill( x, 5, void 0, 3 ); // $ExpectError + fill( x, 5, {}, 3 ); // $ExpectError + fill( x, 5, ( x: number ): number => x, 3 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = [ 1, 2, 3 ]; + + fill( x, 0, 1, '5' ); // $ExpectError + fill( x, 0, 1, true ); // $ExpectError + fill( x, 0, 1, false ); // $ExpectError + fill( x, 0, 1, null ); // $ExpectError + fill( x, 0, 1, void 0 ); // $ExpectError + fill( x, 0, 1, {} ); // $ExpectError + fill( x, 0, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + fill(); // $ExpectError + fill( [ 1, 2, 3 ] ); // $ExpectError + fill( [ 1, 2, 3 ], 0 ); // $ExpectError + fill( [ 1, 2, 3 ], 0, 1 ); // $ExpectError + fill( [ 1, 2, 3 ], 0, 1, 3, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/fill/examples/index.js b/lib/node_modules/@stdlib/array/base/fill/examples/index.js new file mode 100644 index 000000000000..9a4070f3dcc9 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Float64Array = require( '@stdlib/array/float64' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var fill = require( './../lib' ); + +var x = new Float64Array( zeroTo( 6 ) ); +// returns [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0 ] + +var y = fill( x, 10.0, 0, 6 ); +console.log( y ); +// => [ 10.0, 10.0, 10.0, 10.0, 10.0, 10.0 ] + +y = fill( x, 0.0, 0, 4 ); +console.log( y ); +// => [ 0.0, 0.0, 0.0, 0.0, 10.0, 10.0 ] + +y = fill( x, 20.0, 2, 6 ); +console.log( y ); +// => [ 0.0, 0.0, 20.0, 20.0, 20.0, 20.0 ] + +y = fill( x, 30.0, 2, 4 ); +console.log( y ); +// => [ 0.0, 0.0, 30.0, 30.0, 20.0, 20.0 ] diff --git a/lib/node_modules/@stdlib/array/base/fill/lib/index.js b/lib/node_modules/@stdlib/array/base/fill/lib/index.js new file mode 100644 index 000000000000..930b285d06ea --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/lib/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Fill all elements within a portion of an array with a specified value. +* +* @module @stdlib/array/base/fill +* +* @example +* var fill = require( '@stdlib/array/base/fill' ); +* +* var x = [ 1, 2, 3, 4 ]; +* +* var out = fill( x, 5, 1, 3 ); +* // returns [ 1, 5, 5, 4 ] +* +* var bool = ( out === x ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/fill/lib/main.js b/lib/node_modules/@stdlib/array/base/fill/lib/main.js new file mode 100644 index 000000000000..a4e5b6d6ae92 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/lib/main.js @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); + + +// FUNCTIONS // + +/** +* Tests whether an object has a specified method. +* +* @private +* @param {Object} obj - input object +* @param {string} method - method name +* @returns {boolean} boolean indicating whether an object has a specified method +* +* @example +* var bool = hasMethod( [], 'fill' ); +* // e.g., returns true +* +* @example +* var bool = hasMethod( [], 'beep' ); +* // returns false +*/ +function hasMethod( obj, method ) { + return ( typeof obj[ method ] === 'function' ); +} + +/** +* Fills all elements within a portion of an indexed array with a specified value. +* +* @private +* @param {Collection} x - input array +* @param {*} value - fill value +* @param {integer} start - starting index (inclusive) +* @param {integer} end - ending index (exclusive) +* @returns {Array} output array +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* +* var out = indexed( x, 5, 1, 3 ); +* // returns [ 1, 5, 5, 4 ] +*/ +function indexed( x, value, start, end ) { + var i; + for ( i = start; i < end; i++ ) { + x[ i ] = value; + } + return x; +} + +/** +* Fills all elements within a portion of an accessor array with a specified value. +* +* @private +* @param {Object} x - input array object +* @param {*} value - fill value +* @param {integer} start - starting index (inclusive) +* @param {integer} end - ending index (exclusive) +* @returns {AccessorArray} modified input array +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = toAccessorArray( [ 1, 2, 3, 4 ] ); +* var obj = arraylike2object( x ); +* +* var out = accessors( obj, 5, 1, 3 ); +* // returns +* +* var v = x.get( 0 ); +* // returns 1 +* +* v = x.get( 1 ); +* // returns 5 +* +* v = x.get( 2 ); +* // returns 5 +* +* v = x.get( 3 ); +* // returns 4 +*/ +function accessors( x, value, start, end ) { + var data; + var set; + var i; + + data = x.data; + set = x.accessors[ 1 ]; + for ( i = start; i < end; i++ ) { + set( data, i, value ); + } + return data; +} + + +// MAIN // + +/** +* Fills all elements within a portion of an array with a specified value. +* +* @param {Collection} x - input array +* @param {*} value - fill value +* @param {integer} start - starting index (inclusive) +* @param {integer} end - ending index (exclusive) +* @returns {Collection} output array +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* +* var out = fill( x, 5, 1, 3 ); +* // returns [ 1, 5, 5, 4 ] +* +* var bool = ( out === x ); +* // returns true +* +* @example +* var Int32Array = require( '@stdlib/array/int32' ); +* +* var x = new Int32Array( [ 1, 2, 3, 4 ] ); +* +* var out = fill( x, 5, 1, 3 ); +* // returns [ 1, 5, 5, 4 ] +* +* var bool = ( out === x ); +* // returns true +*/ +function fill( x, value, start, end ) { + var obj; + if ( hasMethod( x, 'fill' ) ) { + return x.fill( value, start, end ); + } + obj = arraylike2object( x ); + if ( obj.accessorProtocol ) { + return accessors( obj, value, start, end ); + } + return indexed( x, value, start, end ); +} + + +// EXPORTS // + +module.exports = fill; diff --git a/lib/node_modules/@stdlib/array/base/fill/package.json b/lib/node_modules/@stdlib/array/base/fill/package.json new file mode 100644 index 000000000000..a53b72b52154 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/package.json @@ -0,0 +1,64 @@ +{ + "name": "@stdlib/array/base/fill", + "version": "0.0.0", + "description": "Fill all elements within a portion of an array with a specified value.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "data", + "structure", + "array", + "generic", + "typed", + "accessor", + "fill", + "set" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/fill/test/test.js b/lib/node_modules/@stdlib/array/base/fill/test/test.js new file mode 100644 index 000000000000..8b0b021070e5 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/fill/test/test.js @@ -0,0 +1,312 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var AccessorArray = require( '@stdlib/array/base/accessor' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Int32Array = require( '@stdlib/array/int32' ); +var fill = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof fill, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function fills an array-like object (generic)', function test( t ) { + var expected; + var actual; + var x; + + x = [ 1, 2, 3 ]; + expected = [ 4, 4, 4 ]; + actual = fill( x, 4, 0, x.length ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = [ 1, 2, 3 ]; + expected = [ 1, 5, 5 ]; + actual = fill( x, 5, 1, x.length ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = [ 1, 2, 3 ]; + expected = [ 1, 5, 3 ]; + actual = fill( x, 5, 1, x.length-1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = [ 1, 2, 3 ]; + expected = [ 1, 2, 3 ]; + actual = fill( x, 5, 1, 1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an array-like object (float64)', function test( t ) { + var expected; + var actual; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + actual = fill( x, 5.0, 0, x.length ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + expected = new Float64Array( [ 1.0, 5.0, 5.0 ] ); + actual = fill( x, 5.0, 1, x.length ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + expected = new Float64Array( [ 1.0, 5.0, 3.0 ] ); + actual = fill( x, 5.0, 1, -1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + expected = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + actual = fill( x, 5.0, 1, 1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an array-like object (int32)', function test( t ) { + var expected; + var actual; + var x; + + x = new Int32Array( [ 1, 2, 3 ] ); + expected = new Int32Array( [ 5, 5, 5 ] ); + actual = fill( x, 5, 0, x.length ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = new Int32Array( [ 1, 2, 3 ] ); + expected = new Int32Array( [ 5, 5, 3 ] ); + actual = fill( x, 5, 0, x.length-1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = new Int32Array( [ 1, 2, 3 ] ); + expected = new Int32Array( [ 5, 2, 3 ] ); + actual = fill( x, 5, 0, x.length-2 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = new Int32Array( [ 1, 2, 3 ] ); + expected = new Int32Array( [ 1, 2, 3 ] ); + actual = fill( x, 5, 0, x.length-3 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an array-like object (accessors)', function test( t ) { + var expected; + var actual; + var obj; + var x; + + x = [ 1, 2, 3, 4 ]; + expected = [ 5, 5, 5, 5 ]; + + obj = new AccessorArray( x ); + actual = fill( obj, 5, 0, x.length ); + + t.strictEqual( actual, obj, 'returns expected value' ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 1, 2, 3, 4 ]; + expected = [ 5, 5, 5, 4 ]; + + obj = new AccessorArray( x ); + actual = fill( obj, 5, 0, x.length-1 ); + + t.strictEqual( actual, obj, 'returns expected value' ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 1, 2, 3, 4 ]; + expected = [ 1, 5, 5, 4 ]; + + obj = new AccessorArray( x ); + actual = fill( obj, 5, 1, x.length-1 ); + + t.strictEqual( actual, obj, 'returns expected value' ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 1, 2, 3, 4 ]; + expected = [ 1, 2, 5, 4 ]; + + obj = new AccessorArray( x ); + actual = fill( obj, 5, 2, x.length-1 ); + + t.strictEqual( actual, obj, 'returns expected value' ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 1, 2, 3, 4 ]; + expected = [ 1, 2, 3, 4 ]; + + obj = new AccessorArray( x ); + actual = fill( obj, 5, 3, x.length-1 ); + + t.strictEqual( actual, obj, 'returns expected value' ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function fills an array-like object (array-like)', function test( t ) { + var expected; + var actual; + var x; + + x = { + 'length': 4, + '0': 1, + '1': 2, + '2': 3, + '3': 4 + }; + expected = { + 'length': 4, + '0': 5, + '1': 5, + '2': 5, + '3': 5 + }; + actual = fill( x, 5, 0, x.length ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = { + 'length': 4, + '0': 1, + '1': 2, + '2': 3, + '3': 4 + }; + expected = { + 'length': 4, + '0': 5, + '1': 5, + '2': 5, + '3': 4 + }; + actual = fill( x, 5, 0, x.length-1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = { + 'length': 4, + '0': 1, + '1': 2, + '2': 3, + '3': 4 + }; + expected = { + 'length': 4, + '0': 1, + '1': 5, + '2': 5, + '3': 4 + }; + actual = fill( x, 5, 1, x.length-1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = { + 'length': 4, + '0': 1, + '1': 2, + '2': 3, + '3': 4 + }; + expected = { + 'length': 4, + '0': 1, + '1': 2, + '2': 5, + '3': 4 + }; + actual = fill( x, 5, 2, x.length-1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + x = { + 'length': 4, + '0': 1, + '1': 2, + '2': 3, + '3': 4 + }; + expected = { + 'length': 4, + '0': 1, + '1': 2, + '2': 3, + '3': 4 + }; + actual = fill( x, 5, 3, x.length-1 ); + + t.strictEqual( actual, x, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns an empty array if provided an array of length `0`', function test( t ) { + var expected; + var actual; + + expected = []; + actual = fill( [], 5, 0, 0 ); + + t.deepEqual( actual, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/filled3d-by/README.md b/lib/node_modules/@stdlib/array/base/filled3d-by/README.md index 6d70dba2a097..ea0c57043e02 100644 --- a/lib/node_modules/@stdlib/array/base/filled3d-by/README.md +++ b/lib/node_modules/@stdlib/array/base/filled3d-by/README.md @@ -134,6 +134,12 @@ out = filled3dBy( [ 1, 1, 3 ], constantFunction( void 0 ) );
+* * * + +## See Also + +- [`@stdlib/array/base/filled3d`][@stdlib/array/base/filled3d]: create a filled three-dimensional nested array. +
@@ -142,6 +148,12 @@ out = filled3dBy( [ 1, 1, 3 ], constantFunction( void 0 ) );
+ + +[@stdlib/array/base/filled3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/filled3d + + +
diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/README.md b/lib/node_modules/@stdlib/array/base/indices-complement/README.md new file mode 100644 index 000000000000..4707b4ed3ebd --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/README.md @@ -0,0 +1,126 @@ + + +# indicesComplement + +> Return the complement of a list of array indices. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var indicesComplement = require( '@stdlib/array/base/indices-complement' ); +``` + +#### indicesComplement( N, indices ) + +Returns the complement of a list of array indices. + +```javascript +var idx = indicesComplement( 5, [ 1, 2 ] ); +// returns [ 0, 3, 4 ] +``` + +The function accepts the following arguments: + +- **N**: array length. +- **indices**: list of indices from which to derive the complement. + +
+ + + + + +
+ +## Notes + +- The function **always** returns a new "generic" array. + +
+ + + + + +
+ +## Examples + + + +```javascript +var indicesComplement = require( '@stdlib/array/base/indices-complement' ); + +var out = indicesComplement( 5, [ 1, 3, 4 ] ); +// returns [ 0, 2 ] + +out = indicesComplement( 5, [ 0, 1 ] ); +// returns [ 2, 3, 4 ] + +out = indicesComplement( 5, [ 0 ] ); +// returns [ 1, 2, 3, 4 ] + +out = indicesComplement( 5, [] ); +// returns [ 0, 1, 2, 3, 4 ] + +out = indicesComplement( 5, [ 0, 1, 2, 3, 4 ] ); +// returns [] +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/indices-complement/benchmark/benchmark.js new file mode 100644 index 000000000000..621c8fa4c18e --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives; +var pkg = require( './../package.json' ).name; +var indicesComplement = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + [ 0, 1 ], + [ 0, 1, 2, 3 ], + [ 0 ], + [], + [ 3, 4 ], + [ 1, 3, 4 ] + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = indicesComplement( 5, values[ i%values.length ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isNonNegativeIntegerArray( out ) ) { + b.fail( 'should return an array of nonnegative integers' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/docs/repl.txt b/lib/node_modules/@stdlib/array/base/indices-complement/docs/repl.txt new file mode 100644 index 000000000000..473054b50842 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( N, indices ) + Returns the complement of a list of array indices. + + Parameters + ---------- + N: integer + Array length. + + indices: Collection + List of indices from which to derive the complement. + + Returns + ------- + out: Array + Indices complement. + + Examples + -------- + > var idx = {{alias}}( 5, [ 1, 3 ] ) + [ 0, 2, 4 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/indices-complement/docs/types/index.d.ts new file mode 100644 index 000000000000..72facd9cb536 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/docs/types/index.d.ts @@ -0,0 +1,41 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Returns the complement of a list of array indices. +* +* @param N - array length +* @param indices - list of indices +* @returns indices complement +* +* @example +* var idx = indicesComplement( 5, [ 1, 3 ] ); +* // returns [ 0, 2, 4 ] +*/ +declare function indicesComplement( N: number, indices: Collection ): Array; + + +// EXPORTS // + +export = indicesComplement; diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/indices-complement/docs/types/test.ts new file mode 100644 index 000000000000..83338158be89 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import indicesComplement = require( './index' ); + + +// TESTS // + +// The function returns an array of numbers... +{ + indicesComplement( 5, [ 0, 1 ] ); // $ExpectType number[] +} + +// The compiler throws an error if the function is provided invalid values... +{ + indicesComplement( true, [ 0, 1 ] ); // $ExpectError + indicesComplement( false, [ 0, 1 ] ); // $ExpectError + indicesComplement( '5', [ 0, 1 ] ); // $ExpectError + indicesComplement( [ '5' ], [ 0, 1 ] ); // $ExpectError + indicesComplement( {}, [ 0, 1 ] ); // $ExpectError + indicesComplement( ( x: number ): number => x, [ 0, 1 ] ); // $ExpectError + + indicesComplement( 5, true ); // $ExpectError + indicesComplement( 5, false ); // $ExpectError + indicesComplement( 5, '5' ); // $ExpectError + indicesComplement( 5, 5 ); // $ExpectError + indicesComplement( 5, {} ); // $ExpectError + indicesComplement( 5, ( x: number ): number => x ); // $ExpectError + + indicesComplement( [], true ); // $ExpectError + indicesComplement( {}, false ); // $ExpectError + indicesComplement( false, '5' ); // $ExpectError + indicesComplement( {}, [] ); // $ExpectError + indicesComplement( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + indicesComplement(); // $ExpectError + indicesComplement( 5 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/examples/index.js b/lib/node_modules/@stdlib/array/base/indices-complement/examples/index.js new file mode 100644 index 000000000000..fc6c316f066f --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var indicesComplement = require( './../lib' ); + +var out = indicesComplement( 5, [ 1, 3, 4 ] ); +console.log( out ); +// => [ 0, 2 ] + +out = indicesComplement( 5, [ 0, 1 ] ); +console.log( out ); +// => [ 2, 3, 4 ] + +out = indicesComplement( 5, [ 0 ] ); +console.log( out ); +// => [ 1, 2, 3, 4 ] + +out = indicesComplement( 5, [] ); +console.log( out ); +// => [ 0, 1, 2, 3, 4 ] + +out = indicesComplement( 5, [ 0, 1, 2, 3, 4 ] ); +console.log( out ); +// => [] diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/lib/index.js b/lib/node_modules/@stdlib/array/base/indices-complement/lib/index.js new file mode 100644 index 000000000000..41e1087ce3b3 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the complement of a list of array indices. +* +* @module @stdlib/array/base/indices-complement +* +* @example +* var indicesComplement = require( '@stdlib/array/base/indices-complement' ); +* +* var idx = indicesComplement( 5, [ 1, 2 ] ); +* // returns [ 0, 3, 4 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/lib/main.js b/lib/node_modules/@stdlib/array/base/indices-complement/lib/main.js new file mode 100644 index 000000000000..b8ad6da913fd --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns the complement of a list of array indices. +* +* @param {NonNegativeInteger} N - array length +* @param {NonNegativeIntegerArray} indices - list of indices +* @returns {NonNegativeIntegerArray} indices complement +* +* @example +* var idx = indicesComplement( 5, [ 1, 2 ] ); +* // returns [ 0, 3, 4 ] +*/ +function indicesComplement( N, indices ) { + var hash; + var out; + var i; + + hash = {}; + for ( i = 0; i < indices.length; i++ ) { + hash[ indices[ i ] ] = true; + } + out = []; + for ( i = 0; i < N; i++ ) { + if ( hash[ i ] === void 0 ) { + out.push( i ); + } + } + return out; +} + + +// EXPORTS // + +module.exports = indicesComplement; diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/package.json b/lib/node_modules/@stdlib/array/base/indices-complement/package.json new file mode 100644 index 000000000000..cae90e96d456 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/array/base/indices-complement", + "version": "0.0.0", + "description": "Return the complement of a list of array indices.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "base", + "array", + "indices", + "index", + "idx", + "ind", + "complement", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/array/base/indices-complement/test/test.js b/lib/node_modules/@stdlib/array/base/indices-complement/test/test.js new file mode 100644 index 000000000000..5ec88a8cc2ef --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/indices-complement/test/test.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isArray = require( '@stdlib/assert/is-array' ); +var indicesComplement = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof indicesComplement, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the complement of a list of indices', function test( t ) { + var expected; + var actual; + var idx; + + idx = [ 0, 2, 3 ]; + expected = [ 1, 4 ]; + + actual = indicesComplement( 5, idx ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + idx = [ 0, 2, 3 ]; + expected = [ 1, 4, 5, 6, 7, 8, 9 ]; + + actual = indicesComplement( 10, idx ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + idx = [ 0, 1, 2, 3, 4 ]; + expected = []; + + actual = indicesComplement( 5, idx ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + idx = []; + expected = [ 0, 1, 2, 3, 4 ]; + + actual = indicesComplement( 5, idx ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/lib/index.js b/lib/node_modules/@stdlib/array/base/lib/index.js index f2e24f3c0a8a..810a98e2856a 100644 --- a/lib/node_modules/@stdlib/array/base/lib/index.js +++ b/lib/node_modules/@stdlib/array/base/lib/index.js @@ -324,6 +324,33 @@ setReadOnly( ns, 'bbinary5d', require( '@stdlib/array/base/broadcasted-binary5d' */ setReadOnly( ns, 'bquaternary2d', require( '@stdlib/array/base/broadcasted-quaternary2d' ) ); +/** +* @name bquaternary3d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-quaternary3d} +*/ +setReadOnly( ns, 'bquaternary3d', require( '@stdlib/array/base/broadcasted-quaternary3d' ) ); + +/** +* @name bquaternary4d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-quaternary4d} +*/ +setReadOnly( ns, 'bquaternary4d', require( '@stdlib/array/base/broadcasted-quaternary4d' ) ); + +/** +* @name bquaternary5d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-quaternary5d} +*/ +setReadOnly( ns, 'bquaternary5d', require( '@stdlib/array/base/broadcasted-quaternary5d' ) ); + /** * @name bquinary2d * @memberof ns @@ -333,6 +360,15 @@ setReadOnly( ns, 'bquaternary2d', require( '@stdlib/array/base/broadcasted-quate */ setReadOnly( ns, 'bquinary2d', require( '@stdlib/array/base/broadcasted-quinary2d' ) ); +/** +* @name bquinary4d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-quinary4d} +*/ +setReadOnly( ns, 'bquinary4d', require( '@stdlib/array/base/broadcasted-quinary4d' ) ); + /** * @name bternary2d * @memberof ns @@ -342,6 +378,33 @@ setReadOnly( ns, 'bquinary2d', require( '@stdlib/array/base/broadcasted-quinary2 */ setReadOnly( ns, 'bternary2d', require( '@stdlib/array/base/broadcasted-ternary2d' ) ); +/** +* @name bternary3d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-ternary3d} +*/ +setReadOnly( ns, 'bternary3d', require( '@stdlib/array/base/broadcasted-ternary3d' ) ); + +/** +* @name bternary4d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-ternary4d} +*/ +setReadOnly( ns, 'bternary4d', require( '@stdlib/array/base/broadcasted-ternary4d' ) ); + +/** +* @name bternary5d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/broadcasted-ternary5d} +*/ +setReadOnly( ns, 'bternary5d', require( '@stdlib/array/base/broadcasted-ternary5d' ) ); + /** * @name bunary2d * @memberof ns @@ -549,6 +612,15 @@ setReadOnly( ns, 'fancySlice', require( '@stdlib/array/base/fancy-slice' ) ); */ setReadOnly( ns, 'fancySliceAssign', require( '@stdlib/array/base/fancy-slice-assign' ) ); +/** +* @name fill +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/fill} +*/ +setReadOnly( ns, 'fill', require( '@stdlib/array/base/fill' ) ); + /** * @name filled * @memberof ns @@ -927,6 +999,15 @@ setReadOnly( ns, 'incrspace', require( '@stdlib/array/base/incrspace' ) ); */ setReadOnly( ns, 'indexOf', require( '@stdlib/array/base/index-of' ) ); +/** +* @name indicesComplement +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/indices-complement} +*/ +setReadOnly( ns, 'indicesComplement', require( '@stdlib/array/base/indices-complement' ) ); + /** * @name join * @memberof ns @@ -1035,6 +1116,33 @@ setReadOnly( ns, 'minUnsignedIntegerDataType', require( '@stdlib/array/base/min- */ setReadOnly( ns, 'mskbinary2d', require( '@stdlib/array/base/mskbinary2d' ) ); +/** +* @name mskbinary3d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskbinary3d} +*/ +setReadOnly( ns, 'mskbinary3d', require( '@stdlib/array/base/mskbinary3d' ) ); + +/** +* @name mskbinary4d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskbinary4d} +*/ +setReadOnly( ns, 'mskbinary4d', require( '@stdlib/array/base/mskbinary4d' ) ); + +/** +* @name mskbinary5d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskbinary5d} +*/ +setReadOnly( ns, 'mskbinary5d', require( '@stdlib/array/base/mskbinary5d' ) ); + /** * @name mskfilter * @memberof ns @@ -1044,6 +1152,33 @@ setReadOnly( ns, 'mskbinary2d', require( '@stdlib/array/base/mskbinary2d' ) ); */ setReadOnly( ns, 'mskfilter', require( '@stdlib/array/base/mskfilter' ) ); +/** +* @name mskfilterMap +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskfilter-map} +*/ +setReadOnly( ns, 'mskfilterMap', require( '@stdlib/array/base/mskfilter-map' ) ); + +/** +* @name mskfilter2 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskfilter2} +*/ +setReadOnly( ns, 'mskfilter2', require( '@stdlib/array/base/mskfilter2' ) ); + +/** +* @name mskfiltern +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskfiltern} +*/ +setReadOnly( ns, 'mskfiltern', require( '@stdlib/array/base/mskfiltern' ) ); + /** * @name mskput * @memberof ns @@ -1080,6 +1215,24 @@ setReadOnly( ns, 'mskunary2d', require( '@stdlib/array/base/mskunary2d' ) ); */ setReadOnly( ns, 'mskunary3d', require( '@stdlib/array/base/mskunary3d' ) ); +/** +* @name mskunary4d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskunary4d} +*/ +setReadOnly( ns, 'mskunary4d', require( '@stdlib/array/base/mskunary4d' ) ); + +/** +* @name mskunary5d +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/mskunary5d} +*/ +setReadOnly( ns, 'mskunary5d', require( '@stdlib/array/base/mskunary5d' ) ); + /** * @name nCartesianProduct * @memberof ns @@ -1323,6 +1476,24 @@ setReadOnly( ns, 'resolveSetter', require( '@stdlib/array/base/resolve-setter' ) */ setReadOnly( ns, 'reverse', require( '@stdlib/array/base/reverse' ) ); +/** +* @name scatterFilled +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/scatter-filled} +*/ +setReadOnly( ns, 'scatterFilled', require( '@stdlib/array/base/scatter-filled' ) ); + +/** +* @name scattered +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/scattered} +*/ +setReadOnly( ns, 'scattered', require( '@stdlib/array/base/scattered' ) ); + /** * @name setter * @memberof ns @@ -1395,6 +1566,15 @@ setReadOnly( ns, 'take', require( '@stdlib/array/base/take' ) ); */ setReadOnly( ns, 'takeIndexed', require( '@stdlib/array/base/take-indexed' ) ); +/** +* @name takeIndexed2 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/take-indexed2} +*/ +setReadOnly( ns, 'takeIndexed2', require( '@stdlib/array/base/take-indexed2' ) ); + /** * @name take2d * @memberof ns @@ -1503,6 +1683,15 @@ setReadOnly( ns, 'unary2dBy', require( '@stdlib/array/base/unary2d-by' ) ); */ setReadOnly( ns, 'unary3d', require( '@stdlib/array/base/unary3d' ) ); +/** +* @name unary3dBy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/unary3d-by} +*/ +setReadOnly( ns, 'unary3dBy', require( '@stdlib/array/base/unary3d-by' ) ); + /** * @name unary4d * @memberof ns @@ -1512,6 +1701,15 @@ setReadOnly( ns, 'unary3d', require( '@stdlib/array/base/unary3d' ) ); */ setReadOnly( ns, 'unary4d', require( '@stdlib/array/base/unary4d' ) ); +/** +* @name unary4dBy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/unary4d-by} +*/ +setReadOnly( ns, 'unary4dBy', require( '@stdlib/array/base/unary4d-by' ) ); + /** * @name unary5d * @memberof ns @@ -1521,6 +1719,15 @@ setReadOnly( ns, 'unary4d', require( '@stdlib/array/base/unary4d' ) ); */ setReadOnly( ns, 'unary5d', require( '@stdlib/array/base/unary5d' ) ); +/** +* @name unary5dBy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/array/base/unary5d-by} +*/ +setReadOnly( ns, 'unary5dBy', require( '@stdlib/array/base/unary5d-by' ) ); + /** * @name unarynd * @memberof ns diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/README.md b/lib/node_modules/@stdlib/array/base/mskfilter-map/README.md index 07368993beef..a617ee2cd7ba 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/README.md +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/README.md @@ -20,7 +20,7 @@ limitations under the License. # mskfilterMap -> Apply a mask to a provided input array and return a new array after applying a mapping function. +> Apply a mask and a callback function to a provided input array.
@@ -32,7 +32,7 @@ var mskfilterMap = require( '@stdlib/array/base/mskfilter-map' ); #### mskfilterMap( x, mask, clbk\[, thisArg] ) -Applies a mask to a provided input array and returns a new array after applying a mapping function. +Returns a new array after applying a mask and a callback function to a provided input array. ```javascript function clbk( value ) { @@ -50,10 +50,10 @@ The function supports the following parameters: - **x**: input array. - **mask**: mask array. -- **clbk**: function to apply. -- **thisArg**: applied function execution context (_optional_). +- **clbk**: callback to apply. +- **thisArg**: callback execution context (_optional_). -To set the applied function's execution context, provide a `thisArg`. +To set the execution context of the callback function, provide a `thisArg`. @@ -81,7 +81,7 @@ The function **always** returns a new "generic" array. #### mskfilterMap.assign( x, mask, out, stride, offset, clbk\[, thisArg] ) -Applies a mask and mapping function to a provided input array and assigns results to elements in a provided output array. +Applies a mask and a callback function to a provided input array and assigns results to elements in a provided output array. ```javascript function clbk( value ) { @@ -106,8 +106,8 @@ The function supports the following parameters: - **out**: output array. - **stride**: output array stride. - **offset**: output array offset. -- **clbk**: function to apply. -- **thisArg**: applied function execution context (_optional_). +- **clbk**: callback function. +- **thisArg**: callback execution context (_optional_).
diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js index 3a6e2bd75bc5..1ce5e32f264c 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.assign.length.js @@ -27,7 +27,7 @@ var zeros = require( '@stdlib/array/zeros' ); var ones = require( '@stdlib/array/ones' ); var isArray = require( '@stdlib/assert/is-array' ); var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; -var identity = require( '@stdlib/math/base/special/identity' ); +var identity = require( '@stdlib/utils/identity-function' ); var pkg = require( './../package.json' ).name; var mskfilterMap = require( './../lib' ); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js index 8a65993f2f60..86c146b031db 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.js @@ -24,7 +24,7 @@ var bench = require( '@stdlib/bench' ); var isArray = require( '@stdlib/assert/is-array' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); -var identity = require( '@stdlib/math/base/special/identity' ); +var identity = require( '@stdlib/utils/identity-function' ); var pkg = require( './../package.json' ).name; var mskfilterMap = require( './../lib' ); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js index ba417028e9df..e095ad90d077 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/benchmark/benchmark.length.js @@ -25,7 +25,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var zeroTo = require( '@stdlib/array/base/zero-to' ); var ones = require( '@stdlib/array/base/ones' ); var isArray = require( '@stdlib/assert/is-array' ); -var identity = require( '@stdlib/math/base/special/identity' ); +var identity = require( '@stdlib/utils/identity-function' ); var pkg = require( './../package.json' ).name; var mskfilterMap = require( './../lib' ); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/repl.txt b/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/repl.txt index 5ab7835f7c17..34e90a68eb81 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/repl.txt +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/repl.txt @@ -1,7 +1,7 @@ -{{alias}}( x, mask, fcn[, thisArg] ) - Applies a mask to a provided input array and returns a new array after - applying a mapping function. +{{alias}}( x, mask, clbk[, thisArg] ) + Returns a new array after applying a mask and a callback function to a + provided input array. If a mask array element is truthy, the corresponding element in `x` is included in the output array; otherwise, the corresponding element in `x` @@ -15,11 +15,11 @@ mask: ArrayLikeObject Mask array. - fcn: Function + clbk: Function Function to apply. thisArg: any (optional) - Function execution context. + Callback execution context. Returns ------- @@ -33,8 +33,8 @@ [ 2, 4 ] -{{alias}}.assign( x, mask, out, stride, offset, fcn[, thisArg] ) - Applies a mask and mapping function to a provided input array and assigns +{{alias}}.assign( x, mask, out, stride, offset, clbk[, thisArg] ) + Applies a mask and a callback function to a provided input array and assigns results to elements in a provided output array. If a mask array element is truthy, the corresponding element in `x` is @@ -58,11 +58,11 @@ offset: integer Output array offset. - fcn: Function + clbk: Function Function to apply. thisArg: any (optional) - Function execution context. + Callback execution context. Returns ------- diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/index.d.ts index bbf5f503d4d4..708c4f8a5c73 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/index.d.ts @@ -20,7 +20,7 @@ /// -import { Array2D, Collection } from '@stdlib/types/array'; +import { Collection } from '@stdlib/types/array'; /** * Callback invoked for each array element. @@ -41,7 +41,7 @@ type Unary = ( this: V, value: T ) => U; * Callback invoked for each array element. * * @param value - array element -* @param indices - current array element indices +* @param index - current array element index * @returns result */ type Binary = ( this: V, value: T, index: number ) => U; @@ -50,17 +50,17 @@ type Binary = ( this: V, value: T, index: number ) => U; * Callback invoked for each array element. * * @param value - array element -* @param indices - current array element indices +* @param index - current array element index * @param array - input array * @returns result */ -type Ternary = ( this: V, value: T, index: number, array: Array2D ) => U; +type Ternary = ( this: V, value: T, index: number, array: Collection ) => U; /** * Callback invoked for each array element. * * @param value - array element -* @param indices - current array element indices +* @param index - current array element index * @param array - input array * @returns result */ @@ -71,12 +71,12 @@ type Callback = Nullary | Unary | Binary | Tern */ interface Routine { /** - * Applies a mask to a provided input array and returns a new array after applying a mapping function. + * Returns a new array after applying a mask and a callback function to a provided input array. * * @param x - input array * @param mask - mask array - * @param clbk - callback to invoke - * @param thisArg - execution context + * @param clbk - callback function + * @param thisArg - callback execution context * @returns output array * * @example @@ -92,15 +92,15 @@ interface Routine { ( x: Collection, mask: Collection, clbk: Callback, thisArg?: ThisParameterType> ): Array; /** - * Applies a mask and mapping function to an input array and assigns results to elements in an output array. + * Applies a mask and a callback function to an input array and assigns results to elements in an output array. * * @param x - input array * @param mask - mask array * @param out - output array * @param stride - output array stride * @param offset - output array offset - * @param clbk - callback to invoke - * @param thisArg - execution context + * @param clbk - callback function + * @param thisArg - callback execution context * @returns output array * * @example @@ -123,12 +123,12 @@ interface Routine { } /** -* Applies a mask to a provided input array and returns a new array after applying a mapping function. +* Returns a new array after applying a mask and a callback function to a provided input array. * * @param x - input array * @param mask - mask array -* @param clbk - callback to invoke -* @param thisArg - execution context +* @param clbk - callback function +* @param thisArg - callback execution context * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/test.ts index 38f6761d45d0..45029b41f407 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/test.ts +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/docs/types/test.ts @@ -19,7 +19,7 @@ import mskfilterMap = require( './index' ); /** -* Unary function. +* Callback function. * * @param value - input value * @returns result @@ -250,6 +250,7 @@ function clbk( value: number ): number { const mask = [ 0.0, 0.0, 0.0, 0.0 ]; mskfilterMap.assign(); // $ExpectError + mskfilterMap.assign( x ); // $ExpectError mskfilterMap.assign( x, mask ); // $ExpectError mskfilterMap.assign( x, mask, [ 0, 0, 0, 0 ] ); // $ExpectError mskfilterMap.assign( x, mask, [ 0, 0, 0, 0 ], 1 ); // $ExpectError diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/assign.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/assign.js index 49189a7425cc..fb398861cbc1 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/assign.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/assign.js @@ -26,7 +26,7 @@ var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); // FUNCTIONS // /** -* Applies a mask and mapping function to an indexed array and assigns results to elements in an indexed output array. +* Applies a mask and a callback function to an indexed array and assigns results to elements in an indexed output array. * * @private * @param {Collection} x - input array @@ -35,7 +35,7 @@ var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); * @param {integer} stride - output array stride * @param {NonNegativeInteger} offset - output array offset * @param {Function} clbk - function to apply -* @param {*} [thisArg] - function execution context +* @param {*} [thisArg] - callback execution context * @returns {Collection} output array * * @example @@ -66,7 +66,7 @@ function indexed( x, mask, out, stride, offset, clbk, thisArg ) { } /** -* Applies a mask and mapping function to an input accessor array and assigns results to elements in an output accessor array. +* Applies a mask and a callback function to an input accessor array and assigns results to elements in an output accessor array. * * @private * @param {Object} x - input array object @@ -75,7 +75,7 @@ function indexed( x, mask, out, stride, offset, clbk, thisArg ) { * @param {integer} stride - output array stride * @param {NonNegativeInteger} offset - output array offset * @param {Function} clbk - function to apply -* @param {*} [thisArg] - function execution context +* @param {*} [thisArg] - callback execution context * @returns {Collection} output array * * @example @@ -130,7 +130,7 @@ function accessors( x, mask, out, stride, offset, clbk, thisArg ) { // MAIN // /** -* Applies a mask and mapping function to a provided input array and assigns results to elements in a provided output array. +* Applies a mask and a callback function to a provided input array and assigns results to elements in a provided output array. * * @param {Collection} x - input array * @param {Collection} mask - mask array @@ -138,7 +138,7 @@ function accessors( x, mask, out, stride, offset, clbk, thisArg ) { * @param {integer} stride - output array stride * @param {NonNegativeInteger} offset - output array offset * @param {Function} clbk - function to apply -* @param {*} [thisArg] - function execution context +* @param {*} [thisArg] - callback execution context * @returns {Collection} output array * * @example diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/index.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/index.js index c131c816d6e9..f9f77206a282 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/index.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Apply a mask to a provided input array and return a new array after applying a mapping function. +* Apply a mask and a callback function to a provided input array. * * @module @stdlib/array/base/mskfilter-map * diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/main.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/main.js index 9f860bbaddd2..048d4a20b552 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/main.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/lib/main.js @@ -26,12 +26,12 @@ var resolveGetter = require( '@stdlib/array/base/resolve-getter' ); // MAIN // /** -* Apply a mask to a provided input array and returns a new array after applying a mapping function. +* Returns a new array after applying a mask and a callback function to a provided input array. * * @param {Collection} x - input array * @param {Collection} mask - mask array -* @param {Function} clbk - callback to invoke -* @param {*} [thisArg] - execution context +* @param {Function} clbk - callback function +* @param {*} [thisArg] - callback execution context * @returns {Array} output array * * @example diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/package.json b/lib/node_modules/@stdlib/array/base/mskfilter-map/package.json index c0b047cd7bc1..a9d9574c49f2 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/package.json +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/array/base/mskfilter-map", "version": "0.0.0", - "description": "Apply a mask to a provided input array.", + "description": "Apply a mask and a callback function to a provided input array.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.assign.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.assign.js index a70f3c13ee05..9c60949e92ae 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.assign.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.assign.js @@ -21,9 +21,9 @@ // MODULES // var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); var Complex64Array = require( '@stdlib/array/complex64' ); var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); -var reinterpret = require( '@stdlib/strided/base/reinterpret-complex' ); var Int32Array = require( '@stdlib/array/int32' ); var zeros = require( '@stdlib/array/zeros' ); var mskfilterMap = require( './../lib' ).assign; @@ -88,8 +88,8 @@ tape( 'the function filters array elements (generic)', function test( t ) { t.end(); - function clbk( val ) { - return val * val; + function clbk( v ) { + return v * v; } }); @@ -144,8 +144,8 @@ tape( 'the function filters array elements (real typed array)', function test( t t.end(); - function clbk( val ) { - return val * val; + function clbk( v ) { + return v * v; } }); @@ -156,59 +156,52 @@ tape( 'the function filters array elements (complex typed array)', function test var out; var x; - x = reinterpret(new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ) ); + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); mask = [ 1, 0 ]; - out = reinterpret( zeros( 1, 'complex64' ) ); + out = zeros( 1, 'complex64' ); actual = mskfilterMap( x, mask, out, 1, 0, clbk ); - expected = reinterpret( new Complex64Array( [ 1.0, 4.0, 25.0, 36.0 ] ) ); + expected = new Complex64Array( [ 1.0, 2.0 ] ); t.strictEqual( actual, out, 'returns expected value' ); - isEqual( actual, expected ); + t.strictEqual( isSameComplex64Array( actual, expected ), true, 'returns expected value' ); mask = [ 0, 0 ]; - out = reinterpret( zeros( 0, 'complex64' ) ); + out = zeros( 0, 'complex64' ); actual = mskfilterMap( x, mask, out, 1, 0, clbk ); - expected = reinterpret( new Complex64Array( [] ) ); + expected = new Complex64Array( [] ); t.strictEqual( actual, out, 'returns expected value' ); - isEqual( actual, expected ); + t.strictEqual( isSameComplex64Array( actual, expected ), true, 'returns expected value' ); mask = [ 0, 1 ]; - out = reinterpret( zeros( 1, 'complex64' ) ); + out = zeros( 1, 'complex64' ); actual = mskfilterMap( x, mask, out, 1, 0, clbk ); - expected = reinterpret( new Complex64Array( [ 9.0, 16.0 ] ) ); + expected = new Complex64Array( [ 3.0, 4.0 ] ); t.strictEqual( actual, out, 'returns expected value' ); - isEqual( actual, expected ); + t.strictEqual( isSameComplex64Array( actual, expected ), true, 'returns expected value' ); mask = [ 1, 1 ]; - out = reinterpret( zeros( 3, 'complex64' ) ); + out = zeros( 3, 'complex64' ); actual = mskfilterMap( x, mask, out, 1, 0, clbk ); - expected = reinterpret( new Complex64Array( [ 1.0, 4.0, 9.0, 16.0 ] ) ); + expected = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 ] ); t.strictEqual( actual, out, 'returns expected value' ); - isEqual( actual, expected ); + t.strictEqual( isSameComplex64Array( actual, expected ), true, 'returns expected value' ); mask = [ 1, 0 ]; - out = reinterpret( zeros( 3, 'complex64' ) ); + out = zeros( 3, 'complex64' ); actual = mskfilterMap( x, mask, out, -2, out.length-1, clbk ); - expected = reinterpret( new Complex64Array( [ 0.0, 0.0, 1.0, 4.0 ] ) ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 1.0, 2.0 ] ); t.strictEqual( actual, out, 'returns expected value' ); - isEqual( actual, expected ); + t.strictEqual( isSameComplex64Array( actual, expected ), true, 'returns expected value' ); t.end(); - function isEqual( actual, expected ) { - var i; - for ( i = 0; i < expected.length; i++ ) { - t.strictEqual( actual.get( i ), expected[ i ], 'returns expected value' ); - } - } - - function clbk( val ) { - return val * val; + function clbk( v ) { + return v; } }); @@ -263,19 +256,19 @@ tape( 'the function filters array elements (accessors)', function test( t ) { t.end(); + function clbk( v ) { + return v * v; + } + function isEqual( actual, expected ) { var i; for ( i = 0; i < expected.length; i++ ) { t.strictEqual( actual.get( i ), expected[ i ], 'returns expected value' ); } } - - function clbk( val ) { - return val * val; - } }); -tape( 'the function returns leaves an output array unchanged if provided a second argument having all element equal to zero ', function test( t ) { +tape( 'the function returns leaves an output array unchanged if provided a second argument having all elements equal to zero ', function test( t ) { var expected; var actual; var mask; @@ -304,22 +297,15 @@ tape( 'the function returns leaves an output array unchanged if provided a secon mask = [ 0, 0 ]; - x = reinterpret( new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ) ); - out = reinterpret( new Complex64Array( [ 0.0, 0.0, 0.0, 0.0 ] ) ); - expected = reinterpret( new Complex64Array( [ 0.0, 0.0, 0.0, 0.0 ] ) ); + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); actual = mskfilterMap( x, mask, out, 1, 0, clbk ); - isEqual( actual, expected ); + t.strictEqual( isSameComplex64Array( actual, expected ), true, 'returns expected value' ); t.end(); - function isEqual( actual, expected ) { - var i; - for ( i = 0; i < expected.length; i++ ) { - t.strictEqual( actual.get( i ), expected[ i ], 'returns expected value' ); - } - } - - function clbk( val ) { - return val * val; + function clbk( v ) { + return v * v; } }); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.main.js b/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.main.js index 7429251591e4..6f74254c1ceb 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.main.js +++ b/lib/node_modules/@stdlib/array/base/mskfilter-map/test/test.main.js @@ -73,8 +73,8 @@ tape( 'the function filters array elements', function test( t ) { t.end(); - function clbk( val ) { - return val * val; + function clbk( v ) { + return v * v; } }); @@ -97,8 +97,8 @@ tape( 'the function filters array elements (accessors)', function test( t ) { } t.end(); - function clbk( val ) { - return val; + function clbk( v ) { + return v; } }); @@ -106,12 +106,12 @@ tape( 'the function returns an empty array if provided empty arrays', function t t.deepEqual( mskfilterMap( [], [], clbk ), [], 'returns expected value' ); t.end(); - function clbk( val ) { - return val * val; + function clbk( v ) { + return v * v; } }); -tape( 'the function supports providing a function execution context', function test( t ) { +tape( 'the function supports providing a callback execution context', function test( t ) { var expected; var indices; var values; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/mskfilter/docs/types/test.ts index 77689758fbc1..b00a181e8d7d 100644 --- a/lib/node_modules/@stdlib/array/base/mskfilter/docs/types/test.ts +++ b/lib/node_modules/@stdlib/array/base/mskfilter/docs/types/test.ts @@ -39,7 +39,7 @@ import mskfilter = require( './index' ); mskfilter( {}, [ 0, 0 ] ); // $ExpectError } -// The compiler throws an error if the function is provided a second argument which is not an array-like object containing numbers... +// The compiler throws an error if the function is provided a second argument which is not an array-like object... { mskfilter( [], 1 ); // $ExpectError mskfilter( [], true ); // $ExpectError diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/README.md b/lib/node_modules/@stdlib/array/base/mskfilter2/README.md new file mode 100644 index 000000000000..2a2996f675a3 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/README.md @@ -0,0 +1,114 @@ + + +# mskfilter2 + +> Apply a mask to two provided input arrays in a single pass. + +
+ +## Usage + +```javascript +var mskfilter2 = require( '@stdlib/array/base/mskfilter2' ); +``` + +#### mskfilter2( x, y, mask ) + +Returns new arrays by applying a mask to two provided input arrays in a single pass. + +```javascript +var x = [ 1, 2, 3, 4 ]; +var y = [ 0, 1, 2, 3 ]; + +var out = mskfilter2( x, y, [ 0, 1, 0, 1 ] ); +// returns [ [ 2, 4 ], [ 1, 3 ] ] +``` + +The function supports the following parameters: + +- **x**: first input array. +- **y**: second input array. +- **mask**: mask array. + +The function **always** returns new "generic" arrays. + +
+ + + +
+ +## Notes + +- If a `mask` array element is truthy, the corresponding elements in the input arrays are **included** in the respective output arrays; otherwise, the corresponding elements in the input arrays are "masked" and thus **excluded** from the respective output arrays. + +
+ + + +
+ +## Examples + + + +```javascript +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var mskfilter2 = require( '@stdlib/array/base/mskfilter2' ); + +// Generate linearly spaced arrays: +var x = zeroTo( 20 ); +console.log( x ); + +var y = zeroTo( x.length ); +console.log( y ); + +// Generate a random mask: +var mask = bernoulli( x.length, 0.5, { + 'dtype': 'generic' +}); +console.log( mask ); + +// Filter both arrays using the mask: +var out = mskfilter2( x, y, mask ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js new file mode 100644 index 000000000000..62a2b7786d5f --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var ones = require( '@stdlib/array/base/ones' ); +var pkg = require( './../package.json' ).name; +var mskfilter2 = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::copy:len=100', function benchmark( b ) { + var x; + var y; + var i; + var v; + + x = zeroTo( 100 ); + y = ones( x.length ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = mskfilter2( x, x, y ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArrayArray( v ) ) { + b.fail( 'should return an array of arrays' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js new file mode 100644 index 000000000000..90a7c730cfe6 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/benchmark/benchmark.length.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var ones = require( '@stdlib/array/base/ones' ); +var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var pkg = require( './../package.json' ).name; +var mskfilter2 = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeroTo( len ); + var y = ones( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = mskfilter2( x, x, y ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArrayArray( v ) ) { + b.fail( 'should return an array of arrays' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/docs/repl.txt b/lib/node_modules/@stdlib/array/base/mskfilter2/docs/repl.txt new file mode 100644 index 000000000000..da35ee919b50 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}( x, y, mask ) + Returns new arrays by applying a mask to two provided input arrays in a + single pass. + + If a mask array element is truthy, the corresponding elements in the input + arrays are included in the respective output arrays; otherwise, the + corresponding elements in the input arrays are "masked" and thus excluded + from the output arrays. + + Parameters + ---------- + x: ArrayLikeObject + First input array. + + y: ArrayLikeObject + Second input array. + + mask: ArrayLikeObject + Mask array. + + Returns + ------- + out: Array + Output arrays. + + Examples + -------- + > var x = [ 1, 2, 3, 4 ]; + > var y = [ 0, 1, 2, 3 ]; + > var out = {{alias}}( x, y, [ 0, 1, 0, 1 ] ) + [ [ 2, 4 ], [ 1, 3 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/mskfilter2/docs/types/index.d.ts new file mode 100644 index 000000000000..f5621cdb5e28 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/docs/types/index.d.ts @@ -0,0 +1,46 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Returns new arrays by applying a mask to two provided input arrays in a single pass. +* +* @param x - first input array +* @param y - second input array +* @param mask - mask array +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfilter2( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ +declare function mskfilter2( x: Collection, y: Collection, mask: Collection ): [ Array, Array ]; + + +// EXPORTS // + +export = mskfilter2; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/mskfilter2/docs/types/test.ts new file mode 100644 index 000000000000..aadb9e8f0848 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/docs/types/test.ts @@ -0,0 +1,68 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import mskfilter2 = require( './index' ); + + +// TESTS // + +// The function returns two arrays... +{ + mskfilter2( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[]] + mskfilter2( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [any[], any[]] + mskfilter2( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[]] + mskfilter2( [ '1', '2', '3', '4' ], [ '1', '2', '3', '4' ], [ 0, 0 ] ); // $ExpectType [string[], string[]] +} + +// The compiler throws an error if the function is provided a first argument which is not an array-like object... +{ + mskfilter2( 1, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfilter2( true, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfilter2( false, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfilter2( null, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfilter2( void 0, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfilter2( {}, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not an array-like object... +{ + mskfilter2( [ 1, 2, 3, 4 ], 1, [ 0, 0 ] ); // $ExpectError + mskfilter2( [ 1, 2, 3, 4 ], true, [ 0, 0 ] ); // $ExpectError + mskfilter2( [ 1, 2, 3, 4 ], false, [ 0, 0 ] ); // $ExpectError + mskfilter2( [ 1, 2, 3, 4 ], null, [ 0, 0 ] ); // $ExpectError + mskfilter2( [ 1, 2, 3, 4 ], void 0, [ 0, 0 ] ); // $ExpectError + mskfilter2( [ 1, 2, 3, 4 ], {}, [ 0, 0 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not an array-like object... +{ + mskfilter2( [], [], 1 ); // $ExpectError + mskfilter2( [], [], true ); // $ExpectError + mskfilter2( [], [], false ); // $ExpectError + mskfilter2( [], [], null ); // $ExpectError + mskfilter2( [], [], void 0 ); // $ExpectError + mskfilter2( [], [], {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + mskfilter2(); // $ExpectError + mskfilter2( [] ); // $ExpectError + mskfilter2( [], [] ); // $ExpectError + mskfilter2( [], [], [], [] ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/examples/index.js b/lib/node_modules/@stdlib/array/base/mskfilter2/examples/index.js new file mode 100644 index 000000000000..9310a20fdcea --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var mskfilter2 = require( './../lib' ); + +// Generate linearly spaced arrays: +var x = zeroTo( 20 ); +console.log( x ); + +var y = zeroTo( x.length ); +console.log( y ); + +// Generate a random mask: +var mask = bernoulli( x.length, 0.5, { + 'dtype': 'generic' +}); +console.log( mask ); + +// Filter both arrays using the mask: +var out = mskfilter2( x, y, mask ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/lib/index.js b/lib/node_modules/@stdlib/array/base/mskfilter2/lib/index.js new file mode 100644 index 000000000000..a0eb1f642ca3 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Apply a mask to two provided input arrays in a single pass. +* +* @module @stdlib/array/base/mskfilter2 +* +* @example +* var mskfilter2 = require( '@stdlib/array/base/mskfilter2' ); +* +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfilter2( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/lib/main.js b/lib/node_modules/@stdlib/array/base/mskfilter2/lib/main.js new file mode 100644 index 000000000000..a29774e6f7db --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/lib/main.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolveGetter = require( '@stdlib/array/base/resolve-getter' ); + + +// MAIN // + +/** +* Returns new arrays by applying a mask to two provided input arrays in a single pass. +* +* @param {Collection} x - first input array +* @param {Collection} y - second input array +* @param {Collection} mask - mask array +* @returns {Array} output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfilter2( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ +function mskfilter2( x, y, mask ) { + var xget; + var yget; + var mget; + var o1; + var o2; + var i; + + // Resolve accessors for retrieving array elements: + xget = resolveGetter( x ); + yget = resolveGetter( y ); + mget = resolveGetter( mask ); + + // Extract each desired element from the provided arrays... + o1 = []; + o2 = []; + for ( i = 0; i < x.length; i++ ) { + if ( mget( mask, i ) ) { + o1.push( xget( x, i ) ); // use `Array#push` to ensure "fast" elements + o2.push( yget( y, i ) ); + } + } + return [ o1, o2 ]; +} + + +// EXPORTS // + +module.exports = mskfilter2; diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/package.json b/lib/node_modules/@stdlib/array/base/mskfilter2/package.json new file mode 100644 index 000000000000..a235eef84199 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/array/base/mskfilter2", + "version": "0.0.0", + "description": "Apply a mask to two provided input arrays in a single pass.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "utilities", + "utils", + "generic", + "array", + "take", + "extract", + "copy", + "index", + "mask", + "filter", + "reject" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/test/test.js b/lib/node_modules/@stdlib/array/base/mskfilter2/test/test.js new file mode 100644 index 000000000000..b346e0768ebd --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/test/test.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var mskfilter2 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mskfilter2, 'function', 'main export is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/mskfilter2/test/test.main.js b/lib/node_modules/@stdlib/array/base/mskfilter2/test/test.main.js new file mode 100644 index 000000000000..4d6716db2104 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfilter2/test/test.main.js @@ -0,0 +1,164 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var BooleanArray = require( '@stdlib/array/bool' ); +var isSameComplex64 = require( '@stdlib/assert/is-same-complex64' ); +var isArray = require( '@stdlib/assert/is-array' ); +var mskfilter2 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mskfilter2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function filters array elements', function test( t ) { + var expected; + var actual; + var mask; + var y; + var x; + + x = [ 1, 2, 3, 4 ]; + y = [ 0, 1, 2, 3 ]; + + mask = [ 0, 1, 0, 1 ]; + actual = mskfilter2( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ 2, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 1, 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + mask = [ 0, 0, 0, 0 ]; + actual = mskfilter2( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = []; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = []; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + mask = [ 0, 0, 0, 1 ]; + actual = mskfilter2( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + mask = [ 1, 1, 1, 1 ]; + actual = mskfilter2( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ 1, 2, 3, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 0, 1, 2, 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function filters array elements (accessors)', function test( t ) { + var expected; + var actual; + var mask; + var y; + var x; + var i; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + y = [ 0, 1, 2, 3 ]; + mask = [ 0, 1, 0, 1 ]; + actual = mskfilter2( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ x.get( 1 ), x.get( 3 ) ]; + for ( i = 0; i < expected.length; i++ ) { + t.strictEqual( isSameComplex64( actual[ 0 ][ i ], expected[ i ] ), true, 'returns expected value' ); + } + expected = [ 1, 3 ]; + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + x = new BooleanArray( [ true, false, false, true ] ); + y = [ 0, 1, 2, 3 ]; + mask = [ 0, 1, 0, 1 ]; + actual = mskfilter2( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ x.get( 1 ), x.get( 3 ) ]; + for ( i = 0; i < expected.length; i++ ) { + t.strictEqual( actual[ 0 ][ i ], expected[ i ], 'returns expected value' ); + } + expected = [ 1, 3 ]; + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns empty arrays if provided empty arrays', function test( t ) { + t.deepEqual( mskfilter2( [], [], [] ), [ [], [] ], 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/README.md b/lib/node_modules/@stdlib/array/base/mskfiltern/README.md new file mode 100644 index 000000000000..95739451c4b5 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/README.md @@ -0,0 +1,114 @@ + + +# mskfiltern + +> Apply a mask to one or more provided input arrays in a single pass. + +
+ +## Usage + +```javascript +var mskfiltern = require( '@stdlib/array/base/mskfiltern' ); +``` + +#### mskfiltern( x, \[...arrays,] mask ) + +Returns new arrays by applying a mask to one or more provided input arrays in a single pass. + +```javascript +var x = [ 1, 2, 3, 4 ]; +var y = [ 0, 1, 2, 3 ]; + +var out = mskfiltern( x, y, [ 0, 1, 0, 1 ] ); +// returns [ [ 2, 4 ], [ 1, 3 ] ] +``` + +The function supports the following parameters: + +- **x**: first input array. +- **...arrays**: additional input arrays. +- **mask**: mask array. + +The function **always** returns new "generic" arrays. + +
+ + + +
+ +## Notes + +- If a `mask` array element is truthy, the corresponding elements in the input arrays are **included** in the respective output arrays; otherwise, the corresponding elements in the input arrays are "masked" and thus **excluded** from the respective output arrays. + +
+ + + +
+ +## Examples + + + +```javascript +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var mskfiltern = require( '@stdlib/array/base/mskfiltern' ); + +// Generate linearly spaced arrays: +var x = zeroTo( 20 ); +console.log( x ); + +var y = zeroTo( x.length ); +console.log( y ); + +// Generate a random mask: +var mask = bernoulli( x.length, 0.5, { + 'dtype': 'generic' +}); +console.log( mask ); + +// Filter both arrays using the mask: +var out = mskfiltern( x, y, mask ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js new file mode 100644 index 000000000000..a2f993868ec0 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var ones = require( '@stdlib/array/base/ones' ); +var pkg = require( './../package.json' ).name; +var mskfiltern = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::copy:num_arrays=2,len=100', function benchmark( b ) { + var x; + var y; + var i; + var v; + + x = zeroTo( 100 ); + y = ones( x.length ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = mskfiltern( x, x, y ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArrayArray( v ) ) { + b.fail( 'should return an array of arrays' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js new file mode 100644 index 000000000000..b0c53e10b5ee --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/benchmark/benchmark.length.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var ones = require( '@stdlib/array/base/ones' ); +var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var pkg = require( './../package.json' ).name; +var mskfiltern = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeroTo( len ); + var y = ones( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = mskfiltern( x, x, y ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArrayArray( v ) ) { + b.fail( 'should return an array of arrays' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':num_arrays=2,len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/docs/repl.txt b/lib/node_modules/@stdlib/array/base/mskfiltern/docs/repl.txt new file mode 100644 index 000000000000..f5d52bc17bcd --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}( x[, ...arrays], mask ) + Returns new arrays by applying a mask to one or more provided input arrays + in a single pass. + + If a mask array element is truthy, the corresponding elements in the input + arrays are included in the respective output arrays; otherwise, the + corresponding elements in the input arrays are "masked" and thus excluded + from the output arrays. + + Parameters + ---------- + x: ArrayLikeObject + First input array. + + arrays: ...ArrayLikeObject (optional) + Additional input arrays. + + mask: ArrayLikeObject + Mask array. + + Returns + ------- + out: Array + Output arrays. + + Examples + -------- + > var x = [ 1, 2, 3, 4 ]; + > var y = [ 0, 1, 2, 3 ]; + > var out = {{alias}}( x, y, [ 0, 1, 0, 1 ] ) + [ [ 2, 4 ], [ 1, 3 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/mskfiltern/docs/types/index.d.ts new file mode 100644 index 000000000000..76527347767f --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/docs/types/index.d.ts @@ -0,0 +1,146 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Returns new arrays by applying a mask to a provided input array in a single pass. +* +* @param x - first input array +* @param mask - mask array +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, mask ); +* // returns [ [ 2, 4 ] ] +*/ +declare function mskfiltern( x: Collection, mask: Collection ): [ Array ]; + +/** +* Returns new arrays by applying a mask to two provided input arrays in a single pass. +* +* @param x - first input array +* @param y - second input array +* @param mask - mask array +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ +declare function mskfiltern( x: Collection, y: Collection, mask: Collection ): [ Array, Array ]; + +/** +* Returns new arrays by applying a mask to three provided input arrays in a single pass. +* +* @param x - first input array +* @param y - second input array +* @param z - third input array +* @param mask - mask array +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var z = [ 1, 1, 1, 1 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, z, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ], [ 1, 1 ] ] +*/ +declare function mskfiltern( x: Collection, y: Collection, z: Collection, mask: Collection ): [ Array, Array, Array ]; + +/** +* Returns new arrays by applying a mask to four provided input arrays in a single pass. +* +* @param x - first input array +* @param y - second input array +* @param z - third input array +* @param u - fourth input array +* @param mask - mask array +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var z = [ 1, 1, 1, 1 ]; +* var u = [ 0, 0, 0, 0 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, z, u, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ], [ 1, 1 ], [ 0, 0 ] ] +*/ +declare function mskfiltern( x: Collection, y: Collection, z: Collection, u: Collection, mask: Collection ): [ Array, Array, Array, Array ]; + +/** +* Returns new arrays by applying a mask to five provided input arrays in a single pass. +* +* @param x - first input array +* @param y - second input array +* @param z - third input array +* @param u - fourth input array +* @param v - fifth input array +* @param mask - mask array +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var z = [ 1, 1, 1, 1 ]; +* var u = [ 0, 0, 0, 0 ]; +* var v = [ 1, 2, 3, 4 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, z, u, v, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ], [ 1, 1 ], [ 0, 0 ], [ 2, 4 ] ] +*/ +declare function mskfiltern( x: Collection, y: Collection, z: Collection, u: Collection, v: Collection, mask: Collection ): [ Array, Array, Array, Array, Array ]; + +/** +* Returns new arrays by applying a mask to one or more provided input arrays in a single pass. +* +* @param x - first input array +* @param y - second input array (or mask) +* @param arrays - additional input arrays and mask +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ +declare function mskfiltern( x: Collection, y: Collection, ...arrays: Array ): Array>; + + +// EXPORTS // + +export = mskfiltern; diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/mskfiltern/docs/types/test.ts new file mode 100644 index 000000000000..2a4553c9edba --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import mskfiltern = require( './index' ); + + +// TESTS // + +// The function returns one or more arrays... +{ + mskfiltern( [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[]] + mskfiltern( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[]] + mskfiltern( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[], number[]] + mskfiltern( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[], number[], number[]] + mskfiltern( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[], number[], number[], number[]] + + mskfiltern( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [any[], any[]] + mskfiltern( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectType [number[], number[]] + mskfiltern( [ '1', '2', '3', '4' ], [ '1', '2', '3', '4' ], [ 0, 0 ] ); // $ExpectType [string[], string[]] +} + +// The compiler throws an error if the function is provided a first argument which is not an array-like object... +{ + mskfiltern( 1, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfiltern( true, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfiltern( false, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfiltern( null, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfiltern( void 0, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError + mskfiltern( {}, [ 1, 2, 3, 4 ], [ 0, 0 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not an array-like object... +{ + mskfiltern( [ 1, 2, 3, 4 ], 1, [ 0, 0 ] ); // $ExpectError + mskfiltern( [ 1, 2, 3, 4 ], true, [ 0, 0 ] ); // $ExpectError + mskfiltern( [ 1, 2, 3, 4 ], false, [ 0, 0 ] ); // $ExpectError + mskfiltern( [ 1, 2, 3, 4 ], null, [ 0, 0 ] ); // $ExpectError + mskfiltern( [ 1, 2, 3, 4 ], void 0, [ 0, 0 ] ); // $ExpectError + mskfiltern( [ 1, 2, 3, 4 ], {}, [ 0, 0 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + mskfiltern(); // $ExpectError + mskfiltern( [] ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/examples/index.js b/lib/node_modules/@stdlib/array/base/mskfiltern/examples/index.js new file mode 100644 index 000000000000..596acf8dc6e5 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var mskfiltern = require( './../lib' ); + +// Generate linearly spaced arrays: +var x = zeroTo( 20 ); +console.log( x ); + +var y = zeroTo( x.length ); +console.log( y ); + +// Generate a random mask: +var mask = bernoulli( x.length, 0.5, { + 'dtype': 'generic' +}); +console.log( mask ); + +// Filter both arrays using the mask: +var out = mskfiltern( x, y, mask ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/lib/index.js b/lib/node_modules/@stdlib/array/base/mskfiltern/lib/index.js new file mode 100644 index 000000000000..94a5399dcd31 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Apply a mask to one or more provided input arrays in a single pass. +* +* @module @stdlib/array/base/mskfiltern +* +* @example +* var mskfiltern = require( '@stdlib/array/base/mskfiltern' ); +* +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/lib/main.js b/lib/node_modules/@stdlib/array/base/mskfiltern/lib/main.js new file mode 100644 index 000000000000..f6931f32979e --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/lib/main.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolveGetter = require( '@stdlib/array/base/resolve-getter' ); + + +// MAIN // + +/** +* Returns new arrays by applying a mask to one or more provided input arrays in a single pass. +* +* @param {Collection} x - first input array +* @param {Collection} [...arrays] - additional input arrays +* @param {Collection} mask - mask array +* @returns {Array} output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var mask = [ 0, 1, 0, 1 ]; +* +* var out = mskfiltern( x, y, mask ); +* // returns [ [ 2, 4 ], [ 6, 8 ] ] +*/ +function mskfiltern() { + var getters; + var arrays; + var nargs; + var mget; + var mask; + var out; + var i; + var j; + + nargs = arguments.length; + nargs -= 1; + + // Resolve the mask array and its associated accessor: + mask = arguments[ nargs ]; + mget = resolveGetter( mask ); + + // Resolve accessors for retrieving array elements and initialize the output arrays... + getters = []; + arrays = []; + out = []; + for ( i = 0; i < nargs; i++ ) { + arrays.push( arguments[ i ] ); + getters.push( resolveGetter( arrays[ i ] ) ); + out.push( [] ); + } + // Extract each desired element from the provided arrays... + for ( i = 0; i < mask.length; i++ ) { + if ( mget( mask, i ) ) { + for ( j = 0; j < nargs; j++ ) { + out[ j ].push( getters[ j ]( arrays[ j ], i ) ); // use `Array#push` to ensure "fast" elements + } + } + } + return out; +} + + +// EXPORTS // + +module.exports = mskfiltern; diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/package.json b/lib/node_modules/@stdlib/array/base/mskfiltern/package.json new file mode 100644 index 000000000000..e6a7666b648e --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/array/base/mskfiltern", + "version": "0.0.0", + "description": "Apply a mask to one or more provided input arrays in a single pass.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "utilities", + "utils", + "generic", + "array", + "take", + "extract", + "copy", + "index", + "mask", + "filter", + "reject" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/test/test.js b/lib/node_modules/@stdlib/array/base/mskfiltern/test/test.js new file mode 100644 index 000000000000..dc1236c6e23b --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/test/test.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var mskfiltern = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mskfiltern, 'function', 'main export is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/mskfiltern/test/test.main.js b/lib/node_modules/@stdlib/array/base/mskfiltern/test/test.main.js new file mode 100644 index 000000000000..4ca97c4da187 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/mskfiltern/test/test.main.js @@ -0,0 +1,257 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var BooleanArray = require( '@stdlib/array/bool' ); +var isSameComplex64 = require( '@stdlib/assert/is-same-complex64' ); +var isArray = require( '@stdlib/assert/is-array' ); +var mskfiltern = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mskfiltern, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function filters array elements (1 array)', function test( t ) { + var expected; + var actual; + var mask; + var x; + + x = [ 1, 2, 3, 4 ]; + + mask = [ 0, 1, 0, 1 ]; + actual = mskfiltern( x, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 1, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + + expected = [ 2, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + mask = [ 0, 0, 0, 0 ]; + actual = mskfiltern( x, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 1, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + + expected = []; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + mask = [ 0, 0, 0, 1 ]; + actual = mskfiltern( x, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 1, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + + expected = [ 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + mask = [ 1, 1, 1, 1 ]; + actual = mskfiltern( x, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 1, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + + expected = [ 1, 2, 3, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function filters array elements (2 arrays)', function test( t ) { + var expected; + var actual; + var mask; + var y; + var x; + + x = [ 1, 2, 3, 4 ]; + y = [ 0, 1, 2, 3 ]; + + mask = [ 0, 1, 0, 1 ]; + actual = mskfiltern( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ 2, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 1, 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + mask = [ 0, 0, 0, 0 ]; + actual = mskfiltern( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = []; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = []; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + mask = [ 0, 0, 0, 1 ]; + actual = mskfiltern( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + mask = [ 1, 1, 1, 1 ]; + actual = mskfiltern( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ 1, 2, 3, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 0, 1, 2, 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function filters array elements (3 arrays)', function test( t ) { + var expected; + var actual; + var mask; + var x; + var y; + var z; + + x = [ 1, 2, 3, 4 ]; + y = [ 0, 1, 2, 3 ]; + z = [ 5, 6, 7, 8 ]; + + mask = [ 0, 1, 0, 1 ]; + actual = mskfiltern( x, y, z, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 3, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 2 ] ), true, 'returns expected value' ); + + expected = [ 2, 4 ]; + t.notEqual( actual[ 0 ], x, 'returns expected value' ); + t.deepEqual( actual[ 0 ], expected, 'returns expected value' ); + + expected = [ 1, 3 ]; + t.notEqual( actual[ 1 ], y, 'returns expected value' ); + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + expected = [ 6, 8 ]; + t.notEqual( actual[ 2 ], z, 'returns expected value' ); + t.deepEqual( actual[ 2 ], expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function filters array elements (2 arrays; accessors)', function test( t ) { + var expected; + var actual; + var mask; + var y; + var x; + var i; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + y = [ 0, 1, 2, 3 ]; + mask = [ 0, 1, 0, 1 ]; + actual = mskfiltern( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ x.get( 1 ), x.get( 3 ) ]; + for ( i = 0; i < expected.length; i++ ) { + t.strictEqual( isSameComplex64( actual[ 0 ][ i ], expected[ i ] ), true, 'returns expected value' ); + } + expected = [ 1, 3 ]; + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + x = new BooleanArray( [ true, false, false, true ] ); + y = [ 0, 1, 2, 3 ]; + mask = [ 0, 1, 0, 1 ]; + actual = mskfiltern( x, y, mask ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.strictEqual( actual.length, 2, 'returns expected value' ); + t.strictEqual( isArray( actual[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isArray( actual[ 1 ] ), true, 'returns expected value' ); + + expected = [ x.get( 1 ), x.get( 3 ) ]; + for ( i = 0; i < expected.length; i++ ) { + t.strictEqual( actual[ 0 ][ i ], expected[ i ], 'returns expected value' ); + } + expected = [ 1, 3 ]; + t.deepEqual( actual[ 1 ], expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns empty arrays if provided empty arrays', function test( t ) { + t.deepEqual( mskfiltern( [], [] ), [ [] ], 'returns expected value' ); + t.deepEqual( mskfiltern( [], [], [] ), [ [], [] ], 'returns expected value' ); + t.deepEqual( mskfiltern( [], [], [], [] ), [ [], [], [] ], 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/mskreject/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/mskreject/docs/types/test.ts index af46bf6080a0..dc6498141977 100644 --- a/lib/node_modules/@stdlib/array/base/mskreject/docs/types/test.ts +++ b/lib/node_modules/@stdlib/array/base/mskreject/docs/types/test.ts @@ -39,7 +39,7 @@ import mskreject = require( './index' ); mskreject( {}, [ 0, 0 ] ); // $ExpectError } -// The compiler throws an error if the function is provided a second argument which is not an array-like object containing numbers... +// The compiler throws an error if the function is provided a second argument which is not an array-like object... { mskreject( [], 1 ); // $ExpectError mskreject( [], true ); // $ExpectError diff --git a/lib/node_modules/@stdlib/array/base/ones/README.md b/lib/node_modules/@stdlib/array/base/ones/README.md index 1fd7cb3eea27..be21bf154635 100644 --- a/lib/node_modules/@stdlib/array/base/ones/README.md +++ b/lib/node_modules/@stdlib/array/base/ones/README.md @@ -103,6 +103,17 @@ console.log( arr );
+* * * + +## See Also + +- [`@stdlib/array/base/zeros`][@stdlib/array/base/zeros]: create a zero-filled generic array. +- [`@stdlib/array/base/ones2d`][@stdlib/array/base/ones2d]: create a two-dimensional nested array filled with ones. +- [`@stdlib/array/base/ones3d`][@stdlib/array/base/ones3d]: create a three-dimensional nested array filled with ones. +- [`@stdlib/array/base/ones4d`][@stdlib/array/base/ones4d]: create a four-dimensional nested array filled with ones. +- [`@stdlib/array/base/ones5d`][@stdlib/array/base/ones5d]: create a five-dimensional nested array filled with ones. +- [`@stdlib/array/base/onesnd`][@stdlib/array/base/onesnd]: create an n-dimensional nested array filled with ones. +
@@ -111,6 +122,22 @@ console.log( arr );
+ + +[@stdlib/array/base/zeros]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros + +[@stdlib/array/base/ones2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones2d + +[@stdlib/array/base/ones3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones3d + +[@stdlib/array/base/ones4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones4d + +[@stdlib/array/base/ones5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones5d + +[@stdlib/array/base/onesnd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/onesnd + + +
diff --git a/lib/node_modules/@stdlib/array/base/ones4d/README.md b/lib/node_modules/@stdlib/array/base/ones4d/README.md index 6c9020181acf..9a5cc12705d3 100644 --- a/lib/node_modules/@stdlib/array/base/ones4d/README.md +++ b/lib/node_modules/@stdlib/array/base/ones4d/README.md @@ -95,6 +95,17 @@ out = ones4d( [ 1, 1, 3, 1 ] );
+* * * + +## See Also + +- [`@stdlib/array/base/zeros4d`][@stdlib/array/base/zeros4d]: create a zero-filled four-dimensional nested array. +- [`@stdlib/array/base/ones`][@stdlib/array/base/ones]: create a generic array filled with ones. +- [`@stdlib/array/base/ones2d`][@stdlib/array/base/ones2d]: create a two-dimensional nested array filled with ones. +- [`@stdlib/array/base/ones3d`][@stdlib/array/base/ones3d]: create a three-dimensional nested array filled with ones. +- [`@stdlib/array/base/ones5d`][@stdlib/array/base/ones5d]: create a five-dimensional nested array filled with ones. +- [`@stdlib/array/base/onesnd`][@stdlib/array/base/onesnd]: create an n-dimensional nested array filled with ones. +
@@ -103,6 +114,22 @@ out = ones4d( [ 1, 1, 3, 1 ] );
+ + +[@stdlib/array/base/zeros4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros4d + +[@stdlib/array/base/ones]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones + +[@stdlib/array/base/ones2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones2d + +[@stdlib/array/base/ones3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones3d + +[@stdlib/array/base/ones5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones5d + +[@stdlib/array/base/onesnd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/onesnd + + +
diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/README.md b/lib/node_modules/@stdlib/array/base/scatter-filled/README.md new file mode 100644 index 000000000000..10320768224c --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/README.md @@ -0,0 +1,121 @@ + + +# scatterFilled + +> Scatter a list of provided values to specified indices in a new filled "generic" array. + +
+ +## Usage + +```javascript +var scatterFilled = require( '@stdlib/array/base/scatter-filled' ); +``` + +#### scatterFilled( fill, len, indices, values, mode ) + +Scatters a list of provided values to specified indices in a new filled "generic" array. + +```javascript +var out = scatterFilled( null, 4, [ 1, 3 ], [ 20, 40 ], 'throw' ); +// returns [ null, 20, null, 40 ] +``` + +The function supports the following parameters: + +- **fill**: fill value. +- **len**: output array length. +- **indices**: list of indices. +- **values**: values to scatter. When `indices` contains one or more elements, `values` must be broadcast [compatible][@stdlib/ndarray/base/broadcast-shapes] with `indices` (i.e., must have either one element or the same number of elements as `indices`). +- **mode**: index [mode][@stdlib/ndarray/base/ind]. + +If `indices` is an empty array, the function returns a filled array. + +```javascript +var out = scatterFilled( null, 4, [], [ 20, 40 ], 'throw' ); +// returns [ null, null, null, null ] +``` + +The function supports broadcasting a `values` array containing a single element against an `indices` array containing one or more elements. + +```javascript +var out = scatterFilled( null, 4, [ 1, 3 ], [ 20 ], 'throw' ); +// returns [ null, 20, null, 20 ] +``` + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var scatterFilled = require( '@stdlib/array/base/scatter-filled' ); + +// Generate an array of random indices: +var N = discreteUniform( 5, 15 ); +var indices = filledBy( N, discreteUniform.factory( 0, 10 ) ); +console.log( indices ); + +// Generate an array of random values: +var values = filledBy( N, discreteUniform.factory( 1000, 2025 ) ); +console.log( values ); + +// Scatter a random sample of elements to a new array: +var out = scatterFilled( null, 11, indices, values, 'throw' ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/base/ind]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/ind + +[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes + +
+ + diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/scatter-filled/benchmark/benchmark.js new file mode 100644 index 000000000000..bf9906654373 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/benchmark/benchmark.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isArray = require( '@stdlib/assert/is-array' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var pkg = require( './../package.json' ).name; +var scatterFilled = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::no_broadcasting:len=100', function benchmark( b ) { + var idx; + var x; + var i; + var v; + + x = zeroTo( 100 ); + idx = zeroTo( 100 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = scatterFilled( -1, x.length, idx, x, 'throw' ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::broadcasting:len=100', function benchmark( b ) { + var idx; + var i; + var v; + + idx = zeroTo( 100 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = scatterFilled( -1, 100, idx, [ i ], 'throw' ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/scatter-filled/benchmark/benchmark.length.js new file mode 100644 index 000000000000..8eb15d4771d0 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/benchmark/benchmark.length.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var isArray = require( '@stdlib/assert/is-array' ); +var pkg = require( './../package.json' ).name; +var scatterFilled = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var values; + var idx; + + idx = zeroTo( len ); + values = [ + discreteUniform( len, -10, 0, opts ), + discreteUniform( len, 0, 10, opts ) + ]; + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = scatterFilled( -999, len, idx, values[ i%values.length ], 'throw' ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/docs/repl.txt b/lib/node_modules/@stdlib/array/base/scatter-filled/docs/repl.txt new file mode 100644 index 000000000000..fc95f32cc160 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/docs/repl.txt @@ -0,0 +1,48 @@ + +{{alias}}( fill, len, indices, values, mode ) + Scatters a list of provided values to specified indices in a new filled + "generic" array. + + The function supports broadcasting a `values` array containing a single + element against an `indices` array containing one or more elements. + + If `indices` is an empty array, the function returns a filled array. + + Parameters + ---------- + fill: any + Fill value. + + len: integer + Output array length. + + indices: ArrayLikeObject + List of element indices. + + values: ArrayLikeObject + Values to scatter. When `indices` contains one or more elements, + `values` must be broadcast compatible with `indices` (i.e., must have + either one element or the same number of elements as `indices`). + + mode: string + Specifies how to handle an index outside the interval [0, max], where + `max` is the maximum possible array index. If equal to 'throw', the + function throws an error. If equal to 'normalize', the function throws + an error if provided an out-of-bounds normalized index. If equal to + 'wrap', the function wraps around an index using modulo arithmetic. If + equal to 'clamp', the function sets an index to either 0 (minimum index) + or the maximum index. + + Returns + ------- + out: Array + Output array. + + Examples + -------- + > var out = {{alias}}( null, 4, [ 1, 3 ], [ 20, 40 ], 'throw' ) + [ null, 20, null, 40 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/scatter-filled/docs/types/index.d.ts new file mode 100644 index 000000000000..f6d9d77e952d --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; +import { Mode } from '@stdlib/types/ndarray'; + +/** +* Index array. +*/ +type IndexArray = Collection | AccessorArrayLike; + +/** +* Values array. +*/ +type ValuesArray = Collection | AccessorArrayLike; + +/** +* Scatters a list of provided values to specified indices in a new filled "generic" array. +* +* @param fill - fill value +* @param len - output array length +* @param indices - list of element indices +* @param values - values to scatter +* @param mode - index mode +* @returns output array +* +* @example +* var indices = [ 1, 2 ]; +* var values = [ 20, 30 ]; +* +* var out = scatterFilled( null, 4, indices, values, 'throw' ); +* // returns [ null, 20, 30, null ] +* +* @example +* var out = scatterFilled( null, 4, [ 1, 2 ], [ 30 ], 'throw' ); +* // returns [ null, 30, 30, null ] +*/ +declare function scatterFilled( fill: T, len: number, indices: IndexArray, values: ValuesArray, mode: Mode ): Array; + + +// EXPORTS // + +export = scatterFilled; diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/scatter-filled/docs/types/test.ts new file mode 100644 index 000000000000..b9a135a86a01 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/docs/types/test.ts @@ -0,0 +1,92 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import scatterFilled = require( './index' ); + + +// TESTS // + +// The function returns an array... +{ + const z = new Complex128( 3.0, 4.0 ); + + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectType (number | null)[] + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], 'clamp' ); // $ExpectType (number | null)[] + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], 'wrap' ); // $ExpectType (number | null)[] + scatterFilled( null, 4, [ 1, 3 ], [ true, true ], 'normalize' ); // $ExpectType (boolean | null)[] + + scatterFilled( null, 4, [ 1, 3 ], [ z, z ], 'throw' ); // $ExpectType (Complex128 | null)[] + scatterFilled( null, 4, [ 1, 3 ], [ z, z ], 'throw' ); // $ExpectType (Complex128 | null)[] + scatterFilled( null, 4, [ 1, 3 ], new AccessorArray( [ 20, 30 ] ), 'throw' ); // $ExpectType (number | null)[] +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + scatterFilled( null, '1', [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, true, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, false, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, null, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, void 0, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, [], [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, {}, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not an array-like object containing numbers... +{ + scatterFilled( null, 4, 1, [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, 4, true, [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, 4, false, [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, 4, null, [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, 4, void 0, [ 20, 30 ], 'throw' ); // $ExpectError + scatterFilled( null, 4, {}, [ 20, 30 ], 'throw' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not an array-like object... +{ + scatterFilled( null, 4, [ 1, 3 ], 1, 'throw' ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], true, 'throw' ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], false, 'throw' ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], null, 'throw' ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], void 0, 'throw' ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], {}, 'throw' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a valid index mode... +{ + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], '1' ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], 1 ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], true ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], false ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], null ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], void 0 ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], {} ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], [] ); // $ExpectError + scatterFilled( null, 4, [ 1, 3 ], [ 20, 30 ], ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + scatterFilled(); // $ExpectError + scatterFilled( null ); // $ExpectError + scatterFilled( null, 4 ); // $ExpectError + scatterFilled( null, 4, [] ); // $ExpectError + scatterFilled( null, 4, [], [] ); // $ExpectError + scatterFilled( null, 4, [], [], 'throw', {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/examples/index.js b/lib/node_modules/@stdlib/array/base/scatter-filled/examples/index.js new file mode 100644 index 000000000000..03dd776085e1 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var scatterFilled = require( './../lib' ); + +// Generate an array of random indices: +var N = discreteUniform( 5, 15 ); +var indices = filledBy( N, discreteUniform.factory( 0, 10 ) ); +console.log( indices ); + +// Generate an array of random values: +var values = filledBy( N, discreteUniform.factory( 1000, 2025 ) ); +console.log( values ); + +// Scatter a random sample of elements to a new array: +var out = scatterFilled( null, 11, indices, values, 'throw' ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/lib/index.js b/lib/node_modules/@stdlib/array/base/scatter-filled/lib/index.js new file mode 100644 index 000000000000..dc54ffcefa0d --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Scatter a list of provided values to specified indices in a new filled "generic" array. +* +* @module @stdlib/array/base/scatter-filled +* +* @example +* var scatterFilled = require( '@stdlib/array/base/scatter-filled' ); +* +* var indices = [ 1, 2 ]; +* var values = [ 20, 30 ]; +* +* var out = scatterFilled( null, 4, indices, values, 'throw' ); +* // returns [ null, 20, 30, null ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/lib/main.js b/lib/node_modules/@stdlib/array/base/scatter-filled/lib/main.js new file mode 100644 index 000000000000..4de51bed2c2a --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/lib/main.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var filled = require( '@stdlib/array/base/filled' ); +var put = require( '@stdlib/array/base/put' ); + + +// MAIN // + +/** +* Scatters a list of provided values to specified indices in a new filled "generic" array. +* +* @param {*} fill - fill value +* @param {NonNegativeInteger} len - output array length +* @param {IntegerArray} indices - list of indices +* @param {Collection} values - values to scatter +* @param {string} mode - index mode +* @throws {Error} third argument must be broadcast compatible with the second argument +* @returns {Array} output array +* +* @example +* var indices = [ 1, 2 ]; +* var values = [ 20, 30 ]; +* +* var out = scatterFilled( null, 4, indices, values, 'throw' ); +* // returns [ null, 20, 30, null ] +* +* @example +* var indices = [ 1, 2 ]; +* var values = [ 30 ]; +* +* var out = scatterFilled( null, 4, indices, values, 'throw' ); +* // returns [ null, 30, 30, null ] +*/ +function scatterFilled( fill, len, indices, values, mode ) { + return put( filled( fill, len ), indices, values, mode ); +} + + +// EXPORTS // + +module.exports = scatterFilled; diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/package.json b/lib/node_modules/@stdlib/array/base/scatter-filled/package.json new file mode 100644 index 000000000000..21fbd5e27fd9 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/package.json @@ -0,0 +1,62 @@ +{ + "name": "@stdlib/array/base/scatter-filled", + "version": "0.0.0", + "description": "Scatter a list of provided values to specified indices in a new filled \"generic\" array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "utilities", + "utils", + "generic", + "array", + "set", + "scatter", + "filled", + "fill" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/scatter-filled/test/test.js b/lib/node_modules/@stdlib/array/base/scatter-filled/test/test.js new file mode 100644 index 000000000000..4de7827ed4fd --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scatter-filled/test/test.js @@ -0,0 +1,203 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isArray = require( '@stdlib/assert/is-array' ); +var scatterFilled = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof scatterFilled, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a fourth argument which is not broadcast compatible with the second argument', function test( t ) { + var values; + var i; + + values = [ + [], + [ 1, 2, 3 ], + [ 1, 2, 3, 4 ], + [ 1, 2, 3, 4, 5 ] + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided an array of length ' + values[ i ].length ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + scatterFilled( null, 4, [ 1, 2 ], value, 'throw' ); + }; + } +}); + +tape( 'the function scatters elements to a new array', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ 1, 3 ]; + actual = scatterFilled( null, 4, indices, [ 20, 40 ], 'throw' ); + expected = [ null, 20, null, 40 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 3, 3 ]; + actual = scatterFilled( null, 4, indices, [ 20, 30, 40, 50 ], 'throw' ); + expected = [ null, 30, null, 50 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 3, 2, 1, 0 ]; + actual = scatterFilled( null, 4, indices, [ 20, 30, 40, 50 ], 'throw' ); + expected = [ 50, 40, 30, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + actual = scatterFilled( null, 4, indices, [ 100, 100, 100, 100, 100, 100, 100, 100, 100, 100 ], 'throw' ); + expected = [ null, 100, null, null ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function scatters elements to a new array (broadcasting)', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ 1, 3 ]; + actual = scatterFilled( null, 4, indices, [ 20 ], 'throw' ); + expected = [ null, 20, null, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 3, 3 ]; + actual = scatterFilled( null, 4, indices, [ 20 ], 'throw' ); + expected = [ null, 20, null, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 3, 2, 1, 0 ]; + actual = scatterFilled( null, 4, indices, [ 20 ], 'throw' ); + expected = [ 20, 20, 20, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + actual = scatterFilled( null, 4, indices, [ 100 ], 'throw' ); + expected = [ null, 100, null, null ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a filled array if provided a second argument which is empty', function test( t ) { + var actual; + + actual = scatterFilled( null, 4, [], [ 5, 6, 7, 8 ], 'throw' ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, [ null, null, null, null ], 'returns expected value' ); + + t.end(); +}); + +tape( 'when the "mode" is "throw", the function throws an error if provided an out-of-bounds index', function test( t ) { + var indices; + + indices = [ 4, 5, 1, 2 ]; + + t.throws( badValue, RangeError, 'throws an error' ); + t.end(); + + function badValue() { + scatterFilled( null, 4, indices, [ 200 ], 'throw' ); + } +}); + +tape( 'when the "mode" is "normalize", the function normalizes negative indices', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ -1, -2, -3, -4 ]; + actual = scatterFilled( null, 4, indices, [ 5, 6, 7, 8 ], 'normalize' ); + expected = [ 8, 7, 6, 5 ]; + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'when the "mode" is "normalize", the function throws an error if provided an out-of-bounds index', function test( t ) { + var indices; + + indices = [ 2, 50, 1, 2 ]; + + t.throws( badValue, RangeError, 'throws an error' ); + t.end(); + + function badValue() { + scatterFilled( null, 4, indices, [ 100 ], 'normalize' ); + } +}); + +tape( 'when the "mode" is "clamp", the function clamps out-of-bounds indices', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ -10, 10, -5, 5 ]; + actual = scatterFilled( null, 4, indices, [ 100, 200, 300, 400 ], 'clamp' ); + expected = [ 300, null, null, 400 ]; + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'when the "mode" is "wrap", the function wraps out-of-bounds indices', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ -10, 10, -5, 5 ]; + actual = scatterFilled( null, 4, indices, [ 100, 200, 300, 400 ], 'wrap' ); + expected = [ null, 400, 200, 300 ]; + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/scattered/README.md b/lib/node_modules/@stdlib/array/base/scattered/README.md new file mode 100644 index 000000000000..73d289de1498 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/README.md @@ -0,0 +1,120 @@ + + +# scattered + +> Scatter a list of provided values to specified indices in a new zero-filled "generic" array. + +
+ +## Usage + +```javascript +var scattered = require( '@stdlib/array/base/scattered' ); +``` + +#### scattered( len, indices, values, mode ) + +Scatters a list of provided values to specified indices in a new zero-filled "generic" array. + +```javascript +var out = scattered( 4, [ 1, 3 ], [ 20, 40 ], 'throw' ); +// returns [ 0, 20, 0, 40 ] +``` + +The function supports the following parameters: + +- **len**: output array length. +- **indices**: list of indices. +- **values**: values to scatter. When `indices` contains one or more elements, `values` must be broadcast [compatible][@stdlib/ndarray/base/broadcast-shapes] with `indices` (i.e., must have either one element or the same number of elements as `indices`). +- **mode**: index [mode][@stdlib/ndarray/base/ind]. + +If `indices` is an empty array, the function returns a zero-filled array. + +```javascript +var out = scattered( 4, [], [ 20, 40 ], 'throw' ); +// returns [ 0, 0, 0, 0 ] +``` + +The function supports broadcasting a `values` array containing a single element against an `indices` array containing one or more elements. + +```javascript +var out = scattered( 4, [ 1, 3 ], [ 20 ], 'throw' ); +// returns [ 0, 20, 0, 20 ] +``` + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var scattered = require( '@stdlib/array/base/scattered' ); + +// Generate an array of random indices: +var N = discreteUniform( 5, 15 ); +var indices = filledBy( N, discreteUniform.factory( 0, 10 ) ); +console.log( indices ); + +// Generate an array of random values: +var values = filledBy( N, discreteUniform.factory( 1000, 2025 ) ); +console.log( values ); + +// Scatter a random sample of elements to a new array: +var out = scattered( 11, indices, values, 'throw' ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/base/ind]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/ind + +[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes + +
+ + diff --git a/lib/node_modules/@stdlib/array/base/scattered/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/scattered/benchmark/benchmark.js new file mode 100644 index 000000000000..41120235e615 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/benchmark/benchmark.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isArray = require( '@stdlib/assert/is-array' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var pkg = require( './../package.json' ).name; +var scattered = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::no_broadcasting:len=100', function benchmark( b ) { + var idx; + var x; + var i; + var v; + + x = zeroTo( 100 ); + idx = zeroTo( 100 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = scattered( x.length, idx, x, 'throw' ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::broadcasting:len=100', function benchmark( b ) { + var idx; + var i; + var v; + + idx = zeroTo( 100 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = scattered( 100, idx, [ i ], 'throw' ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/scattered/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/scattered/benchmark/benchmark.length.js new file mode 100644 index 000000000000..4294a447eef3 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/benchmark/benchmark.length.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var isArray = require( '@stdlib/assert/is-array' ); +var pkg = require( './../package.json' ).name; +var scattered = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var values; + var idx; + + idx = zeroTo( len ); + values = [ + discreteUniform( len, -10, 0, opts ), + discreteUniform( len, 0, 10, opts ) + ]; + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = scattered( len, idx, values[ i%values.length ], 'throw' ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( v ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/scattered/docs/repl.txt b/lib/node_modules/@stdlib/array/base/scattered/docs/repl.txt new file mode 100644 index 000000000000..06be220cf66b --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/docs/repl.txt @@ -0,0 +1,45 @@ + +{{alias}}( len, indices, values, mode ) + Scatters a list of provided values to specified indices in a new zero-filled + "generic" array. + + The function supports broadcasting a `values` array containing a single + element against an `indices` array containing one or more elements. + + If `indices` is an empty array, the function returns a zero-filled array. + + Parameters + ---------- + len: integer + Output array length. + + indices: ArrayLikeObject + List of element indices. + + values: ArrayLikeObject + Values to scatter. When `indices` contains one or more elements, + `values` must be broadcast compatible with `indices` (i.e., must have + either one element or the same number of elements as `indices`). + + mode: string + Specifies how to handle an index outside the interval [0, max], where + `max` is the maximum possible array index. If equal to 'throw', the + function throws an error. If equal to 'normalize', the function throws + an error if provided an out-of-bounds normalized index. If equal to + 'wrap', the function wraps around an index using modulo arithmetic. If + equal to 'clamp', the function sets an index to either 0 (minimum index) + or the maximum index. + + Returns + ------- + out: Array + Output array. + + Examples + -------- + > var out = {{alias}}( 4, [ 1, 3 ], [ 20, 40 ], 'throw' ) + [ 0, 20, 0, 40 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/scattered/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/scattered/docs/types/index.d.ts new file mode 100644 index 000000000000..b52a2fe1ee00 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/docs/types/index.d.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; +import { Mode } from '@stdlib/types/ndarray'; + +/** +* Index array. +*/ +type IndexArray = Collection | AccessorArrayLike; + +/** +* Values array. +*/ +type ValuesArray = Collection | AccessorArrayLike; + +/** +* Scatters a list of provided values to specified indices in a new zero-filled "generic" array. +* +* @param len - output array length +* @param indices - list of element indices +* @param values - values to scatter +* @param mode - index mode +* @returns output array +* +* @example +* var indices = [ 1, 2 ]; +* var values = [ 20, 30 ]; +* +* var out = scattered( 4, indices, values, 'throw' ); +* // returns [ 0, 20, 30, 0 ] +* +* @example +* var out = scattered( 4, [ 1, 2 ], [ 30 ], 'throw' ); +* // returns [ 0, 30, 30, 0 ] +*/ +declare function scattered( len: number, indices: IndexArray, values: ValuesArray, mode: Mode ): Array; + + +// EXPORTS // + +export = scattered; diff --git a/lib/node_modules/@stdlib/array/base/scattered/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/scattered/docs/types/test.ts new file mode 100644 index 000000000000..c76ed7acd6ff --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/docs/types/test.ts @@ -0,0 +1,92 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import scattered = require( './index' ); + + +// TESTS // + +// The function returns an array... +{ + const z = new Complex128( 3.0, 4.0 ); + + scattered( 4, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectType number[] + scattered( 4, [ 1, 3 ], [ 20, 30 ], 'clamp' ); // $ExpectType number[] + scattered( 4, [ 1, 3 ], [ 20, 30 ], 'wrap' ); // $ExpectType number[] + scattered( 4, [ 1, 3 ], [ true, true ], 'normalize' ); // $ExpectType (number | boolean)[] + + scattered( 4, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectType number[] + scattered( 4, [ 1, 3 ], [ z, z ], 'throw' ); // $ExpectType (number | Complex128)[] + scattered( 4, [ 1, 3 ], [ z, z ], 'throw' ); // $ExpectType (number | Complex128)[] + scattered( 4, [ 1, 3 ], new AccessorArray( [ 20, 30 ] ), 'throw' ); // $ExpectType number[] +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + scattered( '1', [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scattered( true, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scattered( false, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scattered( null, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scattered( void 0, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scattered( [], [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError + scattered( {}, [ 1, 3 ], [ 20, 30 ], 'throw' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not an array-like object containing numbers... +{ + scattered( 4, 1, [ 20, 30 ], 'throw' ); // $ExpectError + scattered( 4, true, [ 20, 30 ], 'throw' ); // $ExpectError + scattered( 4, false, [ 20, 30 ], 'throw' ); // $ExpectError + scattered( 4, null, [ 20, 30 ], 'throw' ); // $ExpectError + scattered( 4, void 0, [ 20, 30 ], 'throw' ); // $ExpectError + scattered( 4, {}, [ 20, 30 ], 'throw' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not an array-like object... +{ + scattered( 4, [ 1, 3 ], 1, 'throw' ); // $ExpectError + scattered( 4, [ 1, 3 ], true, 'throw' ); // $ExpectError + scattered( 4, [ 1, 3 ], false, 'throw' ); // $ExpectError + scattered( 4, [ 1, 3 ], null, 'throw' ); // $ExpectError + scattered( 4, [ 1, 3 ], void 0, 'throw' ); // $ExpectError + scattered( 4, [ 1, 3 ], {}, 'throw' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a valid index mode... +{ + scattered( 4, [ 1, 3 ], [ 20, 30 ], '1' ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], 1 ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], true ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], false ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], null ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], void 0 ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], {} ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], [] ); // $ExpectError + scattered( 4, [ 1, 3 ], [ 20, 30 ], ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + scattered(); // $ExpectError + scattered( 4 ); // $ExpectError + scattered( 4, [] ); // $ExpectError + scattered( 4, [], [] ); // $ExpectError + scattered( 4, [], [], 'throw', {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/scattered/examples/index.js b/lib/node_modules/@stdlib/array/base/scattered/examples/index.js new file mode 100644 index 000000000000..d4da4a71accd --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var scattered = require( './../lib' ); + +// Generate an array of random indices: +var N = discreteUniform( 5, 15 ); +var indices = filledBy( N, discreteUniform.factory( 0, 10 ) ); +console.log( indices ); + +// Generate an array of random values: +var values = filledBy( N, discreteUniform.factory( 1000, 2025 ) ); +console.log( values ); + +// Scatter a random sample of elements to a new array: +var out = scattered( 11, indices, values, 'throw' ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/array/base/scattered/lib/index.js b/lib/node_modules/@stdlib/array/base/scattered/lib/index.js new file mode 100644 index 000000000000..b6578847298d --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Scatter a list of provided values to specified indices in a new zero-filled "generic" array. +* +* @module @stdlib/array/base/scattered +* +* @example +* var scattered = require( '@stdlib/array/base/scattered' ); +* +* var indices = [ 1, 2 ]; +* var values = [ 20, 30 ]; +* +* var out = scattered( 4, indices, values, 'throw' ); +* // returns [ 0, 20, 30, 0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/scattered/lib/main.js b/lib/node_modules/@stdlib/array/base/scattered/lib/main.js new file mode 100644 index 000000000000..ca0642bd0c0a --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/lib/main.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var zeros = require( '@stdlib/array/base/zeros' ); +var put = require( '@stdlib/array/base/put' ); + + +// MAIN // + +/** +* Scatters a list of provided values to specified indices in a new zero-filled "generic" array. +* +* @param {NonNegativeInteger} len - output array length +* @param {IntegerArray} indices - list of indices +* @param {Collection} values - values to scatter +* @param {string} mode - index mode +* @throws {Error} third argument must be broadcast compatible with the second argument +* @returns {Array} output array +* +* @example +* var indices = [ 1, 2 ]; +* var values = [ 20, 30 ]; +* +* var out = scattered( 4, indices, values, 'throw' ); +* // returns [ 0, 20, 30, 0 ] +* +* @example +* var indices = [ 1, 2 ]; +* var values = [ 30 ]; +* +* var out = scattered( 4, indices, values, 'throw' ); +* // returns [ 0, 30, 30, 0 ] +*/ +function scattered( len, indices, values, mode ) { + return put( zeros( len ), indices, values, mode ); +} + + +// EXPORTS // + +module.exports = scattered; diff --git a/lib/node_modules/@stdlib/array/base/scattered/package.json b/lib/node_modules/@stdlib/array/base/scattered/package.json new file mode 100644 index 000000000000..098221dca365 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/package.json @@ -0,0 +1,62 @@ +{ + "name": "@stdlib/array/base/scattered", + "version": "0.0.0", + "description": "Scatter a list of provided values to specified indices in a new zero-filled \"generic\" array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "utilities", + "utils", + "generic", + "array", + "set", + "scatter", + "filled", + "fill" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/scattered/test/test.js b/lib/node_modules/@stdlib/array/base/scattered/test/test.js new file mode 100644 index 000000000000..b9a27d3b397a --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/scattered/test/test.js @@ -0,0 +1,203 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isArray = require( '@stdlib/assert/is-array' ); +var scattered = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof scattered, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a third argument which is not broadcast compatible with the second argument', function test( t ) { + var values; + var i; + + values = [ + [], + [ 1, 2, 3 ], + [ 1, 2, 3, 4 ], + [ 1, 2, 3, 4, 5 ] + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided an array of length ' + values[ i ].length ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + scattered( 4, [ 1, 2 ], value, 'throw' ); + }; + } +}); + +tape( 'the function scatters elements to a new array', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ 1, 3 ]; + actual = scattered( 4, indices, [ 20, 40 ], 'throw' ); + expected = [ 0, 20, 0, 40 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 3, 3 ]; + actual = scattered( 4, indices, [ 20, 30, 40, 50 ], 'throw' ); + expected = [ 0, 30, 0, 50 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 3, 2, 1, 0 ]; + actual = scattered( 4, indices, [ 20, 30, 40, 50 ], 'throw' ); + expected = [ 50, 40, 30, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + actual = scattered( 4, indices, [ 100, 100, 100, 100, 100, 100, 100, 100, 100, 100 ], 'throw' ); + expected = [ 0, 100, 0, 0 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function scatters elements to a new array (broadcasting)', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ 1, 3 ]; + actual = scattered( 4, indices, [ 20 ], 'throw' ); + expected = [ 0, 20, 0, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 3, 3 ]; + actual = scattered( 4, indices, [ 20 ], 'throw' ); + expected = [ 0, 20, 0, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 3, 2, 1, 0 ]; + actual = scattered( 4, indices, [ 20 ], 'throw' ); + expected = [ 20, 20, 20, 20 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + actual = scattered( 4, indices, [ 100 ], 'throw' ); + expected = [ 0, 100, 0, 0 ]; + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a zero-filled array if provided a second argument which is empty', function test( t ) { + var actual; + + actual = scattered( 4, [], [ 5, 6, 7, 8 ], 'throw' ); + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, [ 0, 0, 0, 0 ], 'returns expected value' ); + + t.end(); +}); + +tape( 'when the "mode" is "throw", the function throws an error if provided an out-of-bounds index', function test( t ) { + var indices; + + indices = [ 4, 5, 1, 2 ]; + + t.throws( badValue, RangeError, 'throws an error' ); + t.end(); + + function badValue() { + scattered( 4, indices, [ 200 ], 'throw' ); + } +}); + +tape( 'when the "mode" is "normalize", the function normalizes negative indices', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ -1, -2, -3, -4 ]; + actual = scattered( 4, indices, [ 5, 6, 7, 8 ], 'normalize' ); + expected = [ 8, 7, 6, 5 ]; + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'when the "mode" is "normalize", the function throws an error if provided an out-of-bounds index', function test( t ) { + var indices; + + indices = [ 2, 50, 1, 2 ]; + + t.throws( badValue, RangeError, 'throws an error' ); + t.end(); + + function badValue() { + scattered( 4, indices, [ 100 ], 'normalize' ); + } +}); + +tape( 'when the "mode" is "clamp", the function clamps out-of-bounds indices', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ -10, 10, -5, 5 ]; + actual = scattered( 4, indices, [ 100, 200, 300, 400 ], 'clamp' ); + expected = [ 300, 0, 0, 400 ]; + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'when the "mode" is "wrap", the function wraps out-of-bounds indices', function test( t ) { + var expected; + var indices; + var actual; + + indices = [ -10, 10, -5, 5 ]; + actual = scattered( 4, indices, [ 100, 200, 300, 400 ], 'wrap' ); + expected = [ 0, 400, 200, 300 ]; + + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/slice/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/slice/docs/types/index.d.ts index 16a1075f880c..748041306db3 100644 --- a/lib/node_modules/@stdlib/array/base/slice/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/base/slice/docs/types/index.d.ts @@ -20,7 +20,7 @@ /// -import { Collection, TypedArray, ComplexTypedArray } from '@stdlib/types/array'; +import { Collection, TypedArray, ComplexTypedArray, BooleanTypedArray } from '@stdlib/types/array'; /** * Returns a shallow copy of a portion of an array. @@ -46,7 +46,7 @@ import { Collection, TypedArray, ComplexTypedArray } from '@stdlib/types/array'; * var out = slice( x, 0, 3 ); * // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] */ -declare function slice( x: T, start: number, end: number ): T; +declare function slice( x: T, start: number, end: number ): T; /** * Returns a shallow copy of a portion of an array. diff --git a/lib/node_modules/@stdlib/array/base/slice/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/slice/docs/types/test.ts index 9ddfc3d1ee0e..af3213bed67a 100644 --- a/lib/node_modules/@stdlib/array/base/slice/docs/types/test.ts +++ b/lib/node_modules/@stdlib/array/base/slice/docs/types/test.ts @@ -18,6 +18,7 @@ import Complex128Array = require( '@stdlib/array/complex128' ); import Complex64Array = require( '@stdlib/array/complex64' ); +import BooleanArray = require( '@stdlib/array/bool' ); import slice = require( './index' ); @@ -37,6 +38,7 @@ import slice = require( './index' ); slice( new Uint8ClampedArray( [ 1, 2, 3 ] ), 0, 3 ); // $ExpectType Uint8ClampedArray slice( new Complex128Array( [ 1, 2, 3, 4, 5, 6 ] ), 0, 3 ); // $ExpectType Complex128Array slice( new Complex64Array( [ 1, 2, 3, 4, 5, 6 ] ), 0, 3 ); // $ExpectType Complex64Array + slice( new BooleanArray( [ true, false, true, false ] ), 0, 3 ); // $ExpectType BooleanArray } // The compiler throws an error if the function is provided a first argument which is not a collection... diff --git a/lib/node_modules/@stdlib/array/base/take-indexed/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/take-indexed/docs/types/index.d.ts index 9c642c062a13..c8a47d8ac579 100644 --- a/lib/node_modules/@stdlib/array/base/take-indexed/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/base/take-indexed/docs/types/index.d.ts @@ -23,7 +23,7 @@ import { Collection } from '@stdlib/types/array'; /** -* Takes element from an indexed array. +* Takes elements from an indexed array. * * ## Notes * diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/README.md b/lib/node_modules/@stdlib/array/base/take-indexed2/README.md new file mode 100644 index 000000000000..2b1592521f2f --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/README.md @@ -0,0 +1,117 @@ + + +# takeIndexed2 + +> Take elements from two indexed arrays in a single pass. + +
+ +## Usage + +```javascript +var takeIndexed2 = require( '@stdlib/array/base/take-indexed2' ); +``` + +#### takeIndexed2( x, y, indices ) + +Takes elements from two indexed arrays in a single pass. + +```javascript +var x = [ 1, 2, 3, 4 ]; +var y = [ 5, 6, 7, 8 ]; + +var out = takeIndexed2( x, y, [ 1, 3 ] ); +// returns [ [ 2, 4 ], [ 6, 8 ] ] +``` + +If `indices` is an empty array, the function returns empty arrays. + +```javascript +var x = [ 1, 2, 3, 4 ]; +var y = [ 5, 6, 7, 8 ]; + +var out = takeIndexed2( x, y, [] ); +// returns [ [], [] ] +``` + +
+ + + +
+ +## Notes + +- The function does **not** perform bounds checking. If an index is less than zero or greater than the maximum index of `x` or `y`, the value of the corresponding element in the respective output array is undefined. +- An _indexed_ array-like object is a data structure in which one retrieves elements via integer indices using bracket `[]` notation (e.g., `Float64Array`, `Int32Array`, `Array`, etc). This is in contrast to an _accessor_ array-like object in which one retrieves elements using `get` and `set` methods (e.g., `Complex64Array` and `Complex128Array`). + +
+ + + +
+ +## Examples + + + +```javascript +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var linspace = require( '@stdlib/array/base/linspace' ); +var takeIndexed2 = require( '@stdlib/array/base/take-indexed2' ); + +// Generate linearly spaced arrays: +var x = linspace( 0, 100, 11 ); +console.log( x ); + +var y = linspace( 100, 200, 11 ); +console.log( y ); + +// Generate an array of random indices: +var N = discreteUniform( 5, 15 ); +var indices = filledBy( N, discreteUniform.factory( 0, x.length-1 ) ); +console.log( indices ); + +// Take a random sample of elements from `x` and `y`: +var out = takeIndexed2( x, y, indices ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/base/take-indexed2/benchmark/benchmark.js new file mode 100644 index 000000000000..6866e9e3e1e4 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var zeroTo = require( '@stdlib/array/base/zero-to' ); +var pkg = require( './../package.json' ).name; +var take2 = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::copy:len=100', function benchmark( b ) { + var x; + var i; + var v; + + x = zeroTo( 100 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = take2( x, x, x ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArrayArray( v ) ) { + b.fail( 'should return an array of arrays' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/benchmark/benchmark.length.js b/lib/node_modules/@stdlib/array/base/take-indexed2/benchmark/benchmark.length.js new file mode 100644 index 000000000000..beb89cd16b0e --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/benchmark/benchmark.length.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; +var isArrayArray = require( '@stdlib/assert/is-array-array' ); +var pkg = require( './../package.json' ).name; +var take2 = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var idx = filledBy( len, discreteUniform( 0, 3 ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var x; + var v; + var i; + + x = [ 1, 2, 3, 4 ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = take2( x, x, idx ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArrayArray( v ) ) { + b.fail( 'should return an array of arrays' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/docs/repl.txt b/lib/node_modules/@stdlib/array/base/take-indexed2/docs/repl.txt new file mode 100644 index 000000000000..540c0f4a4f3e --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}( x, y, indices ) + Takes elements from two indexed arrays in a single pass. + + If `indices` is an empty array, the function returns empty arrays. + + The function does *not* perform bounds checking. If an index is less than + zero or greater than the maximum index of `x` or `y`, the value of the + corresponding element in the respective output array is undefined. + + Parameters + ---------- + x: ArrayLikeObject + First input array. + + y: ArrayLikeObject + Second input array. + + indices: ArrayLikeObject + List of element indices. + + Returns + ------- + out: Array + Output arrays. + + Examples + -------- + > var x = [ 1, 2, 3, 4 ]; + > var y = [ 5, 6, 7, 8 ]; + > var out = {{alias}}( x, y, [ 1, 3 ] ) + [ [ 2, 4 ], [ 6, 8 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/base/take-indexed2/docs/types/index.d.ts new file mode 100644 index 000000000000..b25eeeecac70 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/docs/types/index.d.ts @@ -0,0 +1,50 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Takes elements from two indexed arrays in a single pass. +* +* ## Notes +* +* - The function does **not** perform bounds checking. If an index is less than zero or greater than the maximum index of `x` or `y`, the value of the corresponding element in the respective output array is undefined. +* +* @param x - first input array +* @param y - second input array +* @param indices - list of element indices +* @returns output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var indices = [ 3, 1, 2, 0 ]; +* +* var out = take2( x, y, indices ); +* // returns [ [ 4, 2, 3, 1 ], [ 8, 6, 7, 5 ] ] +*/ +declare function take2( x: Collection, y: Collection, indices: Collection ): [ Array, Array ]; + + +// EXPORTS // + +export = take2; diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/docs/types/test.ts b/lib/node_modules/@stdlib/array/base/take-indexed2/docs/types/test.ts new file mode 100644 index 000000000000..7e41a191bc6e --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/docs/types/test.ts @@ -0,0 +1,68 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import take2 = require( './index' ); + + +// TESTS // + +// The function returns an array of arrays... +{ + take2( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectType [number[], number[]] + take2( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectType [any[], any[]] + take2( [ 1, 2, 3, 4 ], [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectType [number[], number[]] + take2( [ '1', '2', '3', '4' ], [ '1', '2', '3', '4' ], [ 1, 3 ] ); // $ExpectType [string[], string[]] +} + +// The compiler throws an error if the function is provided a first argument which is not an array-like object... +{ + take2( 1, [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectError + take2( true, [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectError + take2( false, [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectError + take2( null, [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectError + take2( void 0, [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectError + take2( {}, [ 1, 2, 3, 4 ], [ 1, 3 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not an array-like object... +{ + take2( [ 1, 2, 3, 4 ], 1, [ 1, 3 ] ); // $ExpectError + take2( [ 1, 2, 3, 4 ], true, [ 1, 3 ] ); // $ExpectError + take2( [ 1, 2, 3, 4 ], false, [ 1, 3 ] ); // $ExpectError + take2( [ 1, 2, 3, 4 ], null, [ 1, 3 ] ); // $ExpectError + take2( [ 1, 2, 3, 4 ], void 0, [ 1, 3 ] ); // $ExpectError + take2( [ 1, 2, 3, 4 ], {}, [ 1, 3 ] ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not an array-like object containing numbers... +{ + take2( [], [], 1 ); // $ExpectError + take2( [], [], true ); // $ExpectError + take2( [], [], false ); // $ExpectError + take2( [], [], null ); // $ExpectError + take2( [], [], void 0 ); // $ExpectError + take2( [], [], {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + take2(); // $ExpectError + take2( [] ); // $ExpectError + take2( [], [] ); // $ExpectError + take2( [], [], [], [] ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/examples/index.js b/lib/node_modules/@stdlib/array/base/take-indexed2/examples/index.js new file mode 100644 index 000000000000..0807682421ce --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var filledBy = require( '@stdlib/array/base/filled-by' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var linspace = require( '@stdlib/array/base/linspace' ); +var take2 = require( './../lib' ); + +// Generate linearly spaced arrays: +var x = linspace( 0, 100, 11 ); +console.log( x ); + +var y = linspace( 100, 200, 11 ); +console.log( y ); + +// Generate an array of random indices: +var N = discreteUniform( 5, 15 ); +var indices = filledBy( N, discreteUniform.factory( 0, x.length-1 ) ); +console.log( indices ); + +// Take a random sample of elements from `x` and `y`: +var out = take2( x, y, indices ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/lib/index.js b/lib/node_modules/@stdlib/array/base/take-indexed2/lib/index.js new file mode 100644 index 000000000000..4abb5e96c737 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Take elements from two indexed arrays in a single pass. +* +* @module @stdlib/array/base/take-indexed2 +* +* @example +* var take2 = require( '@stdlib/array/base/take-indexed2' ); +* +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var indices = [ 3, 1, 2, 0 ]; +* +* var out = take2( x, y, indices ); +* // returns [ [ 4, 2, 3, 1 ], [ 8, 6, 7, 5 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/lib/main.js b/lib/node_modules/@stdlib/array/base/take-indexed2/lib/main.js new file mode 100644 index 000000000000..5fb5b2121ec1 --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Takes elements from two indexed arrays in a single pass. +* +* @param {Collection} x - first input array +* @param {Collection} y - second input array +* @param {NonNegativeIntegerArray} indices - list of indices +* @returns {Array} output arrays +* +* @example +* var x = [ 1, 2, 3, 4 ]; +* var y = [ 5, 6, 7, 8 ]; +* var indices = [ 3, 1, 2, 0 ]; +* +* var out = take2( x, y, indices ); +* // returns [ [ 4, 2, 3, 1 ], [ 8, 6, 7, 5 ] ] +*/ +function take2( x, y, indices ) { + var o1; + var o2; + var i; + + o1 = []; + o2 = []; + for ( i = 0; i < indices.length; i++ ) { + o1.push( x[ indices[ i ] ] ); // use `Array#push` to ensure "fast" elements + o2.push( y[ indices[ i ] ] ); + } + return [ o1, o2 ]; +} + + +// EXPORTS // + +module.exports = take2; diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/package.json b/lib/node_modules/@stdlib/array/base/take-indexed2/package.json new file mode 100644 index 000000000000..1cd89957047f --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/package.json @@ -0,0 +1,62 @@ +{ + "name": "@stdlib/array/base/take-indexed2", + "version": "0.0.0", + "description": "Take elements from two indexed arrays in a single pass.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "utilities", + "utils", + "generic", + "array", + "take", + "extract", + "copy", + "index" + ] +} diff --git a/lib/node_modules/@stdlib/array/base/take-indexed2/test/test.js b/lib/node_modules/@stdlib/array/base/take-indexed2/test/test.js new file mode 100644 index 000000000000..6502bb07f36a --- /dev/null +++ b/lib/node_modules/@stdlib/array/base/take-indexed2/test/test.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var take2 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof take2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function takes elements from two arrays', function test( t ) { + var expected; + var indices; + var actual; + var x; + var y; + + x = [ 1, 2, 3, 4 ]; + y = [ 5, 6, 7, 8 ]; + + indices = [ 1, 3 ]; + actual = take2( x, y, indices ); + expected = [ + [ 2, 4 ], + [ 6, 8 ] + ]; + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 3, 3 ]; + actual = take2( x, y, indices ); + expected = [ + [ 2, 2, 4, 4 ], + [ 6, 6, 8, 8 ] + ]; + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 3, 2, 1, 0 ]; + actual = take2( x, y, indices ); + expected = [ + [ 4, 3, 2, 1 ], + [ 8, 7, 6, 5 ] + ]; + t.deepEqual( actual, expected, 'returns expected value' ); + + indices = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + actual = take2( x, y, indices ); + expected = [ + [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], + [ 6, 6, 6, 6, 6, 6, 6, 6, 6, 6 ] + ]; + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function does not perform bounds checking', function test( t ) { + var expected; + var indices; + var actual; + var x; + var y; + + x = [ 1, 2, 3, 4 ]; + y = [ 5, 6, 7, 8 ]; + + indices = [ 4, 5, 1, 2 ]; + actual = take2( x, y, indices ); + expected = [ + [ void 0, void 0, 2, 3 ], + [ void 0, void 0, 6, 7 ] + ]; + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns empty arrays if provided a third argument which is empty', function test( t ) { + var x = [ 1, 2, 3, 4 ]; + t.deepEqual( take2( x, x, [] ), [ [], [] ], 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/array/base/zeros3d/README.md b/lib/node_modules/@stdlib/array/base/zeros3d/README.md index c82e7c1ac869..b7b30ddee9fd 100644 --- a/lib/node_modules/@stdlib/array/base/zeros3d/README.md +++ b/lib/node_modules/@stdlib/array/base/zeros3d/README.md @@ -95,6 +95,17 @@ out = zeros3d( [ 1, 3, 1 ] );
+* * * + +## See Also + +- [`@stdlib/array/base/zeros`][@stdlib/array/base/zeros]: create a zero-filled generic array. +- [`@stdlib/array/base/ones3d`][@stdlib/array/base/ones3d]: create a three-dimensional nested array filled with ones. +- [`@stdlib/array/base/zeros2d`][@stdlib/array/base/zeros2d]: create a zero-filled two-dimensional nested array. +- [`@stdlib/array/base/zeros4d`][@stdlib/array/base/zeros4d]: create a zero-filled four-dimensional nested array. +- [`@stdlib/array/base/zeros5d`][@stdlib/array/base/zeros5d]: create a zero-filled five-dimensional nested array. +- [`@stdlib/array/base/zerosnd`][@stdlib/array/base/zerosnd]: create a zero-filled n-dimensional nested array. +
@@ -103,6 +114,22 @@ out = zeros3d( [ 1, 3, 1 ] );
+ + +[@stdlib/array/base/zeros]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros + +[@stdlib/array/base/ones3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones3d + +[@stdlib/array/base/zeros2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros2d + +[@stdlib/array/base/zeros4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros4d + +[@stdlib/array/base/zeros5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros5d + +[@stdlib/array/base/zerosnd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zerosnd + + +
diff --git a/lib/node_modules/@stdlib/array/fixed-endian-float32/README.md b/lib/node_modules/@stdlib/array/fixed-endian-float32/README.md index e5218ccebff8..65469eb4528d 100644 --- a/lib/node_modules/@stdlib/array/fixed-endian-float32/README.md +++ b/lib/node_modules/@stdlib/array/fixed-endian-float32/README.md @@ -422,6 +422,13 @@ logEach( '%s', out );
+* * * + +## See Also + +- [`@stdlib/array/fixed-endian-float64`][@stdlib/array/fixed-endian-float64]: Float64Array having a specified byte order. +- [`@stdlib/array/float32`][@stdlib/array/float32]: Float32Array. +
@@ -438,6 +445,12 @@ logEach( '%s', out ); [@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + + +[@stdlib/array/fixed-endian-float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/fixed-endian-float64 + + + diff --git a/lib/node_modules/@stdlib/array/float32/README.md b/lib/node_modules/@stdlib/array/float32/README.md index e48de663268f..3f4796534797 100644 --- a/lib/node_modules/@stdlib/array/float32/README.md +++ b/lib/node_modules/@stdlib/array/float32/README.md @@ -233,8 +233,8 @@ var arr = Float32Array.from( [ 1.0, 2.0 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -371,9 +371,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -490,9 +490,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -552,9 +552,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -615,9 +615,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -670,9 +670,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -893,9 +893,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -957,10 +957,10 @@ var v = arr.reduce( fcn, 0.0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1000,10 +1000,10 @@ var v = arr.reduce( fcn, 0.0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1176,9 +1176,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/float64/README.md b/lib/node_modules/@stdlib/array/float64/README.md index 9e2abee7bc66..ee04993e6922 100644 --- a/lib/node_modules/@stdlib/array/float64/README.md +++ b/lib/node_modules/@stdlib/array/float64/README.md @@ -229,8 +229,8 @@ var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -885,9 +885,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -949,10 +949,10 @@ var v = arr.reduce( fcn, 0.0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -992,10 +992,10 @@ var v = arr.reduce( fcn, 0.0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1168,9 +1168,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/int16/README.md b/lib/node_modules/@stdlib/array/int16/README.md index 1a577098baee..3a165efea386 100644 --- a/lib/node_modules/@stdlib/array/int16/README.md +++ b/lib/node_modules/@stdlib/array/int16/README.md @@ -229,8 +229,8 @@ var arr = Int16Array.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/int32/README.md b/lib/node_modules/@stdlib/array/int32/README.md index c9215ea7a37e..45def2674ec2 100644 --- a/lib/node_modules/@stdlib/array/int32/README.md +++ b/lib/node_modules/@stdlib/array/int32/README.md @@ -229,8 +229,8 @@ var arr = Int32Array.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/int8/README.md b/lib/node_modules/@stdlib/array/int8/README.md index 545894ac08e9..50288ee35f70 100644 --- a/lib/node_modules/@stdlib/array/int8/README.md +++ b/lib/node_modules/@stdlib/array/int8/README.md @@ -229,8 +229,8 @@ var arr = Int8Array.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/to-fancy/README.md b/lib/node_modules/@stdlib/array/to-fancy/README.md index abb3b16e8c24..e78a9971b8ee 100644 --- a/lib/node_modules/@stdlib/array/to-fancy/README.md +++ b/lib/node_modules/@stdlib/array/to-fancy/README.md @@ -37,7 +37,7 @@ var x = [ 1, 2, 3, 4, 5, 6, 7, 8 ]; // Turn the plain array into a "fancy" array: var y = array2fancy( x ); -// Select the first 3 elements: +// Select the first three elements: var v = y[ ':3' ]; // returns [ 1, 2, 3 ] @@ -45,7 +45,7 @@ var v = y[ ':3' ]; v = y[ '1::2' ]; // returns [ 2, 4, 6, 8 ] -// Select every other element, in reverse order, starting with the least element: +// Select every other element, in reverse order, starting with the last element: v = y[ '::-2' ]; // returns [ 8, 6, 4, 2 ] diff --git a/lib/node_modules/@stdlib/array/uint16/README.md b/lib/node_modules/@stdlib/array/uint16/README.md index f1962df57fd5..159606fe33ff 100644 --- a/lib/node_modules/@stdlib/array/uint16/README.md +++ b/lib/node_modules/@stdlib/array/uint16/README.md @@ -229,8 +229,8 @@ var arr = Uint16Array.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/uint32/README.md b/lib/node_modules/@stdlib/array/uint32/README.md index c081d0e2ff33..da419b7ac2d8 100644 --- a/lib/node_modules/@stdlib/array/uint32/README.md +++ b/lib/node_modules/@stdlib/array/uint32/README.md @@ -229,8 +229,8 @@ var arr = Uint32Array.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index.. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/uint8/README.md b/lib/node_modules/@stdlib/array/uint8/README.md index 53b5170784f6..7adbddf55bce 100644 --- a/lib/node_modules/@stdlib/array/uint8/README.md +++ b/lib/node_modules/@stdlib/array/uint8/README.md @@ -229,8 +229,8 @@ var arr = Uint8Array.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/array/uint8c/README.md b/lib/node_modules/@stdlib/array/uint8c/README.md index aa4caf80a488..de33ece9549b 100644 --- a/lib/node_modules/@stdlib/array/uint8c/README.md +++ b/lib/node_modules/@stdlib/array/uint8c/README.md @@ -229,8 +229,8 @@ var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn ); A callback function is provided two arguments: -- `value`: source value -- `index`: source index +- `value`: source value. +- `index`: source index. To set the callback execution context, provide a `thisArg`. @@ -363,9 +363,9 @@ var bool = arr.every( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -482,9 +482,9 @@ var arr2 = arr1.filter( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -544,9 +544,9 @@ var v = arr.find( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -607,9 +607,9 @@ var idx = arr.findIndex( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -662,9 +662,9 @@ console.log( str ); The callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -879,9 +879,9 @@ var arr2 = arr1.map( fcn ); A callback is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -943,10 +943,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -986,10 +986,10 @@ var v = arr.reduce( fcn, 0 ); A callback is provided four arguments: -- `acc`: accumulated result -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `acc`: accumulated result. +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. @@ -1162,9 +1162,9 @@ var bool = arr.some( predicate ); A `predicate` function is provided three arguments: -- `value`: array element -- `index`: array index -- `arr`: array on which the method is invoked +- `value`: array element. +- `index`: array index. +- `arr`: array on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/assert/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/docs/types/index.d.ts index cc62ce665707..f33d9927759e 100644 --- a/lib/node_modules/@stdlib/assert/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/assert/docs/types/index.d.ts @@ -2643,7 +2643,7 @@ interface Namespace { * * - The function validates that a value is a string. For all other types, the function returns `false`. * - * - A duration string is a string containing a sequence of time units. A time unit is a non-negative integer followed by a unit identifier. The following unit identifiers are supported: + * - A duration string is a string containing a sequence of time units. A time unit is a nonnegative integer followed by a unit identifier. The following unit identifiers are supported: * * - `d`: days * - `h`: hours diff --git a/lib/node_modules/@stdlib/assert/is-duration-string/README.md b/lib/node_modules/@stdlib/assert/is-duration-string/README.md index 91228b698dbb..ef825221f69a 100644 --- a/lib/node_modules/@stdlib/assert/is-duration-string/README.md +++ b/lib/node_modules/@stdlib/assert/is-duration-string/README.md @@ -52,7 +52,7 @@ bool = isDurationString( '1d2h' ); - The function validates that a `value` is a `string`. For all other types, the function returns `false`. -- A duration string is a string containing a sequence of time units. A time unit is a non-negative integer followed by a unit identifier. The following unit identifiers are supported: +- A duration string is a string containing a sequence of time units. A time unit is a nonnegative integer followed by a unit identifier. The following unit identifiers are supported: - `d`: days - `h`: hours diff --git a/lib/node_modules/@stdlib/assert/is-duration-string/docs/repl.txt b/lib/node_modules/@stdlib/assert/is-duration-string/docs/repl.txt index 56266b319ca3..6ad4b1bedc48 100644 --- a/lib/node_modules/@stdlib/assert/is-duration-string/docs/repl.txt +++ b/lib/node_modules/@stdlib/assert/is-duration-string/docs/repl.txt @@ -6,7 +6,7 @@ function returns `false`. A duration string is a string containing a sequence of time units. A time - unit is a non-negative integer followed by a unit identifier. The following + unit is a nonnegative integer followed by a unit identifier. The following unit identifiers are supported: - d: days. diff --git a/lib/node_modules/@stdlib/assert/is-duration-string/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-duration-string/docs/types/index.d.ts index 0ac9bd4149b1..fc8b61e61b64 100644 --- a/lib/node_modules/@stdlib/assert/is-duration-string/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/assert/is-duration-string/docs/types/index.d.ts @@ -25,7 +25,7 @@ * * - The function validates that a value is a string. For all other types, the function returns `false`. * -* - A duration string is a string containing a sequence of time units. A time unit is a non-negative integer followed by a unit identifier. The following unit identifiers are supported: +* - A duration string is a string containing a sequence of time units. A time unit is a nonnegative integer followed by a unit identifier. The following unit identifiers are supported: * * - `d`: days * - `h`: hours diff --git a/lib/node_modules/@stdlib/assert/is-duration-string/lib/main.js b/lib/node_modules/@stdlib/assert/is-duration-string/lib/main.js index b8627af0ce11..2d03f81f908a 100644 --- a/lib/node_modules/@stdlib/assert/is-duration-string/lib/main.js +++ b/lib/node_modules/@stdlib/assert/is-duration-string/lib/main.js @@ -37,7 +37,7 @@ var RE_DURATION_STRING = /^(?:\d+d)?(?:\d+h)?(?:\d+m)?(?:\d+s)?(?:\d+ms)?$/i; * * - The function validates that a value is a string. For all other types, the function returns `false`. * -* - A duration string is a string containing a sequence of time units. A time unit is a non-negative integer followed by a unit identifier. The following unit identifiers are supported: +* - A duration string is a string containing a sequence of time units. A time unit is a nonnegative integer followed by a unit identifier. The following unit identifiers are supported: * * - `d`: days * - `h`: hours diff --git a/lib/node_modules/@stdlib/assert/is-pascalcase/README.md b/lib/node_modules/@stdlib/assert/is-pascalcase/README.md index 1cdab12cd475..2c816747b526 100644 --- a/lib/node_modules/@stdlib/assert/is-pascalcase/README.md +++ b/lib/node_modules/@stdlib/assert/is-pascalcase/README.md @@ -166,6 +166,12 @@ true
+* * * + +## See Also + +- [`@stdlib/assert/is-string`][@stdlib/assert/is-string]: test if a value is a string. +
@@ -180,6 +186,8 @@ true +[@stdlib/assert/is-string]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-string + diff --git a/lib/node_modules/@stdlib/assert/is-property-key/test/test.js b/lib/node_modules/@stdlib/assert/is-property-key/test/test.js index 603e15a5879d..172e80697f74 100644 --- a/lib/node_modules/@stdlib/assert/is-property-key/test/test.js +++ b/lib/node_modules/@stdlib/assert/is-property-key/test/test.js @@ -54,14 +54,14 @@ tape( 'the function returns `true` if provided a symbol primitive', opts, functi t.end(); }); -tape( 'the function returns `true` if provided a non-negative integer primitive', function test( t ) { +tape( 'the function returns `true` if provided a nonnegative integer primitive', function test( t ) { t.strictEqual( isPropertyKey( 0 ), true, 'returns true' ); t.strictEqual( isPropertyKey( 1 ), true, 'returns true' ); t.strictEqual( isPropertyKey( 139 ), true, 'returns true' ); t.end(); }); -tape( 'the function returns `false` if not provided a string, symbol, or non-negative integer primitive', function test( t ) { +tape( 'the function returns `false` if not provided a string, symbol, or nonnegative integer primitive', function test( t ) { var values; var i; @@ -77,7 +77,7 @@ tape( 'the function returns `false` if not provided a string, symbol, or non-neg [], function noop() {}, new String( 'beep' ), // eslint-disable-line no-new-wrappers - new Number( 1 ) // eslint-disable-line no-new-wrappers + new Number( 1 ) ]; for ( i = 0; i < values.length; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/base/cscal/README.md b/lib/node_modules/@stdlib/blas/base/cscal/README.md index 5ff72d193ef5..262c37244d5e 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/README.md +++ b/lib/node_modules/@stdlib/blas/base/cscal/README.md @@ -37,28 +37,18 @@ Scales values from `cx` by `ca`. ```javascript var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); -var realf = require( '@stdlib/complex/float32/real' ); -var imagf = require( '@stdlib/complex/float32/imag' ); var cx = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); var ca = new Complex64( 2.0, 0.0 ); cscal( 3, ca, cx, 1 ); - -var z = cx.get( 0 ); -// returns - -var re = realf( z ); -// returns 2.0 - -var im = imagf( z ); -// returns 2.0 +// cx => [ 2.0, 2.0, 2.0, 1.0, 1.0, 1.0 ] ``` The function has the following parameters: - **N**: number of indexed elements. -- **ca**: scalar [`Complex64`][@stdlib/complex/float32/ctor] constant. +- **ca**: scalar [`Complex64`][@stdlib/complex/float32/ctor] constant. - **cx**: input [`Complex64Array`][@stdlib/array/complex64]. - **strideX**: index increment for `cx`. @@ -67,22 +57,12 @@ The `N` and stride parameters determine how values from `cx` are scaled by `ca`. ```javascript var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); -var realf = require( '@stdlib/complex/float32/real' ); -var imagf = require( '@stdlib/complex/float32/imag' ); var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); var ca = new Complex64( 2.0, 0.0 ); cscal( 2, ca, cx, 2 ); - -var z = cx.get( 2 ); -// returns - -var re = realf( z ); -// returns 10.0 - -var im = imagf( z ); -// returns 12.0 +// cx => [ 1.0, 2.0, 10.0, 12.0, 5.0, 6.0, 14.0, 16.0 ] ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. @@ -92,8 +72,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); -var realf = require( '@stdlib/complex/float32/real' ); -var imagf = require( '@stdlib/complex/float32/imag' ); // Initial array: var cx0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); @@ -106,15 +84,7 @@ var cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // start at // Scales every other value from `cx1` by `ca`... cscal( 3, ca, cx1, 1 ); - -var z = cx0.get( 1 ); -// returns - -var re = realf( z ); -// returns -2.0 - -var im = imagf( z ); -// returns 14.0 +// cx = [ -2.0, 14.0, -2.0, 22.0, -2.0, 30.0, 5.0, 6.0 ] ``` #### cscal.ndarray( N, ca, cx, strideX, offsetX ) @@ -124,22 +94,12 @@ Scales values from `cx` by `ca` using alternative indexing semantics. ```javascript var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); -var realf = require( '@stdlib/complex/float32/real' ); -var imagf = require( '@stdlib/complex/float32/imag' ); var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var ca = new Complex64( 2.0, 2.0 ); cscal.ndarray( 3, ca, cx, 1, 0 ); - -var z = cx.get( 0 ); -// returns - -var re = realf( z ); -// returns -2.0 - -var im = imagf( z ); -// returns 6.0 +// cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 26.0 ] ``` The function has the following additional parameters: @@ -151,22 +111,12 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Complex64Array = require( '@stdlib/array/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); -var realf = require( '@stdlib/complex/float32/real' ); -var imagf = require( '@stdlib/complex/float32/imag' ); var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); var ca = new Complex64( 2.0, 2.0 ); cscal.ndarray( 2, ca, cx, 2, 1 ); - -var z = cx.get( 3 ); -// returns - -var re = realf( z ); -// returns -2.0 - -var im = imagf( z ); -// returns 30.0 +// cx => [ 1.0, 2.0, -2.0, 30.0, 5.0, 6.0, -6.0, 58.0 ] ``` diff --git a/lib/node_modules/@stdlib/blas/base/cscal/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/cscal/docs/repl.txt index 894daacaf6c1..3cc4daff11dc 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/base/cscal/docs/repl.txt @@ -37,32 +37,20 @@ > var cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var ca = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 2.0 ); > {{alias}}( 2, ca, cx, 1 ); - > var z = cx.get( 0 ); - > var re = {{alias:@stdlib/complex/float32/real}}( z ) - -3.0 - > var im = {{alias:@stdlib/complex/float32/imag}}( z ) - 4.0 + [ 2.0, 2.0, 2.0, 1.0 ] // Advanced indexing: > cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); > ca = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 1.0 ); > {{alias}}( 2, ca, cx, 2 ); - > z = cx.get( 0 ); - > re = {{alias:@stdlib/complex/float32/real}}( z ) - -1.0 - > im = {{alias:@stdlib/complex/float32/imag}}( z ) - 3.0 + [ 1.0, 2.0, 10.0, 12.0, 5.0, 6.0 ] // Using typed array views: > var cx0 = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); > var cx1 = new {{alias:@stdlib/array/complex64}}( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); > var ca = new {{alias:@stdlib/complex/float32/ctor}}( 2.0, 2.0 ); > {{alias}}( 2, ca, cx1, 1 ); - > z = cx0.get( 1 ); - > re = {{alias:@stdlib/complex/float32/real}}( z ) - -2.0 - > im = {{alias:@stdlib/complex/float32/imag}}( z ) - 14.0 + [ -2.0, 14.0, -2.0, 22.0, -2.0, 30.0 ] {{alias}}.ndarray( N, ca, cx, strideX, offsetX ) @@ -102,21 +90,13 @@ > var cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); > var ca = new {{alias:@stdlib/complex/float32/ctor}}( 2.0, 2.0 ); > {{alias}}.ndarray( 2, ca, cx, 1, 0 ); - > var z = cx.get( 0 ); - > var re = {{alias:@stdlib/complex/float32/real}}( z ) - -2.0 - > var im = {{alias:@stdlib/complex/float32/imag}}( z ) - 6.0 + [ 0.0, 4.0, -2.0, 10.0 ] // Advanced indexing: > cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); > ca = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 2.0 ); > {{alias}}.ndarray( 2, ca, cx, 1, 2 ); - > z = cx.get( 2 ); - > re = {{alias:@stdlib/complex/float32/real}}( z ) - -7.0 - > im = {{alias:@stdlib/complex/float32/imag}}( z ) - 16.0 + [ 1.0, 2.0, -5.0, 10.0, 5.0, 6.0, -9.0, 22.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/blas/base/cscal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/cscal/docs/types/index.d.ts index 07b49959ce4a..03a855242e7b 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/base/cscal/docs/types/index.d.ts @@ -39,22 +39,12 @@ interface Routine { * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); - * var realf = require( '@stdlib/complex/float32/real' ); - * var imagf = require( '@stdlib/complex/float32/imag' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( 3, ca, cx, 1 ); - * - * var z = cx.get( 0 ); - * // returns - * - * var re = realf( z ); - * // returns -2.0 - * - * var im = imagf( z ); - * // returns 6.0 + * // cx = [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ ( N: number, ca: Complex64, cx: Complex64Array, strideX: number ): Complex64Array; @@ -71,22 +61,12 @@ interface Routine { * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); - * var realf = require( '@stdlib/complex/float32/real' ); - * var imagf = require( '@stdlib/complex/float32/imag' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal.ndarray( 3, ca, cx, 1, 0 ); - * - * var z = cx.get( 0 ); - * // returns - * - * var re = realf( z ); - * // returns -2.0 - * - * var im = imagf( z ); - * // returns 6.0 + * // cx = [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ ndarray( N: number, ca: Complex64, cx: Complex64Array, strideX: number, offsetX: number ): Complex64Array; } @@ -103,42 +83,22 @@ interface Routine { * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); -* var realf = require( '@stdlib/complex/float32/real' ); -* var imagf = require( '@stdlib/complex/float32/imag' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( 3, ca, cx, 1 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx = [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] * * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); -* var realf = require( '@stdlib/complex/float32/real' ); -* var imagf = require( '@stdlib/complex/float32/imag' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal.ndarray( 2, ca, cx, 1, 0 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx = [ -2.0, 6.0, -2.0, 14.0, 5.0, 6.0 ] */ declare var cscal: Routine; diff --git a/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.js b/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.js index 3972bf276145..4ea634a38986 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.js +++ b/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.js @@ -45,15 +45,7 @@ var ndarray = require( './ndarray.js' ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( 3, ca, cx, 1 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ function cscal( N, ca, cx, strideX ) { var ox = stride2offset( N, strideX ); diff --git a/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.native.js b/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.native.js index d78d3b077d9d..f635cd9b98fc 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.native.js +++ b/lib/node_modules/@stdlib/blas/base/cscal/lib/cscal.native.js @@ -38,22 +38,12 @@ var addon = require( './../src/addon.node' ); * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); -* var realf = require( '@stdlib/complex/float32/real' ); -* var imagf = require( '@stdlib/complex/float32/imag' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( cx.length, ca, cx, 1 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ function cscal( N, ca, cx, strideX ) { var viewCX = reinterpret( cx, 0 ); diff --git a/lib/node_modules/@stdlib/blas/base/cscal/lib/index.js b/lib/node_modules/@stdlib/blas/base/cscal/lib/index.js index 89ba26de16fa..693de614b983 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/lib/index.js +++ b/lib/node_modules/@stdlib/blas/base/cscal/lib/index.js @@ -26,44 +26,24 @@ * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); -* var realf = require( '@stdlib/complex/float32/real' ); -* var imagf = require( '@stdlib/complex/float32/imag' ); * var cscal = require( '@stdlib/blas/base/cscal' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( 3, ca, cx, 1 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] * * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); -* var realf = require( '@stdlib/complex/float32/real' ); -* var imagf = require( '@stdlib/complex/float32/imag' ); * var cscal = require( '@stdlib/blas/base/cscal' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal.ndarray( 3, ca cx, 1, 0 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.js index 6b56245e080c..67d642f1b483 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.js @@ -38,22 +38,12 @@ var cmulf = require( '@stdlib/complex/float32/base/mul' ); * @example * var Complex64Array = require( '@stdlib/array/complex64' ); * var Complex64 = require( '@stdlib/complex/float32/ctor' ); -* var realf = require( '@stdlib/complex/float32/real' ); -* var imagf = require( '@stdlib/complex/float32/imag' ); * * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( 3, ca, cx, 1, 0 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ function cscal( N, ca, cx, strideX, offsetX ) { var ix; diff --git a/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.native.js index ad22c3f43488..d4cd7b0af3d2 100644 --- a/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/cscal/lib/ndarray.native.js @@ -46,15 +46,7 @@ var addon = require( './../src/addon.node' ); * var ca = new Complex64( 2.0, 2.0 ); * * cscal( cx.length, ca, cx, 1, 0 ); -* -* var z = cx.get( 0 ); -* // returns -* -* var re = realf( z ); -* // returns -2.0 -* -* var im = imagf( z ); -* // returns 6.0 +* // cx => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0 ] */ function cscal( N, ca, cx, strideX, offsetX ) { var viewCX = reinterpret( cx, 0 ); diff --git a/lib/node_modules/@stdlib/blas/base/drotm-wasm/README.md b/lib/node_modules/@stdlib/blas/base/drotm-wasm/README.md index bda4dcbfb039..e2991dc4a44b 100644 --- a/lib/node_modules/@stdlib/blas/base/drotm-wasm/README.md +++ b/lib/node_modules/@stdlib/blas/base/drotm-wasm/README.md @@ -53,7 +53,7 @@ The function has the following parameters: - **strideX**: index increment for `x`. - **y**: input [`Float64Array`][@stdlib/array/float64]. - **strideY**: index increment for `y`. -- **param**: parameters for the modified Givens transformation +- **param**: parameters for the modified Givens transformation. The `N` and stride parameters determine how values in the strided arrays are accessed at runtime. For example, to apply a modified Givens plane rotation to every other element, diff --git a/lib/node_modules/@stdlib/blas/base/drotm/README.md b/lib/node_modules/@stdlib/blas/base/drotm/README.md index 1c3cbd622814..40e183f70ff2 100644 --- a/lib/node_modules/@stdlib/blas/base/drotm/README.md +++ b/lib/node_modules/@stdlib/blas/base/drotm/README.md @@ -53,7 +53,7 @@ The function has the following parameters: - **strideX**: index increment for `x`. - **y**: second input [`Float64Array`][mdn-float64array]. - **strideY**: index increment for `y`. -- **param**: parameters for the modified Givens transformation +- **param**: parameters for the modified Givens transformation. The `N` and stride parameters determine how values in the strided arrays are accessed at runtime. For example, to apply a modified Givens plane rotation to every other element, diff --git a/lib/node_modules/@stdlib/blas/base/saxpy/README.md b/lib/node_modules/@stdlib/blas/base/saxpy/README.md index efac1e63552e..d8dc513995ac 100644 --- a/lib/node_modules/@stdlib/blas/base/saxpy/README.md +++ b/lib/node_modules/@stdlib/blas/base/saxpy/README.md @@ -307,8 +307,8 @@ int main( void ) { ## See Also -- [`@stdlib/blas/base/daxpy`][@stdlib/blas/base/daxpy]: multiply a vector x by a constant and add the result to y. -- [`@stdlib/blas/base/gaxpy`][@stdlib/blas/base/gaxpy]: multiply x by a constant and add the result to y. +- [`@stdlib/blas/base/daxpy`][@stdlib/blas/base/daxpy]: multiply a vector `x` by a constant and add the result to `y`. +- [`@stdlib/blas/base/gaxpy`][@stdlib/blas/base/gaxpy]: multiply a vector `x` by a constant and add the result to `y`. diff --git a/lib/node_modules/@stdlib/blas/base/sgemm/README.md b/lib/node_modules/@stdlib/blas/base/sgemm/README.md index e3356fcbab40..2f77a3779901 100644 --- a/lib/node_modules/@stdlib/blas/base/sgemm/README.md +++ b/lib/node_modules/@stdlib/blas/base/sgemm/README.md @@ -58,7 +58,7 @@ The function has the following parameters: - **lda**: stride of the first dimension of `A` (leading dimension of `A`). - **B**: second input matrix stored in linear memory as a [`Float32Array`][mdn-float32array]. - **ldb**: stride of the first dimension of `B` (leading dimension of `B`). -- **β**: scalar constant +- **β**: scalar constant. - **C**: third input matrix stored in linear memory as a [`Float32Array`][mdn-float32array]. - **ldc**: stride of the first dimension of `C` (leading dimension of `C`). diff --git a/lib/node_modules/@stdlib/blas/base/srotm/README.md b/lib/node_modules/@stdlib/blas/base/srotm/README.md index d5d0fbdf379d..5e1861198e23 100644 --- a/lib/node_modules/@stdlib/blas/base/srotm/README.md +++ b/lib/node_modules/@stdlib/blas/base/srotm/README.md @@ -53,7 +53,7 @@ The function has the following parameters: - **strideX**: index increment for `x`. - **y**: second input [`Float32Array`][mdn-float32array]. - **strideY**: index increment for `y`. -- **param**: parameters for the modified Givens transformation +- **param**: parameters for the modified Givens transformation. The `N` and stride parameters determine how values in the strided arrays are accessed at runtime. For example, to apply a modified Givens plane rotation to every other element, diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/README.md b/lib/node_modules/@stdlib/blas/base/zdscal/README.md new file mode 100644 index 000000000000..4bcd8970c392 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/README.md @@ -0,0 +1,233 @@ + + +# zdscal + +> Scale a double-precision complex floating-point vector by a double-precision floating-point constant. + +
+ +## Usage + +```javascript +var zdscal = require( '@stdlib/blas/base/zdscal' ); +``` + +#### zdscal( N, da, zx, strideZX ) + +Scales a double-precision complex floating-point vector by a double-precision floating-point constant. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); + +zdscal( 3, 2.0, zx, 1 ); + +var z = zx.get( 0 ); +// returns + +var re = real( z ); +// returns 2.0 + +var im = imag( z ); +// returns 2.0 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **da**: scalar constant. +- **zx**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideZX**: stride length for `zx`. + +The `N` and stride parameters determine which elements in `zx` are scaled by `da`. For example, to scale every other element in `zx` by `da`, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +zdscal( 2, 2.0, zx, 2 ); + +var z = zx.get( 2 ); +// returns + +var re = real( z ); +// returns 10.0 + +var im = imag( z ); +// returns 12.0 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +// Initial array: +var zx0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +// Create an offset view: +var zx1 = new Complex128Array( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Scale every element in `zx1`: +zdscal( 3, 2.0, zx1, 1 ); + +var z = zx0.get( 0 ); +// returns + +var re = real( z ); +// returns 1.0 + +var im = imag( z ); +// returns 2.0 + +z = zx0.get( 1 ); +// returns + +re = real( z ); +// returns 6.0 + +im = imag( z ); +// returns 8.0 +``` + +#### zdscal.ndarray( N, da, zx, strideZX, offsetZX ) + +Scales a double-precision complex floating-point vector by a double-precision floating-point constant using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +zdscal.ndarray( 3, 2.0, zx, 1, 0 ); + +var z = zx.get( 0 ); +// returns + +var re = real( z ); +// returns 2.0 + +var im = imag( z ); +// returns 4.0 +``` + +The function has the following additional parameters: + +- **offsetZX**: starting index for `zx`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to scale every other element in the input strided array starting from the second element, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +zdscal.ndarray( 2, 2.0, zx, 2, 1 ); + +var z = zx.get( 3 ); +// returns + +var re = real( z ); +// returns 14.0 + +var im = imag( z ); +// returns 16.0 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `zx` unchanged. +- `zdscal()` corresponds to the [BLAS][blas] level 1 function [`zdscal`][zdscal]. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zdscal = require( '@stdlib/blas/base/zdscal' ); + +function rand() { + return new Complex128( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +var zx = filledarrayBy( 10, 'complex128', rand ); +console.log( zx.toString() ); + +zdscal( zx.length, 2.0, zx, 1 ); +console.log( zx.toString() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[blas]: http://www.netlib.org/blas + +[zdscal]: https://www.netlib.org/lapack/explore-html/d2/de8/group__scal_ga40d50a435a5fcf16cf41fa80d746819f.html#ga40d50a435a5fcf16cf41fa80d746819f + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/zdscal/benchmark/benchmark.js new file mode 100644 index 000000000000..44194d6be6b4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/benchmark/benchmark.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var pkg = require( './../package.json' ).name; +var zdscal = require( './../lib/zdscal.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var zxbuf; + var zx; + + zxbuf = uniform( len*2, -100.0, 100.0, options ); + zx = new Complex128Array( zxbuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zdscal( zx.length, 2.0, zx, 1 ); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/zdscal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..ebefeb815a35 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/benchmark/benchmark.ndarray.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var pkg = require( './../package.json' ).name; +var zdscal = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var zxbuf; + var zx; + + zxbuf = uniform( len*2, -100.0, 100.0, options ); + zx = new Complex128Array( zxbuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zdscal( zx.length, 2.0, zx, 1, 0 ); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':ndarray:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/zdscal/docs/repl.txt new file mode 100644 index 000000000000..daf02cf15b11 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/docs/repl.txt @@ -0,0 +1,116 @@ + +{{alias}}( N, da, zx, strideZX ) + Scales a double-precision complex floating-point vector by a double- + precision floating-point constant. + + The `N` and stride parameters determine which elements in `zx` are scaled by + `da`. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N` is less than or equal to `0`, the function returns `zx` unchanged. + + + Parameters + ---------- + N: integer + Number of indexed elements. + + da: double + Scalar constant. + + zx: Complex128Array + Input array. + + strideZX: integer + Stride length for `zx`. + + Returns + ------- + zx: Complex128Array + Input array. + + Examples + -------- + // Standard usage: + > var zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > {{alias}}( 2, 2.0, zx, 1 ); + > var z = zx.get( 0 ); + > var re = {{alias:@stdlib/complex/float64/real}}( z ) + 2.0 + > var im = {{alias:@stdlib/complex/float64/imag}}( z ) + 4.0 + + // N and stride parameters: + > zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > {{alias}}( 2, 2.0, zx, 2 ); + > z = zx.get( 2 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + 10.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + 12.0 + + // Using typed array views: + > var zx0 = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var zx1 = new {{alias:@stdlib/array/complex128}}( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 2.0, zx1, 1 ); + > z = zx0.get( 1 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + 6.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + 8.0 + + +{{alias}}.ndarray( N, da, zx, strideZX, offsetZX ) + Scales a double-precision complex floating-point vector by a double- + precision floating-point constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + da: number + Scalar constant. + + zx: Complex128Array + Input array. + + strideZX: integer + Stride length for `zx`. + + offsetZX: integer + Starting index for `zx`. + + Returns + ------- + zx: Complex128Array + Input array. + + Examples + -------- + // Standard usage: + > var zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > {{alias}}.ndarray( 2, 2.0, zx, 1, 0 ); + > var z = zx.get( 0 ); + > var re = {{alias:@stdlib/complex/float64/real}}( z ) + 2.0 + > var im = {{alias:@stdlib/complex/float64/imag}}( z ) + 4.0 + + // Advanced indexing: + > zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + > {{alias}}.ndarray( 2, 2.0, zx, 1, 2 ); + > z = zx.get( 2 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + 10.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + 12.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/zdscal/docs/types/index.d.ts new file mode 100644 index 000000000000..e669d140c00f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/docs/types/index.d.ts @@ -0,0 +1,139 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zdscal`. +*/ +interface Routine { + /** + * Scales a double-precision complex floating-point vector by a double-precision floating-point constant. + * + * @param N - number of indexed elements + * @param za - scalar constant + * @param zx - input array + * @param strideZX - `zx` stride length + * @returns input array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * zdscal( 3, 2.0, zx, 1 ); + * + * var z = zx.get( 0 ); + * // returns + * + * var re = real( z ); + * // returns 2.0 + * + * var im = imag( z ); + * // returns 4.0 + */ + ( N: number, da: number, zx: Complex128Array, strideZX: number ): Complex128Array; + + /** + * Scales a double-precision complex floating-point vector by a double-precision floating-point constant. + * + * @param N - number of indexed elements + * @param da - scalar constant + * @param zx - input array + * @param strideZX - `zx` stride length + * @param offsetZX - starting index for `zx` + * @returns input array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * zdscal.ndarray( 3, 2.0, zx, 1, 0 ); + * + * var z = zx.get( 0 ); + * // returns + * + * var re = real( z ); + * // returns 2.0 + * + * var im = imag( z ); + * // returns 4.0 + */ + ndarray( N: number, da: number, zx: Complex128Array, strideZX: number, offsetZX: number ): Complex128Array; +} + +/** +* Scales a double-precision complex floating-point vector by a double-precision floating-point constant. +* +* @param N - number of indexed elements +* @param da - scalar constant +* @param zx - input array +* @param strideZX - `zx` stride length +* @returns input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zdscal( 3, 2.0, zx, 1 ); +* +* var z = zx.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 6.0 +* +* var im = imag( z ); +* // returns 8.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zdscal.ndarray( 2, 2.0, zx, 1, 1 ); +* +* var z = zx.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 10.0 +* +* var im = imag( z ); +* // returns 12.0 +*/ +declare var zdscal: Routine; + + +// EXPORTS // + +export = zdscal; diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/zdscal/docs/types/test.ts new file mode 100644 index 000000000000..d857869e57da --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/docs/types/test.ts @@ -0,0 +1,191 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import zdscal = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zdscal( zx.length, 2.0, zx, 1 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal( '10', 2.0, zx, 1 ); // $EzxpectError + zdscal( true, 2.0, zx, 1 ); // $ExpectError + zdscal( false, 2.0, zx, 1 ); // $ExpectError + zdscal( null, 2.0, zx, 1 ); // $ExpectError + zdscal( undefined, 2.0, zx, 1 ); // $ExpectError + zdscal( [], 2.0, zx, 1 ); // $ExpectError + zdscal( {}, 2.0, zx, 1 ); // $ExpectError + zdscal( ( zx: number ): number => zx, 2.0, zx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal( zx.length, new Complex128( 1.0, 2.0 ), zx, 1 ); // $ExpectError + zdscal( zx.length, '10', zx, 1 ); // $ExpectError + zdscal( zx.length, true, zx, 1 ); // $ExpectError + zdscal( zx.length, false, zx, 1 ); // $ExpectError + zdscal( zx.length, null, zx, 1 ); // $ExpectError + zdscal( zx.length, undefined, zx, 1 ); // $ExpectError + zdscal( zx.length, [ '1' ], zx, 1 ); // $ExpectError + zdscal( zx.length, {}, zx, 1 ); // $ExpectError + zdscal( zx.length, ( zx: number ): number => zx, zx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zdscal( zx.length, 2.0, 10, 1 ); // $ExpectError + zdscal( zx.length, 2.0, '10', 1 ); // $ExpectError + zdscal( zx.length, 2.0, true, 1 ); // $ExpectError + zdscal( zx.length, 2.0, false, 1 ); // $ExpectError + zdscal( zx.length, 2.0, null, 1 ); // $ExpectError + zdscal( zx.length, 2.0, undefined, 1 ); // $ExpectError + zdscal( zx.length, 2.0, [ '1' ], 1 ); // $ExpectError + zdscal( zx.length, 2.0, {}, 1 ); // $ExpectError + zdscal( zx.length, 2.0, ( zx: number ): number => zx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal( zx.length, 2.0, zx, '10' ); // $ExpectError + zdscal( zx.length, 2.0, zx, true ); // $ExpectError + zdscal( zx.length, 2.0, zx, false ); // $ExpectError + zdscal( zx.length, 2.0, zx, null ); // $ExpectError + zdscal( zx.length, 2.0, zx, undefined ); // $ExpectError + zdscal( zx.length, 2.0, zx, [] ); // $ExpectError + zdscal( zx.length, 2.0, zx, {} ); // $ExpectError + zdscal( zx.length, 2.0, zx, ( zx: number ): number => zx ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const zx = new Complex128Array( 10 ); + + zdscal(); // $ExpectError + zdscal( zx.length ); // $ExpectError + zdscal( zx.length, 2.0 ); // $ExpectError + zdscal( zx.length, 2.0, zx ); // $ExpectError + zdscal( zx.length, 2.0, zx, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zdscal.ndarray( zx.length, 2.0, zx, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal.ndarray( '10', 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( true, 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( false, 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( null, 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( undefined, 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( [], 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( {}, 2.0, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( ( zx: number ): number => zx, 2.0, zx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal.ndarray( zx.length, new Complex128( 1.0, 2.0 ), zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, '10', zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, true, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, false, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, null, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, undefined, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, [ '1' ], zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, {}, zx, 1, 0 ); // $ExpectError + zdscal.ndarray( zx.length, ( zx: number ): number => zx, zx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zdscal( zx.length, 2.0, 10, 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, '10', 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, true, 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, false, 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, null, 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, undefined, 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, [ '1' ], 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, {}, 1, 0 ); // $ExpectError + zdscal( zx.length, 2.0, ( zx: number ): number => zx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal.ndarray( zx.length, 2.0, zx, '10', 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, true, 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, false, 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, null, 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, undefined, 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, [], 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, {}, 0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, ( zx: number ): number => zx, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zdscal.ndarray( zx.length, 2.0, zx, 1, '10' ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, true ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, false ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, null ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, undefined ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, [] ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, {} ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, ( zx: number ): number => zx ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const zx = new Complex128Array( 10 ); + + zdscal.ndarray(); // $ExpectError + zdscal.ndarray( zx.length ); // $ExpectError + zdscal.ndarray( zx.length, 2.0 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1 ); // $ExpectError + zdscal.ndarray( zx.length, 2.0, zx, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/examples/index.js b/lib/node_modules/@stdlib/blas/base/zdscal/examples/index.js new file mode 100644 index 000000000000..86e6529bb69e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zdscal = require( './../lib' ); + +function rand() { + return new Complex128( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +var zx = filledarrayBy( 10, 'complex128', rand ); +console.log( zx.toString() ); + +zdscal( zx.length, 2.0, zx, 1 ); +console.log( zx.toString() ); diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/lib/index.js b/lib/node_modules/@stdlib/blas/base/zdscal/lib/index.js new file mode 100644 index 000000000000..bed34c7d314b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/lib/index.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 1 routine to scale a double-precision complex floating-point vector by a double-precision floating-point constant. +* +* @module @stdlib/blas/base/zdscal +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zdscal = require( '@stdlib/blas/base/zdscal' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zdscal( 3, 2.0, zx, 1 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns -2.0 +* +* var im = imag( z ); +* // returns 6.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zdscal = require( '@stdlib/blas/base/zdscal' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zdscal.ndarray( 3, 2.0, zx, 1, 0 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns -2.0 +* +* var im = imag( z ); +* // returns 6.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zdscal; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zdscal = main; +} else { + zdscal = tmp; +} + + +// EXPORTS // + +module.exports = zdscal; + +// exports: { "ndarray": "zdscal.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/lib/main.js b/lib/node_modules/@stdlib/blas/base/zdscal/lib/main.js new file mode 100644 index 000000000000..2d88da0211e0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zdscal = require( './zdscal.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zdscal, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zdscal; diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/zdscal/lib/ndarray.js new file mode 100644 index 000000000000..37182fe629d5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/lib/ndarray.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + + +// MAIN // + +/** +* Scales a double-precision complex floating-point vector by a double-precision floating-point constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} da - constant +* @param {Complex128Array} zx - input array +* @param {integer} strideZX - `zx` stride length +* @param {NonNegativeInteger} offsetZX - starting `zx` index +* @returns {Complex128Array} input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zdscal( 3, 2.0, zx, 1, 0 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 2.0 +* +* var im = imag( z ); +* // returns 4.0 +*/ +function zdscal( N, da, zx, strideZX, offsetZX ) { + var zx64; + var ix; + var sx; + var i; + + if ( N <= 0 || da === 1.0 ) { + return zx; + } + // Reinterpret the input array as a real-valued array of interleaved real and imaginary components: + zx64 = reinterpret( zx, 0 ); + + // Adjust the stride and offset accordingly: + ix = offsetZX * 2; + sx = strideZX * 2; + + for ( i = 0; i < N; i++ ) { + zx64[ ix ] *= da; + zx64[ ix+1 ] *= da; + ix += sx; + } + return zx; +} + + +// EXPORTS // + +module.exports = zdscal; diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/lib/zdscal.js b/lib/node_modules/@stdlib/blas/base/zdscal/lib/zdscal.js new file mode 100644 index 000000000000..c68df863272d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/lib/zdscal.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Scales a double-precision complex floating-point vector by a double-precision floating-point constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} da - constant +* @param {Complex128Array} zx - input array +* @param {integer} strideZX - `zx` stride length +* @returns {Complex128Array} input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zdscal( 3, 2.0, zx, 1 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 2.0 +* +* var im = imag( z ); +* // returns 4.0 +*/ +function zdscal( N, da, zx, strideZX ) { + return ndarray( N, da, zx, strideZX, stride2offset( N, strideZX ) ); +} + + +// EXPORTS // + +module.exports = zdscal; diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/package.json b/lib/node_modules/@stdlib/blas/base/zdscal/package.json new file mode 100644 index 000000000000..2107fd81e8c7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/blas/base/zdscal", + "version": "0.0.0", + "description": "Scale a double-precision complex floating-point vector by a double-precision floating-point constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 1", + "linear", + "algebra", + "subroutines", + "zdscal", + "scale", + "vector", + "typed", + "array", + "ndarray", + "complex", + "complex128", + "double", + "float64", + "float64array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/test/test.js b/lib/node_modules/@stdlib/blas/base/zdscal/test/test.js new file mode 100644 index 000000000000..67ccee99c8a3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var isBrowser = require( '@stdlib/assert/is-browser' ); +var zdscal = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': isBrowser +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zdscal, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zdscal.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zdscal = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zdscal, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zdscal; + var main; + + main = require( './../lib/zdscal.js' ); + + zdscal = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zdscal, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/base/zdscal/test/test.ndarray.js new file mode 100644 index 000000000000..c8e16e0b6450 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/test/test.ndarray.js @@ -0,0 +1,267 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zdscal = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zdscal, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( zdscal.length, 5, 'arity of 5' ); + t.end(); +}); + +tape( 'the function scales elements from `zx` by `da`', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.3, // 1 + 0.1, // 1 + 0.5, // 2 + 0.0, // 2 + 0.0, // 3 + 0.5, // 3 + 0.0, // 4 + 0.2, // 4 + 2.0, + 3.0, + 2.0, + 3.0 + ]); + + zdscal( 4, 2.0, zx, 1, 0 ); + + expected = new Complex128Array([ + 0.6, // 1 + 0.2, // 1 + 1.0, // 2 + 0.0, // 2 + 0.0, // 3 + 1.0, // 3 + 0.0, // 4 + 0.4, // 4 + 2.0, + 3.0, + 2.0, + 3.0 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, // 1 + 0.1, // 1 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 3 + -0.3, // 3 + 7.0, + 2.0 + ]); + + zdscal( 3, 2.0, zx, 2, 0 ); + + expected = new Complex128Array([ + 0.2, // 1 + 0.2, // 1 + 3.0, + 6.0, + -1.2, // 2 + 0.2, // 2 + 4.0, + 7.0, + 0.2, // 3 + -0.6, // 3 + 7.0, + 2.0 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, // 3 + 0.1, // 3 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 1 + -0.3, // 1 + 7.0, + 2.0 + ]); + + zdscal( 3, 2.0, zx, -2, 4 ); + + expected = new Complex128Array([ + 0.2, // 3 + 0.2, // 3 + 3.0, + 6.0, + -1.2, // 2 + 0.2, // 2 + 4.0, + 7.0, + 0.2, // 1 + -0.6, // 1 + 7.0, + 2.0 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `zx` offset', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + 6.0, // 1 + 0.1, // 2 + -0.3, // 2 + 7.0, // 3 + 2.0 // 3 + ]); + + zdscal( 3, 2.0, zx, 1, 3 ); + + expected = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 8.0, // 1 + 12.0, // 1 + 0.2, // 2 + -0.6, // 2 + 14.0, // 3 + 4.0 // 3 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + out = zdscal( 4, 2.0, zx, 1, 0 ); + + t.strictEqual( out, zx, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + expected = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); // eslint-disable-line max-len + + zdscal( -1, 2.0, zx, 1, 0 ); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + + zdscal( 0, 2.0, zx, 1, 0 ); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 2 + 6.0, // 2 + 0.1, + -0.3, + 7.0, + 2.0, + 2.0, // 1 + 3.0 // 1 + ]); + + zdscal( 2, 2.0, zx, -3, 6 ); + + expected = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 8.0, // 2 + 12.0, // 2 + 0.1, + -0.3, + 7.0, + 2.0, + 4.0, // 1 + 6.0 // 1 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/zdscal/test/test.zdscal.js b/lib/node_modules/@stdlib/blas/base/zdscal/test/test.zdscal.js new file mode 100644 index 000000000000..dd012578436b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/zdscal/test/test.zdscal.js @@ -0,0 +1,217 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zdscal = require( './../lib/zdscal.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zdscal, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( zdscal.length, 4, 'arity of 4' ); + t.end(); +}); + +tape( 'the function scales elements from `zx` by `da`', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.3, // 1 + 0.1, // 1 + 0.5, // 2 + 0.0, // 2 + 0.0, // 3 + 0.5, // 3 + 0.0, // 4 + 0.2 // 4 + ]); + + zdscal( 4, 2.0, zx, 1 ); + + expected = new Complex128Array([ + 0.6, // 1 + 0.2, // 1 + 1.0, // 2 + 0.0, // 2 + 0.0, // 3 + 1.0, // 3 + 0.0, // 4 + 0.4 // 4 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, // 1 + 0.1, // 1 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 3 + -0.3, // 3 + 7.0, + 2.0 + ]); + + zdscal( 3, 2.0, zx, 2 ); + + expected = new Complex128Array([ + 0.2, // 1 + 0.2, // 1 + 3.0, + 6.0, + -1.2, // 2 + 0.2, // 2 + 4.0, + 7.0, + 0.2, // 3 + -0.6, // 3 + 7.0, + 2.0 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, // 3 + 0.1, // 3 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 1 + -0.3, // 1 + 7.0, + 2.0 + ]); + + zdscal( 3, 2.0, zx, -2 ); + + expected = new Complex128Array([ + 0.2, // 3 + 0.2, // 3 + 3.0, + 6.0, + -1.2, // 2 + 0.2, // 2 + 4.0, + 7.0, + 0.2, // 1 + -0.6, // 1 + 7.0, + 2.0 + ]); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + out = zdscal( 4, 2.0, zx, 1 ); + + t.strictEqual( out, zx, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + expected = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); // eslint-disable-line max-len + + zdscal( -1, 2.0, zx, 1 ); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + + zdscal( 0, 2.0, zx, 1 ); + t.strictEqual( isSameComplex128Array( zx, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var zx0; + var zx1; + + // Initial array: + zx0 = new Complex128Array([ + 0.1, + -0.3, + 8.0, // 1 + 9.0, // 1 + 0.5, // 2 + -0.1, // 2 + 2.0, // 3 + 5.0, // 3 + 2.0, + 3.0 + ]); + + // Create offset view: + zx1 = new Complex128Array( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + + zdscal( 3, 2.0, zx1, 1 ); + + expected = new Complex128Array([ + 0.1, + -0.3, + 16.0, // 1 + 18.0, // 1 + 1.0, // 2 + -0.2, // 2 + 4.0, // 3 + 10.0, // 3 + 2.0, + 3.0 + ]); + t.strictEqual( isSameComplex128Array( zx0, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md index 3d13ca4e0660..1ee952c9ebd3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/README.md @@ -86,30 +86,30 @@ var ns = extblas; - [`dssumpw( N, x, strideX )`][@stdlib/blas/ext/base/dssumpw]: calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation and returning an extended precision result. - [`dsum( N, x, strideX )`][@stdlib/blas/ext/base/dsum]: calculate the sum of double-precision floating-point strided array elements. - [`dsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn]: calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. -- [`dsumkbn2( N, x, stride )`][@stdlib/blas/ext/base/dsumkbn2]: calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. -- [`dsumors( N, x, stride )`][@stdlib/blas/ext/base/dsumors]: calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation. -- [`dsumpw( N, x, stride )`][@stdlib/blas/ext/base/dsumpw]: calculate the sum of double-precision floating-point strided array elements using pairwise summation. -- [`gapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapx]: add a constant to each element in a strided array. -- [`gapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsum]: add a constant to each strided array element and compute the sum. -- [`gapxsumkbn( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumkbn]: add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. -- [`gapxsumkbn2( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumkbn2]: add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. -- [`gapxsumors( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumors]: add a constant to each strided array element and compute the sum using ordinary recursive summation. -- [`gapxsumpw( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumpw]: add a constant to each strided array element and compute the sum using pairwise summation. -- [`gasumpw( N, x, stride )`][@stdlib/blas/ext/base/gasumpw]: calculate the sum of absolute values (_L1_ norm) of strided array elements using pairwise summation. +- [`dsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn2]: calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. +- [`dsumors( N, x, strideX )`][@stdlib/blas/ext/base/dsumors]: calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation. +- [`dsumpw( N, x, strideX )`][@stdlib/blas/ext/base/dsumpw]: calculate the sum of double-precision floating-point strided array elements using pairwise summation. +- [`gapx( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapx]: add a scalar constant to each element in a strided array. +- [`gapxsum( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsum]: add a scalar constant to each strided array element and compute the sum. +- [`gapxsumkbn( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumkbn]: add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. +- [`gapxsumkbn2( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumkbn2]: add a scalar constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. +- [`gapxsumors( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumors]: add a scalar constant to each strided array element and compute the sum using ordinary recursive summation. +- [`gapxsumpw( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumpw]: add a scalar constant to each strided array element and compute the sum using pairwise summation. +- [`gasumpw( N, x, strideX )`][@stdlib/blas/ext/base/gasumpw]: calculate the sum of absolute values (_L1_ norm) of strided array elements using pairwise summation. - [`gcusum( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gcusum]: calculate the cumulative sum of strided array elements. - [`gcusumkbn( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gcusumkbn]: calculate the cumulative sum of strided array elements using an improved Kahan–Babuška algorithm. - [`gcusumkbn2( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gcusumkbn2]: calculate the cumulative sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. - [`gcusumors( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gcusumors]: calculate the cumulative sum of strided array elements using ordinary recursive summation. - [`gcusumpw( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gcusumpw]: calculate the cumulative sum of strided array elements using pairwise summation. -- [`gfillBy( N, x, stride, clbk[, thisArg] )`][@stdlib/blas/ext/base/gfill-by]: fill a strided array according to a provided callback function. -- [`gfill( N, alpha, x, stride )`][@stdlib/blas/ext/base/gfill]: fill a strided array with a specified scalar constant. +- [`gfillBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/blas/ext/base/gfill-by]: fill a strided array according to a provided callback function. +- [`gfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gfill]: fill a strided array with a specified scalar constant. - [`gnannsumkbn( N, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/gnannsumkbn]: calculate the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm. -- [`gnansum( N, x, stride )`][@stdlib/blas/ext/base/gnansum]: calculate the sum of strided array elements, ignoring `NaN` values. -- [`gnansumkbn( N, x, stride )`][@stdlib/blas/ext/base/gnansumkbn]: calculate the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm. -- [`gnansumkbn2( N, x, stride )`][@stdlib/blas/ext/base/gnansumkbn2]: calculate the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm. -- [`gnansumors( N, x, stride )`][@stdlib/blas/ext/base/gnansumors]: calculate the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation. -- [`gnansumpw( N, x, stride )`][@stdlib/blas/ext/base/gnansumpw]: calculate the sum of strided array elements, ignoring `NaN` values and using pairwise summation. -- [`grev( N, x, stride )`][@stdlib/blas/ext/base/grev]: reverse a strided array in-place. +- [`gnansum( N, x, strideX )`][@stdlib/blas/ext/base/gnansum]: calculate the sum of strided array elements, ignoring `NaN` values. +- [`gnansumkbn( N, x, strideX )`][@stdlib/blas/ext/base/gnansumkbn]: calculate the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm. +- [`gnansumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/gnansumkbn2]: calculate the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm. +- [`gnansumors( N, x, strideX )`][@stdlib/blas/ext/base/gnansumors]: calculate the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation. +- [`gnansumpw( N, x, strideX )`][@stdlib/blas/ext/base/gnansumpw]: calculate the sum of strided array elements, ignoring `NaN` values and using pairwise summation. +- [`grev( N, x, strideX )`][@stdlib/blas/ext/base/grev]: reverse a strided array in-place. - [`gsort2hp( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2hp]: simultaneously sort two strided arrays based on the sort order of the first array using heapsort. - [`gsort2ins( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2ins]: simultaneously sort two strided arrays based on the sort order of the first array using insertion sort. - [`gsort2sh( N, order, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gsort2sh]: simultaneously sort two strided arrays based on the sort order of the first array using Shellsort. @@ -117,17 +117,17 @@ var ns = extblas; - [`gsortins( N, order, x, stride )`][@stdlib/blas/ext/base/gsortins]: sort a strided array using insertion sort. - [`gsortsh( N, order, x, stride )`][@stdlib/blas/ext/base/gsortsh]: sort a strided array using Shellsort. - [`gsum( N, x, stride )`][@stdlib/blas/ext/base/gsum]: calculate the sum of strided array elements. -- [`gsumkbn( N, x, stride )`][@stdlib/blas/ext/base/gsumkbn]: calculate the sum of strided array elements using an improved Kahan–Babuška algorithm. -- [`gsumkbn2( N, x, stride )`][@stdlib/blas/ext/base/gsumkbn2]: calculate the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. -- [`gsumors( N, x, stride )`][@stdlib/blas/ext/base/gsumors]: calculate the sum of strided array elements using ordinary recursive summation. -- [`gsumpw( N, x, stride )`][@stdlib/blas/ext/base/gsumpw]: calculate the sum of strided array elements using pairwise summation. -- [`sapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapx]: add a constant to each element in a single-precision floating-point strided array. -- [`sapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsum]: add a constant to each single-precision floating-point strided array element and compute the sum. -- [`sapxsumkbn( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumkbn]: add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. -- [`sapxsumkbn2( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumkbn2]: add a constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. -- [`sapxsumors( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumors]: add a constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation. -- [`sapxsumpw( N, alpha, x, stride )`][@stdlib/blas/ext/base/sapxsumpw]: add a constant to each single-precision floating-point strided array element and compute the sum using pairwise summation. -- [`sasumpw( N, x, stride )`][@stdlib/blas/ext/base/sasumpw]: calculate the sum of absolute values (_L1_ norm) of single-precision floating-point strided array elements using pairwise summation. +- [`gsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/gsumkbn]: calculate the sum of strided array elements using an improved Kahan–Babuška algorithm. +- [`gsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/gsumkbn2]: calculate the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. +- [`gsumors( N, x, strideX )`][@stdlib/blas/ext/base/gsumors]: calculate the sum of strided array elements using ordinary recursive summation. +- [`gsumpw( N, x, strideX )`][@stdlib/blas/ext/base/gsumpw]: calculate the sum of strided array elements using pairwise summation. +- [`sapx( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapx]: add a scalar constant to each element in a single-precision floating-point strided array. +- [`sapxsum( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsum]: add a scalar constant to each single-precision floating-point strided array element and compute the sum. +- [`sapxsumkbn( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumkbn]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. +- [`sapxsumkbn2( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumkbn2]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. +- [`sapxsumors( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumors]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation. +- [`sapxsumpw( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sapxsumpw]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using pairwise summation. +- [`sasumpw( N, x, strideX )`][@stdlib/blas/ext/base/sasumpw]: calculate the sum of absolute values (_L1_ norm) of single-precision floating-point strided array elements using pairwise summation. - [`scusum( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/scusum]: calculate the cumulative sum of single-precision floating-point strided array elements. - [`scusumkbn( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/scusumkbn]: calculate the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. - [`scusumkbn2( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/scusumkbn2]: calculate the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md b/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md index f0a97cb8c937..c6a3afbd39f4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/README.md @@ -48,7 +48,7 @@ The function has the following parameters: - **N**: number of indexed elements. - **alpha**: scalar constant. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: stride length for `x`. +- **strideX**: stride length. The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element: @@ -168,14 +168,14 @@ console.log( x ); #include "stdlib/blas/ext/base/dapx.h" ``` -#### c_dapx( N, alpha, \*X, strideX ) +#### stdlib_strided_dapx( N, alpha, \*X, strideX ) Adds a scalar constant to each element in a double-precision floating-point strided array. ```c double x[] = { 1.0, 2.0, 3.0, 4.0 }; -c_dapx( 4, 5.0, x, 1 ); +stdlib_strided_dapx( 4, 5.0, x, 1 ); ``` @@ -187,17 +187,17 @@ The function accepts the following arguments: - **strideX**: `[in] CBLAS_INT` stride length for `X`. ```c -void c_dapx( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ); +void stdlib_strided_dapx( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ); ``` -#### c_dapx_ndarray( N, alpha, \*X, strideX, offsetX ) +#### stdlib_strided_dapx_ndarray( N, alpha, \*X, strideX, offsetX ) Adds a scalar constant to each element in a double-precision floating-point strided array using alternative indexing semantics. ```c double x[] = { 1.0, 2.0, 3.0, 4.0 }; -c_dapx_ndarray( 4, 5.0, x, 1, 0 ); +stdlib_strided_dapx_ndarray( 4, 5.0, x, 1, 0 ); ``` The function accepts the following arguments: @@ -205,11 +205,11 @@ The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **alpha**: `[in] double` scalar constant. - **X**: `[inout] double*` input array. -- **strideX**: `[in] CBLAS_INT` stride length for `X`. -- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. ```c -void c_dapx_ndarray( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +void stdlib_strided_dapx_ndarray( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); ``` @@ -245,7 +245,7 @@ int main( void ) { const int strideX = 1; // Fill the array: - c_dapx( N, 5.0, x, strideX ); + stdlib_strided_dapx( N, 5.0, x, strideX ); // Print the result: for ( int i = 0; i < 8; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/c/benchmark.length.c index a4e9dbd372b0..678f2c5df6c1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/benchmark/c/benchmark.length.c @@ -106,7 +106,7 @@ static double benchmark1( int iterations, int len ) { t = tic(); for ( i = 0; i < iterations; i++ ) { // cppcheck-suppress uninitvar - c_dapx( len, 5.0, x, 1 ); + stdlib_strided_dapx( len, 5.0, x, 1 ); if ( x[ 0 ] != x[ 0 ] ) { printf( "should not return NaN\n" ); break; @@ -131,7 +131,7 @@ static double benchmark2( int iterations, int len ) { t = tic(); for ( i = 0; i < iterations; i++ ) { // cppcheck-suppress uninitvar - c_dapx_ndarray( len, 5.0, x, 1, 0 ); + stdlib_strided_dapx_ndarray( len, 5.0, x, 1, 0 ); if ( x[ 0 ] != x[ 0 ] ) { printf( "should not return NaN\n" ); break; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/c/example.c index ec1ac38026ef..e77cbe0d09ba 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/examples/c/example.c @@ -30,7 +30,7 @@ int main( void ) { const int strideX = 1; // Add a constant to each element: - c_dapx( N, 5.0, x, strideX ); + stdlib_strided_dapx( N, 5.0, x, strideX ); // Print the result: for ( int i = 0; i < 8; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/include/stdlib/blas/ext/base/dapx.h b/lib/node_modules/@stdlib/blas/ext/base/dapx/include/stdlib/blas/ext/base/dapx.h index d292078b1ca3..7298dbee5a8f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/include/stdlib/blas/ext/base/dapx.h +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/include/stdlib/blas/ext/base/dapx.h @@ -31,12 +31,12 @@ extern "C" { /** * Adds a scalar constant to each element in a double-precision floating-point strided array. */ -void API_SUFFIX(c_dapx)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ); +void API_SUFFIX(stdlib_strided_dapx)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ); /** * Adds a scalar constant to each element in a double-precision floating-point strided array using alternative indexing semantics. */ -void API_SUFFIX(c_dapx_ndarray)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +void API_SUFFIX(stdlib_strided_dapx_ndarray)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.js index efe6621ddb44..d13e30fd1128 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.js @@ -39,9 +39,8 @@ var M = 5; * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); -* var alpha = 5.0; * -* dapx( 3, alpha, x, 1, x.length-3 ); +* dapx( 3, 5.0, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, 1.0, 10.0, -1.0 ] */ function dapx( N, alpha, x, strideX, offsetX ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.native.js index f743b6fac10a..c9291a1a3c20 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/lib/ndarray.native.js @@ -39,9 +39,8 @@ var addon = require( './../src/addon.node' ); * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); -* var alpha = 5.0; * -* dapx( 3, alpha, x, 1, x.length-3 ); +* dapx( 3, 5.0, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, 1.0, 10.0, -1.0 ] */ function dapx( N, alpha, x, strideX, offsetX ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.c index 455f74e295db..88e2c6bb251c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/src/addon.c @@ -38,7 +38,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); - API_SUFFIX(c_dapx)( N, alpha, X, strideX ); + API_SUFFIX(stdlib_strided_dapx)( N, alpha, X, strideX ); return NULL; } @@ -56,7 +56,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); - API_SUFFIX(c_dapx_ndarray)( N, alpha, X, strideX, offsetX ); + API_SUFFIX(stdlib_strided_dapx_ndarray)( N, alpha, X, strideX, offsetX ); return NULL; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapx/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dapx/src/main.c index 193e2fec7590..dd9e1084271b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapx/src/main.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dapx/src/main.c @@ -28,9 +28,9 @@ * @param X input array * @param strideX stride length */ -void API_SUFFIX(c_dapx)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ) { +void API_SUFFIX(stdlib_strided_dapx)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ) { CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); - API_SUFFIX(c_dapx_ndarray)( N, alpha, X, strideX, ox ); + API_SUFFIX(stdlib_strided_dapx_ndarray)( N, alpha, X, strideX, ox ); } /** @@ -42,7 +42,7 @@ void API_SUFFIX(c_dapx)( const CBLAS_INT N, const double alpha, double *X, const * @param strideX stride length * @param offsetX starting index */ -void API_SUFFIX(c_dapx_ndarray)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { +void API_SUFFIX(stdlib_strided_dapx_ndarray)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { CBLAS_INT ix; CBLAS_INT m; CBLAS_INT i; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md index 1b1afe9a0d9d..79234328c4e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/README.md @@ -285,7 +285,7 @@ int main( void ) { - [`@stdlib/blas/ext/base/dapxsum`][@stdlib/blas/ext/base/dapxsum]: add a scalar constant to each double-precision floating-point strided array element and compute the sum. - [`@stdlib/blas/ext/base/dsumkbn`][@stdlib/blas/ext/base/dsumkbn]: calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. -- [`@stdlib/blas/ext/base/gapxsumkbn`][@stdlib/blas/ext/base/gapxsumkbn]: add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. +- [`@stdlib/blas/ext/base/gapxsumkbn`][@stdlib/blas/ext/base/gapxsumkbn]: add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. - [`@stdlib/blas/ext/base/sapxsumkbn`][@stdlib/blas/ext/base/sapxsumkbn]: add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/manifest.json index f587df37ca10..e5e1db92b9e7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumkbn/manifest.json @@ -79,7 +79,8 @@ "libpath": [], "dependencies": [ "@stdlib/blas/base/shared", - "@stdlib/strided/base/stride2offset" + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/abs" ] }, { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dapxsumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/dapxsumors/README.md index 01bbc0703969..20e7f8ed63ba 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dapxsumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dapxsumors/README.md @@ -280,10 +280,10 @@ int main( void ) { ## See Also -- [`@stdlib/blas/ext/base/dapxsum`][@stdlib/blas/ext/base/dapxsum]: adds a constant to each double-precision floating-point strided array element and computes the sum. +- [`@stdlib/blas/ext/base/dapxsum`][@stdlib/blas/ext/base/dapxsum]: add a scalar constant to each double-precision floating-point strided array element and compute the sum. - [`@stdlib/blas/ext/base/dsumors`][@stdlib/blas/ext/base/dsumors]: calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation. -- [`@stdlib/blas/ext/base/gapxsumors`][@stdlib/blas/ext/base/gapxsumors]: adds a constant to each strided array element and computes the sum using ordinary recursive summation. -- [`@stdlib/blas/ext/base/sapxsumors`][@stdlib/blas/ext/base/sapxsumors]: adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +- [`@stdlib/blas/ext/base/gapxsumors`][@stdlib/blas/ext/base/gapxsumors]: add a constant to each strided array element and compute the sum using ordinary recursive summation. +- [`@stdlib/blas/ext/base/sapxsumors`][@stdlib/blas/ext/base/sapxsumors]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation. diff --git a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts index f3eac464da8f..1012e374b5c1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts @@ -1370,7 +1370,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1396,7 +1396,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1422,7 +1422,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1444,12 +1444,12 @@ interface Namespace { dsumpw: typeof dsumpw; /** - * Adds a constant to each element in a strided array. + * Adds a scalar constant to each element in a strided array. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -1467,12 +1467,12 @@ interface Namespace { gapx: typeof gapx; /** - * Adds a constant to each strided array element and computes the sum. + * Adds a scalar constant to each strided array element and computes the sum. * * @param N - number of indexed elements * @param alpha - constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1490,12 +1490,12 @@ interface Namespace { gapxsum: typeof gapxsum; /** - * Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. + * Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1513,12 +1513,12 @@ interface Namespace { gapxsumkbn: typeof gapxsumkbn; /** - * Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. + * Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1536,12 +1536,12 @@ interface Namespace { gapxsumkbn2: typeof gapxsumkbn2; /** - * Adds a constant to each strided array element and computes the sum using ordinary recursive summation. + * Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1559,12 +1559,12 @@ interface Namespace { gapxsumors: typeof gapxsumors; /** - * Adds a constant to each strided array element and computes the sum using pairwise summation. + * Adds a scalar constant to each strided array element and computes the sum using pairwise summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1586,7 +1586,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1609,9 +1609,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -1636,9 +1636,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -1663,9 +1663,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -1690,9 +1690,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -1717,9 +1717,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -1739,12 +1739,12 @@ interface Namespace { gcusumpw: typeof gcusumpw; /** - * Fills a strided array with a specified scalar value. + * Fills a strided array with a specified scalar constant. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -1777,8 +1777,8 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param clbk - callback + * @param strideX - stride length + * @param clbk - callback function * @param thisArg - execution context * @returns `x` * @@ -1809,9 +1809,9 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param out - output array whose first element is the sum and whose second element is the number of non-NaN elements - * @param strideOut - `out` stride length + * @param strideOut - stride length for `out` * @returns output array * * @example @@ -1835,7 +1835,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1857,7 +1857,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1879,7 +1879,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1901,7 +1901,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1923,7 +1923,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -1945,7 +1945,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -2169,7 +2169,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2191,7 +2191,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2213,7 +2213,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2235,7 +2235,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2253,12 +2253,12 @@ interface Namespace { gsumpw: typeof gsumpw; /** - * Adds a constant to each element in a single-precision floating-point strided array. + * Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -2280,12 +2280,12 @@ interface Namespace { sapx: typeof sapx; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2307,12 +2307,12 @@ interface Namespace { sapxsum: typeof sapxsum; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2334,12 +2334,12 @@ interface Namespace { sapxsumkbn: typeof sapxsumkbn; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2361,12 +2361,12 @@ interface Namespace { sapxsumkbn2: typeof sapxsumkbn2; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2388,12 +2388,12 @@ interface Namespace { sapxsumors: typeof sapxsumors; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2419,7 +2419,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -2446,9 +2446,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -2477,9 +2477,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -2508,9 +2508,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -2539,9 +2539,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -2570,9 +2570,9 @@ interface Namespace { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md index 20ea8a24b5db..8bf197f27804 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/README.md @@ -36,7 +36,7 @@ limitations under the License. var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); ``` -#### dsumkbn2( N, x, stride ) +#### dsumkbn2( N, x, strideX ) Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. @@ -45,7 +45,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var v = dsumkbn2( 3, x, 1 ); +var v = dsumkbn2( x.length, x, 1 ); // returns 1.0 ``` @@ -53,9 +53,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -80,7 +80,7 @@ var v = dsumkbn2( 4, x1, 2 ); // returns 5.0 ``` -#### dsumkbn2.ndarray( N, x, stride, offset ) +#### dsumkbn2.ndarray( N, x, strideX, offsetX ) Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. @@ -89,19 +89,18 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var v = dsumkbn2.ndarray( 3, x, 1, 0 ); +var v = dsumkbn2.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -130,11 +129,12 @@ var v = dsumkbn2.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = dsumkbn2( x.length, x, 1 ); @@ -145,8 +145,123 @@ console.log( v ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dsumkbn2.h" +``` + +#### stdlib_strided_dsumkbn2( N, \*X, strideX ) + +Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + +double v = stdlib_strided_dsumkbn2( 4, x, 1 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsumkbn2( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsumkbn2_ndarray( N, \*X, strideX, offsetX ) + +Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + +double v = stdlib_strided_dsumkbn2_ndarray( 4, x, 1, 0 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsumkbn2_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dsumkbn2.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the sum: + double v = stdlib_strided_dsumkbn2( N, x, strideX ); + + // Print the result: + printf( "sum: %lf\n", v ); +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js index 66237dbf6082..73821cb0ba02 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var dsumkbn2 = require( './../lib/dsumkbn2.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js index 1eb8239f0d78..970f9c599d42 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var dsumkbn2 = tryRequire( resolve( __dirname, './../lib/dsumkbn2.native.js' ) ) var opts = { 'skip': ( dsumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js index 88a1b89b76ed..a1140774100a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var dsumkbn2 = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js index b587ad2fde9b..3002f93ac258 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var dsumkbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/c/benchmark.length.c index b0f588bac5ce..af2585fe4ab4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + //cppcheck-suppress uninitvar v = stdlib_strided_dsumkbn2( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + //cppcheck-suppress uninitvar + v = stdlib_strided_dsumkbn2_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/repl.txt index 9f7b1409d597..ff123adf7edc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed + The `N` and stride parameters determine which elements in `x` are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,28 +34,25 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -66,10 +63,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/types/index.d.ts index 9392b4f1443b..442ae97bb82e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsumkbn2( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsumkbn2.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/c/example.c index 3fceb0339216..216365c5ba3e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/c/example.c @@ -17,7 +17,6 @@ */ #include "stdlib/blas/ext/base/dsumkbn2.h" -#include #include int main( void ) { @@ -25,13 +24,13 @@ int main( void ) { const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify the stride length: - const int64_t stride = 2; + const int strideX = 2; // Compute the sum: - double v = stdlib_strided_dsumkbn2( N, x, stride ); + double v = stdlib_strided_dsumkbn2( N, x, strideX ); // Print the result: printf( "sum: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js index c3b802e07f38..48def1b1b42b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsumkbn2 = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = dsumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include/stdlib/blas/ext/base/dsumkbn2.h b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include/stdlib/blas/ext/base/dsumkbn2.h index 510ae882cdfd..e3dbd459c213 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include/stdlib/blas/ext/base/dsumkbn2.h +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/include/stdlib/blas/ext/base/dsumkbn2.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_DSUMKBN2_H #define STDLIB_BLAS_EXT_BASE_DSUMKBN2_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. */ -double stdlib_strided_dsumkbn2( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsumkbn2)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsumkbn2_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.js index af09b995ffa2..ab046471f7da 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.js @@ -20,7 +20,8 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,63 +39,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumkbn2( N, x, 1 ); +* var v = dsumkbn2( x.length, x, 1 ); * // returns 1.0 */ -function dsumkbn2( N, x, stride ) { - var sum; - var ccs; - var ix; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c = (sum-t) + v; - } else { - c = (v-t) + sum; - } - sum = t; - t = cs + c; - if ( abs( cs ) >= abs( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - ix += stride; - } - return sum + cs + ccs; +function dsumkbn2( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.native.js index eb9fbb3338bb..edc4cb98de18 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/dsumkbn2.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumkbn2( N, x, 1 ); +* var v = dsumkbn2( x.length, x, 1 ); * // returns 1.0 */ -function dsumkbn2( N, x, stride ) { - return addon( N, x, stride ); +function dsumkbn2( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/index.js index 52d959f2b369..f224b12dde83 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/index.js @@ -28,20 +28,17 @@ * var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumkbn2( N, x, 1 ); +* var v = dsumkbn2( x.length, x, 1 ); * // returns 1.0 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = 3;; * -* var v = dsumkbn2.ndarray( N, x, 2, 1 ); +* var v = dsumkbn2.ndarray( 4, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.js index fb283fd02921..64e5d6682dbe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.js @@ -38,21 +38,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = 4; * -* var v = dsumkbn2( N, x, 2, 1 ); +* var v = dsumkbn2( 4, x, 2, 1 ); * // returns 5.0 */ -function dsumkbn2( N, x, stride, offset ) { +function dsumkbn2( N, x, strideX, offsetX ) { var sum; var ccs; var ix; @@ -66,10 +64,10 @@ function dsumkbn2( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; sum = 0.0; ccs = 0.0; // second order correction term for lost low order bits cs = 0.0; // first order correction term for lost low order bits @@ -90,7 +88,7 @@ function dsumkbn2( N, x, stride, offset ) { } cs = t; ccs += cc; - ix += stride; + ix += strideX; } return sum + cs + ccs; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.native.js index 6fdd350530d2..e254d48df707 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './dsumkbn2.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,26 +30,20 @@ var addon = require( './dsumkbn2.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = 4; * -* var v = dsumkbn2( N, x, 2, 1 ); +* var v = dsumkbn2( 4, x, 2, 1 ); * // returns 5.0 */ -function dsumkbn2( N, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - - return addon( N, view, stride ); +function dsumkbn2( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/manifest.json index bcafb815b9e0..95e0331dd32d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/manifest.json @@ -28,7 +28,7 @@ { "task": "build", "src": [ - "./src/dsumkbn2.c" + "./src/main.c" ], "include": [ "./include" @@ -40,13 +40,16 @@ "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-strided-float64array", - "@stdlib/math/base/special/abs" + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/abs", + "@stdlib/napi/create-double" ] }, { "task": "benchmark", "src": [ - "./src/dsumkbn2.c" + "./src/main.c" ], "include": [ "./include" @@ -54,13 +57,15 @@ "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", "@stdlib/math/base/special/abs" ] }, { "task": "examples", "src": [ - "./src/dsumkbn2.c" + "./src/main.c" ], "include": [ "./include" @@ -68,6 +73,8 @@ "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", "@stdlib/math/base/special/abs" ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.c index 322422386ad3..b896fa028e0d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/addon.c @@ -17,12 +17,13 @@ */ #include "stdlib/blas/ext/base/dsumkbn2.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -36,11 +37,25 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - - napi_value v; - napi_create_double( env, stdlib_strided_dsumkbn2( N, X, strideX ), &v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsumkbn2)( N, X, strideX ), v ); + return v; +} +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsumkbn2_ndarray)( N, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ); +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/dsumkbn2.c b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/dsumkbn2.c deleted file mode 100644 index 49bc11fdff51..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/dsumkbn2.c +++ /dev/null @@ -1,84 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/dsumkbn2.h" -#include "stdlib/math/base/special/abs.h" -#include - -/** -* Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. -* -* ## Method -* -* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). -* -* ## References -* -* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsumkbn2( const int64_t N, const double *X, const int64_t stride ) { - double sum; - double ccs; - int64_t ix; - int64_t i; - double cs; - double cc; - double v; - double t; - double c; - - if ( N <= 0 ) { - return 0.0; - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - ccs = 0.0; // second order correction term for lost lower order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - t = sum + v; - if ( stdlib_base_abs( sum ) >= stdlib_base_abs( v ) ) { - c = (sum-t) + v; - } else { - c = (v-t) + sum; - } - sum = t; - t = cs + c; - if ( stdlib_base_abs( cs ) >= stdlib_base_abs( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - ix += stride; - } - return sum + cs + ccs; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/main.c new file mode 100644 index 000000000000..43ea376f1f05 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/src/main.c @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dsumkbn2.h" +#include "stdlib/math/base/special/abs.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. +* +* ## Method +* +* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). +* +* ## References +* +* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsumkbn2)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX( stdlib_strided_dsumkbn2_ndarray )( N, X, strideX, ox ); +} + +/** +* Computes the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). +* +* ## References +* +* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsumkbn2_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double sum; + double ccs; + double cs; + double cc; + double v; + double t; + double c; + + if ( N <= 0 ) { + return 0.0; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * X[ ix ]; + } + sum = 0.0; + ccs = 0.0; // second order correction term for lost lower order bits + cs = 0.0; // first order correction term for lost low order bits + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + t = sum + v; + if ( stdlib_base_abs( sum ) >= stdlib_base_abs( v ) ) { + c = (sum-t) + v; + } else { + c = (v-t) + sum; + } + sum = t; + t = cs + c; + if ( stdlib_base_abs( cs ) >= stdlib_base_abs( c ) ) { + cc = (cs-t) + c; + } else { + cc = (c-t) + cs; + } + cs = t; + ccs += cc; + ix += strideX; + } + return sum + cs + ccs; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js index 0e74cf92c7cb..87c207198eea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.js @@ -139,14 +139,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumkbn2( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js index 09a7a5b243f5..831a125f8370 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.dsumkbn2.native.js @@ -230,14 +230,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumkbn2( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js index 6eaad80ee38d..e5b1b366b09a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.js @@ -139,14 +139,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumkbn2( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js index 668f399f2ab6..2fee9488664e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumkbn2/test/test.ndarray.native.js @@ -148,14 +148,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumkbn2( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsumors/README.md index a68ee7615de1..24d284967a28 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/README.md @@ -36,7 +36,7 @@ limitations under the License. var dsumors = require( '@stdlib/blas/ext/base/dsumors' ); ``` -#### dsumors( N, x, stride ) +#### dsumors( N, x, strideX ) Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation. @@ -44,9 +44,8 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsumors( N, x, 1 ); +var v = dsumors( x.length, x, 1 ); // returns 1.0 ``` @@ -54,9 +53,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -81,7 +80,7 @@ var v = dsumors( 4, x1, 2 ); // returns 5.0 ``` -#### dsumors.ndarray( N, x, stride, offset ) +#### dsumors.ndarray( N, x, strideX, offsetX ) Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. @@ -89,17 +88,16 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsumors.ndarray( N, x, 1, 0 ); +var v = dsumors.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -132,11 +130,12 @@ var v = dsumors.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsumors = require( '@stdlib/blas/ext/base/dsumors' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = dsumors( x.length, x, 1 ); @@ -147,6 +146,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dsumors.h" +``` + +#### stdlib_strided_dsumors( N, \*X, strideX ) + +Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + +double v = stdlib_strided_dsumors( 4, x, 1 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsumors( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsumors_ndarray( N, \*X, strideX, offsetX ) + +Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + +double v = stdlib_strided_dsumors_ndarray( 4, x, 1, 0 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsumors_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dsumors.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the sum: + double v = stdlib_strided_dsumors( N, x, strideX ); + + // Print the result: + printf( "sum: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.js index 9b3e2d4bef0d..a97ca4c555dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var dsumors = require( './../lib/dsumors.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.native.js index 8b672c697421..8883de399395 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var dsumors = tryRequire( resolve( __dirname, './../lib/dsumors.native.js' ) ); var opts = { 'skip': ( dsumors instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.js index 70a66dd7eb52..ad1e57e607e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var dsumors = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.native.js index 968891660d53..63748e835a6c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,8 +35,9 @@ var dsumors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsumors instanceof Error ) }; - -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -50,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/c/benchmark.length.c index b4d5522c6769..fb076870db7a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsumors( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsumors_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/repl.txt index 185990e3e948..002b814f29bc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in - the strided array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,7 +34,7 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > {{alias}}( 3, x, 2 ) 1.0 @@ -46,12 +46,12 @@ -1.0 -{{alias}}.ndarray( N, x, stride, offset ) +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -62,10 +62,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/types/index.d.ts index 83c7d3e90ec9..5424168878bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsumors( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsumors.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/c/example.c index 9e4a35796b11..fb8200a9138e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/c/example.c @@ -17,7 +17,6 @@ */ #include "stdlib/blas/ext/base/dsumors.h" -#include #include int main( void ) { @@ -25,13 +24,13 @@ int main( void ) { const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify the stride length: - const int64_t stride = 2; + const int strideX = 2; // Compute the sum: - double v = stdlib_strided_dsumors( N, x, stride ); + double v = stdlib_strided_dsumors( N, x, strideX ); // Print the result: printf( "sum: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/index.js index 135bb82786bc..d2bc6a40eb3c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsumors = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( -100.0, 100.0 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = dsumors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/include/stdlib/blas/ext/base/dsumors.h b/lib/node_modules/@stdlib/blas/ext/base/dsumors/include/stdlib/blas/ext/base/dsumors.h index 295194854344..b6ea9b5bf8cb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/include/stdlib/blas/ext/base/dsumors.h +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/include/stdlib/blas/ext/base/dsumors.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_DSUMORS_H #define STDLIB_BLAS_EXT_BASE_DSUMORS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation. */ -double stdlib_strided_dsumors( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsumors)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsumors_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.js index 83f63edf7cf2..52e15e8b6b00 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.js @@ -18,9 +18,10 @@ 'use strict'; -// VARIABLES // +// MODULES // -var M = 6; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,59 +31,19 @@ var M = 6; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumors( N, x, 1 ); +* var v = dsumors( x.length, x, 1 ); * // returns 1.0 */ -function dsumors( N, x, stride ) { - var sum; - var ix; - var m; - var i; - - sum = 0.0; - if ( N <= 0 ) { - return sum; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - // If the stride is equal to `1`, use unrolled loops... - if ( stride === 1 ) { - m = N % M; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - sum += x[ i ]; - } - } - if ( N < M ) { - return sum; - } - for ( i = m; i < N; i += M ) { - sum += x[i] + x[i+1] + x[i+2] + x[i+3] + x[i+4] + x[i+5]; - } - return sum; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - sum += x[ ix ]; - ix += stride; - } - return sum; +function dsumors( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.native.js index 0003c7a965a2..b534962fdff9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/dsumors.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumors( N, x, 1 ); +* var v = dsumors( x.length, x, 1 ); * // returns 1.0 */ -function dsumors( N, x, stride ) { - return addon( N, x, stride ); +function dsumors( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.js index ce8a477c1d06..aed48a12582f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.js @@ -30,8 +30,8 @@ var M = 6; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -42,7 +42,7 @@ var M = 6; * var v = dsumors( 4, x, 2, 1 ); * // returns 5.0 */ -function dsumors( N, x, stride, offset ) { +function dsumors( N, x, strideX, offsetX ) { var sum; var ix; var m; @@ -52,20 +52,20 @@ function dsumors( N, x, stride, offset ) { if ( N <= 0 ) { return sum; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; // If the stride is equal to `1`, use unrolled loops... - if ( stride === 1 ) { + if ( strideX === 1 ) { m = N % M; // If we have a remainder, run a clean-up loop... if ( m > 0 ) { for ( i = 0; i < m; i++ ) { sum += x[ ix ]; - ix += stride; + ix += strideX; } } if ( N < M ) { @@ -79,7 +79,7 @@ function dsumors( N, x, stride, offset ) { } for ( i = 0; i < N; i++ ) { sum += x[ ix ]; - ix += stride; + ix += strideX; } return sum; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.native.js index 7b504ac85635..ece6adfb522f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './dsumors.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,8 +30,8 @@ var addon = require( './dsumors.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -44,11 +42,8 @@ var addon = require( './dsumors.native.js' ); * var v = dsumors( 4, x, 2, 1 ); * // returns 5.0 */ -function dsumors( N, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - return addon( N, view, stride ); +function dsumors( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dsumors/manifest.json index 0e56c59ff518..090d0bc750de 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/manifest.json @@ -28,7 +28,7 @@ { "task": "build", "src": [ - "./src/dsumors.c" + "./src/main.c" ], "include": [ "./include" @@ -39,32 +39,41 @@ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float64array" + "@stdlib/napi/argv-strided-float64array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/napi/create-double" ] }, { "task": "benchmark", "src": [ - "./src/dsumors.c" + "./src/main.c" ], "include": [ "./include" ], "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] }, { "task": "examples", "src": [ - "./src/dsumors.c" + "./src/main.c" ], "include": [ "./include" ], "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/addon.c index 3a3abf37afae..d961295d7f47 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/addon.c @@ -17,12 +17,13 @@ */ #include "stdlib/blas/ext/base/dsumors.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -34,14 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - - napi_value v; - napi_status status = napi_create_double( env, stdlib_strided_dsumors( N, X, stride ), &v ); - assert( status == napi_ok ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsumors)( N, X, strideX ), v ); + return v; +} +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsumors_ndarray)( N, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/dsumors.c b/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/dsumors.c deleted file mode 100644 index 70ba331a26b5..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/dsumors.c +++ /dev/null @@ -1,71 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/dsumors.h" -#include - -/** -* Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsumors( const int64_t N, const double *X, const int64_t stride ) { - double sum; - int64_t ix; - int64_t m; - int64_t i; - - sum = 0.0; - if ( N <= 0 ) { - return sum; - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - // If the stride is equal to `1`, use unrolled loops... - if ( stride == 1 ) { - m = N % 6; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - sum += X[ i ]; - } - } - if ( N < 6 ) { - return sum; - } - for ( i = m; i < N; i += 6 ) { - sum += X[i] + X[i+1] + X[i+2] + X[i+3] + X[i+4] + X[i+5]; - } - return sum; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - sum += X[ ix ]; - ix += stride; - } - return sum; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/main.c new file mode 100644 index 000000000000..9b7cc3c820b0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/src/main.c @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dsumors.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsumors)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsumors_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the sum of double-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsumors_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT m; + CBLAS_INT i; + double sum; + + sum = 0.0; + if ( N <= 0 ) { + return sum; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * X[ ix ]; + } + // If the stride is equal to `1`, use unrolled loops... + if ( strideX == 1 ) { + m = N % 6; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + sum += X[ i ]; + } + } + if ( N < 6 ) { + return sum; + } + for ( i = m; i < N; i += 6 ) { + sum += X[i] + X[i+1] + X[i+2] + X[i+3] + X[i+4] + X[i+5]; + } + return sum; + } + for ( i = 0; i < N; i++ ) { + sum += X[ ix ]; + ix += strideX; + } + return sum; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.js index f0efe66c5128..92be3b88da26 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumors( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.native.js index 9f01b98c8b10..fb45f0c75e9d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.dsumors.native.js @@ -226,14 +226,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumors( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.js index aa96547800b5..45025df84f0f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumors( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.native.js index cf7249ed6bd2..4ce5b4c65d69 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumors/test/test.ndarray.native.js @@ -144,14 +144,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumors( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/README.md index 3c03cbc53312..a126be7b570b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/README.md @@ -36,7 +36,7 @@ limitations under the License. var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ); ``` -#### dsumpw( N, x, stride ) +#### dsumpw( N, x, strideX ) Computes the sum of double-precision floating-point strided array elements using pairwise summation. @@ -44,9 +44,8 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsumpw( N, x, 1 ); +var v = dsumpw( x.length, x, 1 ); // returns 1.0 ``` @@ -54,9 +53,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -81,7 +80,7 @@ var v = dsumpw( 4, x1, 2 ); // returns 5.0 ``` -#### dsumpw.ndarray( N, x, stride, offset ) +#### dsumpw.ndarray( N, x, strideX, offsetX ) Computes the sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. @@ -89,17 +88,16 @@ Computes the sum of double-precision floating-point strided array elements using var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsumpw.ndarray( N, x, 1, 0 ); +var v = dsumpw.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -132,11 +130,12 @@ var v = dsumpw.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = dsumpw( x.length, x, 1 ); @@ -147,8 +146,123 @@ console.log( v ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dsumpw.h" +``` + +#### stdlib_strided_dsumpw( N, \*X, strideX ) + +Computes the sum of double-precision floating-point strided array elements using pairwise summation. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + +double v = stdlib_strided_dsumpw( 4, x, 1 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsumpw( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsumpw_ndarray( N, \*X, strideX, offsetX ) + +Computes the sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + +double v = stdlib_strided_dsumpw_ndarray( 4, x, 1, 0 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsumpw_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dsumpw.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the sum: + double v = stdlib_strided_dsumpw( N, x, strideX ); + + // Print the result: + printf( "sum: %lf\n", v ); +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js index d6b22fda28af..3231547e99e7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var dsumpw = require( './../lib/dsumpw.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js index 399f150736c5..bdacaadfb4eb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var dsumpw = tryRequire( resolve( __dirname, './../lib/dsumpw.native.js' ) ); var opts = { 'skip': ( dsumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js index 0e13afde1ac7..a9d05dd1bcc5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var dsumpw = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js index fa9cd2f89840..a90174ec8898 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var dsumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float64', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/c/benchmark.length.c index acdac0386225..e9c0b0278c0f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsumpw( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsumpw_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/repl.txt index 8b39ccffff64..f692d00e51b5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of double-precision floating-point strided array elements using pairwise summation. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,7 +34,7 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > {{alias}}( 3, x, 2 ) 1.0 @@ -46,12 +46,12 @@ -1.0 -{{alias}}.ndarray( N, x, stride, offset ) +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -62,10 +62,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/types/index.d.ts index ad96f04b9f0a..3a79ebcbb953 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsumpw( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsumpw.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/c/example.c index 197ecdc1225d..50f1c83c588f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/c/example.c @@ -17,7 +17,6 @@ */ #include "stdlib/blas/ext/base/dsumpw.h" -#include #include int main( void ) { @@ -25,13 +24,13 @@ int main( void ) { const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify the stride length: - const int64_t stride = 2; + const int strideX = 2; // Compute the sum: - double v = stdlib_strided_dsumpw( N, x, stride ); + double v = stdlib_strided_dsumpw( N, x, strideX ); // Print the result: printf( "sum: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/index.js index 020cf5dbaa6c..d28c4a29005a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsumpw = require( './../lib' ); -var x = filledarrayBy( 10, 'float64', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = dsumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/include/stdlib/blas/ext/base/dsumpw.h b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/include/stdlib/blas/ext/base/dsumpw.h index 2b417b596c67..84b289f8a02d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/include/stdlib/blas/ext/base/dsumpw.h +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/include/stdlib/blas/ext/base/dsumpw.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_DSUMPW_H #define STDLIB_BLAS_EXT_BASE_DSUMPW_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the sum of double-precision floating-point strided array elements using pairwise summation. */ -double stdlib_strided_dsumpw( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsumpw)( const CBLAS_INT N, const double *X, const CBLAS_INT stride ); + +/** +* Computes the sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsumpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.js index e10415be29ba..00b5977597df 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.js @@ -20,7 +20,8 @@ // MODULES // -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,44 +39,19 @@ var sum = require( './ndarray.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumpw( N, x, 1 ); +* var v = dsumpw( x.length, x, 1 ); * // returns 1.0 */ -function dsumpw( N, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - s += x[ ix ]; - ix += stride; - } - return s; - } - return sum( N, x, stride, ix ); +function dsumpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.native.js index e713cc03bffd..55ddd3f57b4b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/dsumpw.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumpw( N, x, 1 ); +* var v = dsumpw( x.length, x, 1 ); * // returns 1.0 */ -function dsumpw( N, x, stride ) { - return addon( N, x, stride ); +function dsumpw( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/index.js index 84c585bb77b5..26a444422f4d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/index.js @@ -28,9 +28,8 @@ * var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsumpw( N, x, 1 ); +* var v = dsumpw( x.length, x, 1 ); * // returns 1.0 * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.js index c335bca94316..74f607ee325e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.js @@ -44,8 +44,8 @@ var BLOCKSIZE = 128; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -56,7 +56,7 @@ var BLOCKSIZE = 128; * var v = dsumpw( 4, x, 2, 1 ); * // returns 5.0 */ -function dsumpw( N, x, stride, offset ) { +function dsumpw( N, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -74,57 +74,57 @@ function dsumpw( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; for ( i = 0; i < N; i++ ) { s += x[ ix ]; - ix += stride; + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... s0 = x[ ix ]; - s1 = x[ ix+stride ]; - s2 = x[ ix+(2*stride) ]; - s3 = x[ ix+(3*stride) ]; - s4 = x[ ix+(4*stride) ]; - s5 = x[ ix+(5*stride) ]; - s6 = x[ ix+(6*stride) ]; - s7 = x[ ix+(7*stride) ]; - ix += 8 * stride; + s1 = x[ ix+strideX ]; + s2 = x[ ix+(2*strideX) ]; + s3 = x[ ix+(3*strideX) ]; + s4 = x[ ix+(4*strideX) ]; + s5 = x[ ix+(5*strideX) ]; + s6 = x[ ix+(6*strideX) ]; + s7 = x[ ix+(7*strideX) ]; + ix += 8 * strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { s0 += x[ ix ]; - s1 += x[ ix+stride ]; - s2 += x[ ix+(2*stride) ]; - s3 += x[ ix+(3*stride) ]; - s4 += x[ ix+(4*stride) ]; - s5 += x[ ix+(5*stride) ]; - s6 += x[ ix+(6*stride) ]; - s7 += x[ ix+(7*stride) ]; - ix += 8 * stride; + s1 += x[ ix+strideX ]; + s2 += x[ ix+(2*strideX) ]; + s3 += x[ ix+(3*strideX) ]; + s4 += x[ ix+(4*strideX) ]; + s5 += x[ ix+(5*strideX) ]; + s6 += x[ ix+(6*strideX) ]; + s7 += x[ ix+(7*strideX) ]; + ix += 8 * strideX; } // Pairwise sum the accumulators: - s = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); + s = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); // Clean-up loop... for ( i; i < N; i++ ) { s += x[ ix ]; - ix += stride; + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return dsumpw( n, x, stride, ix ) + dsumpw( N-n, x, stride, ix+(n*stride) ); + return dsumpw( n, x, strideX, ix ) + dsumpw( N-n, x, strideX, ix+(n*strideX) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.native.js index 3032e3e37ff0..33a7ec0c6a72 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './dsumpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,8 +30,8 @@ var addon = require( './dsumpw.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -44,11 +42,8 @@ var addon = require( './dsumpw.native.js' ); * var v = dsumpw( 4, x, 2, 1 ); * // returns 5.0 */ -function dsumpw( N, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - return addon( N, view, stride ); +function dsumpw( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json index 118f8b71bba9..090d0bc750de 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json @@ -28,49 +28,52 @@ { "task": "build", "src": [ - "./src/dsumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float64array" + "@stdlib/napi/argv-strided-float64array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/napi/create-double" ] }, { "task": "benchmark", "src": [ - "./src/dsumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] }, { "task": "examples", "src": [ - "./src/dsumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/addon.c index f8ef953974a2..8540c0526906 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/addon.c @@ -17,10 +17,12 @@ */ #include "stdlib/blas/ext/base/dsumpw.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" #include /** @@ -33,14 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - - napi_value v; - napi_status status = napi_create_double( env, stdlib_strided_dsumpw( N, X, stride ), &v ); - assert( status == napi_ok ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsumpw)( N, X, strideX ), v ); + return v; +} +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsumpw_ndarray)( N, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/dsumpw.c b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/dsumpw.c deleted file mode 100644 index e4710ff2c848..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/dsumpw.c +++ /dev/null @@ -1,121 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/dsumpw.h" -#include - -/** -* Computes the sum of double-precision floating-point strided array elements using pairwise summation. -* -* ## Method -* -* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. -* -* ## References -* -* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsumpw( const int64_t N, const double *X, const int64_t stride ) { - double *xp1; - double *xp2; - double sum; - int64_t ix; - int64_t M; - int64_t n; - int64_t i; - double s0; - double s1; - double s2; - double s3; - double s4; - double s5; - double s6; - double s7; - - if ( N <= 0 ) { - return 0.0; - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - sum = 0.0; - for ( i = 0; i < N; i++ ) { - sum += X[ ix ]; - ix += stride; - } - return sum; - } - // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) - if ( N <= 128 ) { - // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... - s0 = X[ ix ]; - s1 = X[ ix+stride ]; - s2 = X[ ix+(2*stride) ]; - s3 = X[ ix+(3*stride) ]; - s4 = X[ ix+(4*stride) ]; - s5 = X[ ix+(5*stride) ]; - s6 = X[ ix+(6*stride) ]; - s7 = X[ ix+(7*stride) ]; - ix += 8 * stride; - - M = N % 8; - for ( i = 8; i < N-M; i += 8 ) { - s0 += X[ ix ]; - s1 += X[ ix+stride ]; - s2 += X[ ix+(2*stride) ]; - s3 += X[ ix+(3*stride) ]; - s4 += X[ ix+(4*stride) ]; - s5 += X[ ix+(5*stride) ]; - s6 += X[ ix+(6*stride) ]; - s7 += X[ ix+(7*stride) ]; - ix += 8 * stride; - } - // Pairwise sum the accumulators: - sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); - - // Clean-up loop... - for (; i < N; i++ ) { - sum += X[ ix ]; - ix += stride; - } - return sum; - } - // Recurse by dividing by two, but avoiding non-multiples of unroll factor... - n = N / 2; - n -= n % 8; - if ( stride < 0 ) { - xp1 = (double *)X + ( (n-N)*stride ); - xp2 = (double *)X; - } else { - xp1 = (double *)X; - xp2 = (double *)X + ( n*stride ); - } - return stdlib_strided_dsumpw( n, xp1, stride ) + stdlib_strided_dsumpw( N-n, xp2, stride ); -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/main.c new file mode 100644 index 000000000000..8705d2bef5ba --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/src/main.c @@ -0,0 +1,131 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dsumpw.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the sum of double-precision floating-point strided array elements using pairwise summation. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsumpw)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsumpw_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the sum of double-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsumpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT M; + CBLAS_INT n; + CBLAS_INT i; + double sum; + double s0; + double s1; + double s2; + double s3; + double s4; + double s5; + double s6; + double s7; + + if ( N <= 0 ) { + return 0.0; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * X[ ix ]; + } + if ( N < 8 ) { + // Use simple summation... + sum = 0.0; + for ( i = 0; i < N; i++ ) { + sum += X[ ix ]; + ix += strideX; + } + return sum; + } + // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) + if ( N <= 128 ) { + // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... + s0 = X[ ix ]; + s1 = X[ ix+strideX ]; + s2 = X[ ix+(2*strideX) ]; + s3 = X[ ix+(3*strideX) ]; + s4 = X[ ix+(4*strideX) ]; + s5 = X[ ix+(5*strideX) ]; + s6 = X[ ix+(6*strideX) ]; + s7 = X[ ix+(7*strideX) ]; + ix += 8 * strideX; + + M = N % 8; + for ( i = 8; i < N-M; i += 8 ) { + s0 += X[ ix ]; + s1 += X[ ix+strideX ]; + s2 += X[ ix+(2*strideX) ]; + s3 += X[ ix+(3*strideX) ]; + s4 += X[ ix+(4*strideX) ]; + s5 += X[ ix+(5*strideX) ]; + s6 += X[ ix+(6*strideX) ]; + s7 += X[ ix+(7*strideX) ]; + ix += 8 * strideX; + } + // Pairwise sum the accumulators: + sum = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); + + // Clean-up loop... + for (; i < N; i++ ) { + sum += X[ ix ]; + ix += strideX; + } + return sum; + } + // Recurse by dividing by two, but avoiding non-multiples of unroll factor... + n = N / 2; + n -= n % 8; + return API_SUFFIX(stdlib_strided_dsumpw_ndarray)( n, X, strideX, ix ) + API_SUFFIX(stdlib_strided_dsumpw_ndarray)( N-n, X, strideX, ix+(n*strideX) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.js index f501fae3f0a1..98cbc7deacc6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.js @@ -152,14 +152,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.native.js index 146763d831a1..e0dcde9546f3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.dsumpw.native.js @@ -243,14 +243,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.js index 88753d3e7292..2f70d32873a0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.js @@ -152,14 +152,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.native.js index bda9e678287e..0875f3ee52d1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/test/test.ndarray.native.js @@ -161,14 +161,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = dsumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapx/README.md index ffb549adc4c1..86643fe3af53 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/README.md @@ -20,7 +20,7 @@ limitations under the License. # gapx -> Add a constant to each element in a strided array. +> Add a scalar constant to each element in a strided array.
@@ -30,9 +30,9 @@ limitations under the License. var gapx = require( '@stdlib/blas/ext/base/gapx' ); ``` -#### gapx( N, alpha, x, stride ) +#### gapx( N, alpha, x, strideX ) -Adds a constant `alpha` to each element in a strided array `x`. +Adds a scalar constant to each element in a strided array. ```javascript var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; @@ -46,17 +46,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **alpha**: scalar constant. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to add a constant to every other element +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; -var N = floor( x.length / 2 ); -gapx( N, 5.0, x, 2 ); +gapx( 4, 5.0, x, 2 ); // x => [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ] ``` @@ -64,23 +61,21 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial array... var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); // Create an offset view... var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length/2 ); // Add a constant to every other element... -gapx( N, 5.0, x1, 2 ); +gapx( 3, 5.0, x1, 2 ); // x0 => [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] ``` -#### gapx.ndarray( N, alpha, x, stride, offset ) +#### gapx.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant `alpha` to each element in a strided array `x` using alternative indexing semantics. +Adds a scalar constant to each element in a strided array using alternative indexing semantics. ```javascript var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; @@ -91,9 +86,9 @@ gapx.ndarray( x.length, 5.0, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of `x` +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: ```javascript var x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; @@ -124,27 +119,12 @@ gapx.ndarray( 3, 5.0, x, 1, x.length-3 ); ```javascript -var round = require( '@stdlib/math/base/special/round' ); -var randu = require( '@stdlib/random/base/randu' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapx = require( '@stdlib/blas/ext/base/gapx' ); -var rand; -var sign; -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - rand = round( randu()*100.0 ); - sign = randu(); - if ( sign < 0.5 ) { - sign = -1.0; - } else { - sign = 1.0; - } - x[ i ] = sign * rand; -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); gapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js index eeb9fd2d2718..d4731e4d1192 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapx = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapx = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js index d1c93f60cc44..cbcc4cc4a7cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapx = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapx = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/repl.txt index 9b6e81ef6745..36cee9fcedce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each element in a strided array. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each element in a strided array. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. @@ -16,52 +16,46 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. Returns ------- x: Array|TypedArray - Input array `x`. + Input array. Examples -------- // Standard Usage: - > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; - > var alpha = 5.0; - > {{alias}}( x.length, alpha, x, 1 ) - [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] + > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + > {{alias}}( x.length, 5.0, x, 1 ) + [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] - // Using `N` and `stride` parameters: - > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > alpha = 5.0; - > var stride = 2; - > {{alias}}( N, alpha, x, stride ) - [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ] + // Using `N` and stride parameters: + > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + > {{alias}}( 4, 5.0, x, 2 ) + [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > alpha = 5.0; - > stride = 2; - > {{alias}}( N, alpha, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) [ 3.0, 3.0, 1.0, 5.0, -1.0 ] > x0 [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each element in a strided array using alternative + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each element in a strided array using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -70,36 +64,32 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. - offset: integer - Starting index of `x`. + offsetX: integer + Starting index. Returns ------- x: Array|TypedArray - Input array `x`. + Input array. Examples -------- // Standard Usage: > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; - > var alpha = 5.0; - > {{alias}}.ndarray( x.length, alpha, x, 1, 0 ) + > {{alias}}.ndarray( x.length, 5.0, x, 1, 0 ) [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] // Using an index offset: > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > alpha = 5.0; - > var stride = 2; - > {{alias}}.ndarray( N, alpha, x, stride, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/types/index.d.ts index 63b99561121c..1220a61887b9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/docs/types/index.d.ts @@ -27,12 +27,12 @@ import { NumericArray } from '@stdlib/types/array'; */ interface Routine { /** - * Adds a constant to each element in a strided array. + * Adds a scalar constant to each element in a strided array. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -41,16 +41,16 @@ interface Routine { * gapx( x.length, 5.0, x, 1 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ - ( N: number, alpha: number, x: NumericArray, stride: number ): NumericArray; + ( N: number, alpha: number, x: NumericArray, strideX: number ): NumericArray; /** - * Adds a constant to each element in a strided array using alternative indexing semantics. + * Adds a scalar constant to each element in a strided array using alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns `x` * * @example @@ -59,16 +59,16 @@ interface Routine { * gapx.ndarray( x.length, 5.0, x, 1, 0 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ - ndarray( N: number, alpha: number, x: NumericArray, stride: number, offset: number ): NumericArray; + ndarray( N: number, alpha: number, x: NumericArray, strideX: number, offsetX: number ): NumericArray; } /** -* Adds a constant to each element in a strided array. +* Adds a scalar constant to each element in a strided array. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns `x` * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/examples/index.js index e144147ac6b4..f1e6691d7442 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/examples/index.js @@ -18,27 +18,12 @@ 'use strict'; -var round = require( '@stdlib/math/base/special/round' ); -var randu = require( '@stdlib/random/base/randu' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapx = require( './../lib' ); -var rand; -var sign; -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - rand = round( randu()*100.0 ); - sign = randu(); - if ( sign < 0.5 ) { - sign = -1.0; - } else { - sign = 1.0; - } - x[ i ] = sign * rand; -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); gapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/index.js index 4ae485701b92..b88896fef52e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each element in a strided array. +* Add a scalar constant to each element in a strided array. * * @module @stdlib/blas/ext/base/gapx * diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/main.js index c6533a3a4ee8..2e49212f5ff5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/main.js @@ -18,20 +18,21 @@ 'use strict'; -// VARIABLES // +// MODULES // -var M = 5; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each element in a strided array. +* Adds a scalar constant to each element in a strided array. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - scalar +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {NumericArray} input array * * @example @@ -40,46 +41,8 @@ var M = 5; * gapx( x.length, 5.0, x, 1 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ -function gapx( N, alpha, x, stride ) { - var ix; - var i; - var m; - - if ( N <= 0 || alpha === 0.0 ) { - return x; - } - // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { - m = N % M; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - x[ i ] += alpha; - } - } - if ( N < M ) { - return x; - } - for ( i = m; i < N; i += M ) { - x[ i ] += alpha; - x[ i+1 ] += alpha; - x[ i+2 ] += alpha; - x[ i+3 ] += alpha; - x[ i+4 ] += alpha; - } - return x; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - x[ ix ] += alpha; - ix += stride; - } - return x; +function gapx( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/ndarray.js index 66c3ea3ed7e7..f63d2cc6b5c8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/lib/ndarray.js @@ -26,23 +26,22 @@ var M = 5; // MAIN // /** -* Adds a constant to each element in a strided array. +* Adds a scalar constant to each element in a strided array. * * @param {PositiveInteger} N - number of indexed elements * @param {number} alpha - scalar * @param {NumericArray} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {NumericArray} input array * * @example * var x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; -* var alpha = 5.0; * -* gapx( 3, alpha, x, 1, x.length-3 ); +* gapx( 3, 5.0, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, 1.0, 10.0, -1.0 ] */ -function gapx( N, alpha, x, stride, offset ) { +function gapx( N, alpha, x, strideX, offsetX ) { var ix; var m; var i; @@ -50,17 +49,17 @@ function gapx( N, alpha, x, stride, offset ) { if ( N <= 0 || alpha === 0.0 ) { return x; } - ix = offset; + ix = offsetX; // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { + if ( strideX === 1 ) { m = N % M; // If we have a remainder, run a clean-up loop... if ( m > 0 ) { for ( i = 0; i < m; i++ ) { x[ ix ] += alpha; - ix += stride; + ix += strideX; } } if ( N < M ) { @@ -78,7 +77,7 @@ function gapx( N, alpha, x, stride, offset ) { } for ( i = 0; i < N; i++ ) { x[ ix ] += alpha; - ix += stride; + ix += strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapx/package.json b/lib/node_modules/@stdlib/blas/ext/base/gapx/package.json index b765f3cfd127..04341d9e2e35 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapx/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gapx/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gapx", "version": "0.0.0", - "description": "Add a constant to each element in a strided array.", + "description": "Add a scalar constant to each element in a strided array.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/README.md index 91beb955d3cc..2a09804a0164 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/README.md @@ -20,7 +20,7 @@ limitations under the License. # gapxsum -> Add a constant to each strided array element and compute the sum. +> Add a scalar constant to each strided array element and compute the sum.
@@ -36,15 +36,14 @@ limitations under the License. var gapxsum = require( '@stdlib/blas/ext/base/gapxsum' ); ``` -#### gapxsum( N, alpha, x, stride ) +#### gapxsum( N, alpha, x, strideX ) -Adds a constant to each strided array element and computes the sum. +Adds a scalar constant to each strided array element and computes the sum. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsum( N, 5.0, x, 1 ); +var v = gapxsum( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsum( N, 5.0, x, 2 ); +var v = gapxsum( 4, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gapxsum( N, 5.0, x1, 2 ); +var v = gapxsum( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### gapxsum.ndarray( N, alpha, x, stride, offset ) +#### gapxsum.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each strided array element and computes the sum using alternative indexing semantics. +Adds a scalar constant to each strided array element and computes the sum using alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsum.ndarray( N, 5.0, x, 1, 0 ); +var v = gapxsum.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsum.ndarray( N, 5.0, x, 2, 1 ); +var v = gapxsum.ndarray( 4, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -133,18 +122,12 @@ var v = gapxsum.ndarray( N, 5.0, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsum = require( '@stdlib/blas/ext/base/gapxsum' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js index 8885759bb849..ac39f9a0658e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsum = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsum = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js index 9a34491a54c6..e4b9855de5a4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsum = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsum = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/repl.txt index 17f721dfc8c2..a4d10ce2a372 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/repl.txt @@ -1,12 +1,12 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each strided array element and computes the sum. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each strided array element and computes the sum. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. - Indexing is relative to the first index. To introduce an offset, use a typed - array view. + Indexing is relative to the first index. To introduce an offset, use typed + array views. If `N <= 0`, the function returns `0.0`. @@ -16,13 +16,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -36,27 +36,24 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each strided array element and computes the sum using - alternative indexing semantics. + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each strided array element and computes the sum + using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,15 +62,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -90,8 +87,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/types/index.d.ts index 01534cdf182f..84712dc38355 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/docs/types/index.d.ts @@ -27,12 +27,12 @@ import { NumericArray } from '@stdlib/types/array'; */ interface Routine { /** - * Adds a constant to each strided array element and computes the sum. + * Adds a scalar constant to each strided array element and computes the sum. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -41,16 +41,16 @@ interface Routine { * var v = gapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: NumericArray, stride: number ): number; + ( N: number, alpha: number, x: NumericArray, strideX: number ): number; /** - * Adds a constant to each strided array element and computes the sum using alternative indexing semantics. + * Adds a scalar constant to each strided array element and computes the sum using alternative indexing semantics. * * @param N - number of indexed elements * @param alpha - constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = gapxsum.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each strided array element and computes the sum. +* Adds a scalar constant to each strided array element and computes the sum. * * @param N - number of indexed elements * @param alpha - constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/examples/index.js index b0b93b3a32e5..943d07945256 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsum = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/index.js index a4b3301ad72d..4ec2af9d5663 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each strided array element and compute the sum. +* Add a scalar constant to each strided array element and compute the sum. * * @module @stdlib/blas/ext/base/gapxsum * @@ -27,19 +27,16 @@ * var gapxsum = require( '@stdlib/blas/ext/base/gapxsum' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsum( N, 5.0, x, 1 ); +* var v = gapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gapxsum = require( '@stdlib/blas/ext/base/gapxsum' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsum.ndarray( N, 5.0, x, 2, 1 ); +* var v = gapxsum.ndarray( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/main.js index 2a2c8297e4f3..f649deb869c9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/main.js @@ -20,29 +20,29 @@ // MODULES // -var gapxsumkbn = require( '@stdlib/blas/ext/base/gapxsumkbn' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each strided array element and computes the sum. +* Adds a scalar constant to each strided array element and computes the sum. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsum( N, 5.0, x, 1 ); +* var v = gapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function gapxsum( N, alpha, x, stride ) { - return gapxsumkbn( N, alpha, x, stride ); +function gapxsum( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/ndarray.js index b6f097d87627..059840b83a74 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/lib/ndarray.js @@ -26,26 +26,23 @@ var gapxsumkbn = require( '@stdlib/blas/ext/base/gapxsumkbn' ).ndarray; // MAIN // /** -* Adds a constant to each strided array element and computes the sum. +* Adds a scalar constant to each strided array element and computes the sum. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsum( N, 5.0, x, 2, 1 ); +* var v = gapxsum( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function gapxsum( N, alpha, x, stride, offset ) { - return gapxsumkbn( N, alpha, x, stride, offset ); +function gapxsum( N, alpha, x, strideX, offsetX ) { + return gapxsumkbn( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/package.json b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/package.json index 0006faa3afb2..d48415a66d0a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gapxsum", "version": "0.0.0", - "description": "Add a constant to each strided array element and compute the sum.", + "description": "Add a scalar constant to each strided array element and compute the sum.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.main.js index a61dec25b508..3105c7d8c1aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.main.js @@ -140,14 +140,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsum( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.ndarray.js index 1101f6899eb3..e261c3eedc22 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsum/test/test.ndarray.js @@ -139,14 +139,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsum( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md index ef044c89548a..0dc4ff595419 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/README.md @@ -20,7 +20,7 @@ limitations under the License. # gapxsumkbn -> Add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. +> Add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.
@@ -36,15 +36,14 @@ limitations under the License. var gapxsumkbn = require( '@stdlib/blas/ext/base/gapxsumkbn' ); ``` -#### gapxsumkbn( N, alpha, x, stride ) +#### gapxsumkbn( N, alpha, x, strideX ) -Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. +Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumkbn( N, 5.0, x, 1 ); +var v = gapxsumkbn( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumkbn( N, 5.0, x, 2 ); +var v = gapxsumkbn( 4, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gapxsumkbn( N, 5.0, x1, 2 ); +var v = gapxsumkbn( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### gapxsumkbn.ndarray( N, alpha, x, stride, offset ) +#### gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. +Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumkbn.ndarray( N, 5.0, x, 1, 0 ); +var v = gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumkbn.ndarray( N, 5.0, x, 2, 1 ); +var v = gapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -133,18 +122,12 @@ var v = gapxsumkbn.ndarray( N, 5.0, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumkbn = require( '@stdlib/blas/ext/base/gapxsumkbn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.js index 42708502ed34..864505285dfd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumkbn = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumkbn = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.ndarray.js index 4d29b62d7b3d..5d7a55828086 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumkbn = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumkbn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/repl.txt index 8086546e1495..2e4ffe83a925 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each strided array element and computes the sum using an - improved Kahan–Babuška algorithm. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each strided array element and computes the sum + using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,27 +37,25 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each strided array element and computes the sum using an - improved Kahan–Babuška algorithm and alternative indexing semantics. + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each strided array element and computes the sum + using an improved Kahan–Babuška algorithm and alternative indexing + semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -66,15 +64,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -91,8 +89,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/types/index.d.ts index 1966e18c72a7..7744cc349d67 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/docs/types/index.d.ts @@ -27,12 +27,12 @@ import { NumericArray } from '@stdlib/types/array'; */ interface Routine { /** - * Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. + * Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -41,16 +41,16 @@ interface Routine { * var v = gapxsumkbn( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: NumericArray, stride: number ): number; + ( N: number, alpha: number, x: NumericArray, strideX: number ): number; /** - * Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. + * Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/examples/index.js index 50a2169217e8..a0bbd3acb496 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumkbn = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/index.js index 79bd8cb9e6c4..d5af602009d2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. +* Add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. * * @module @stdlib/blas/ext/base/gapxsumkbn * @@ -27,19 +27,16 @@ * var gapxsumkbn = require( '@stdlib/blas/ext/base/gapxsumkbn' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumkbn( N, 5.0, x, 1 ); +* var v = gapxsumkbn( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gapxsumkbn = require( '@stdlib/blas/ext/base/gapxsumkbn' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumkbn.ndarray( N, 5.0, x, 2, 1 ); +* var v = gapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/main.js index 640df2f7cf81..c0a046a3c351 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/main.js @@ -20,13 +20,14 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * ## Method * @@ -37,51 +38,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumkbn( N, 5.0, x, 1 ); +* var v = gapxsumkbn( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function gapxsumkbn( N, alpha, x, stride ) { - var sum; - var ix; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return alpha + x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - c = 0.0; - for ( i = 0; i < N; i++ ) { - v = alpha + x[ ix ]; - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c += (sum-t) + v; - } else { - c += (v-t) + sum; - } - sum = t; - ix += stride; - } - return sum + c; +function gapxsumkbn( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/ndarray.js index f532f587dd6d..1f9680fef8db 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/lib/ndarray.js @@ -26,7 +26,7 @@ var abs = require( '@stdlib/math/base/special/abs' ); // MAIN // /** -* Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * ## Method * @@ -37,22 +37,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumkbn( N, 5.0, x, 2, 1 ); +* var v = gapxsumkbn( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function gapxsumkbn( N, alpha, x, stride, offset ) { +function gapxsumkbn( N, alpha, x, strideX, offsetX ) { var sum; var ix; var v; @@ -63,10 +60,10 @@ function gapxsumkbn( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return alpha + x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * ( alpha + x[ ix ] ); } - ix = offset; sum = 0.0; c = 0.0; for ( i = 0; i < N; i++ ) { @@ -78,7 +75,7 @@ function gapxsumkbn( N, alpha, x, stride, offset ) { c += (v-t) + sum; } sum = t; - ix += stride; + ix += strideX; } return sum + c; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/package.json b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/package.json index f0751de6d487..7452c8a12612 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gapxsumkbn", "version": "0.0.0", - "description": "Add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.", + "description": "Add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.main.js index 728daede0674..c4076f2647fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.main.js @@ -140,14 +140,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumkbn( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.ndarray.js index 2d12ea8ac74e..b7ca7336b287 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn/test/test.ndarray.js @@ -139,14 +139,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumkbn( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/README.md index 5839506794d0..946ef9e829e3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/README.md @@ -20,7 +20,7 @@ limitations under the License. # gapxsumkbn2 -> Add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. +> Add a scalar constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
@@ -36,15 +36,14 @@ limitations under the License. var gapxsumkbn2 = require( '@stdlib/blas/ext/base/gapxsumkbn2' ); ``` -#### gapxsumkbn2( N, alpha, x, stride ) +#### gapxsumkbn2( N, alpha, x, strideX ) -Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumkbn2( N, 5.0, x, 1 ); +var v = gapxsumkbn2( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumkbn2( N, 5.0, x, 2 ); +var v = gapxsumkbn2( 4, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gapxsumkbn2( N, 5.0, x1, 2 ); +var v = gapxsumkbn2( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### gapxsumkbn2.ndarray( N, alpha, x, stride, offset ) +#### gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumkbn2.ndarray( N, 5.0, x, 1, 0 ); +var v = gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 ); +var v = gapxsumkbn2.ndarray( 4, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -133,18 +122,12 @@ var v = gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumkbn2 = require( '@stdlib/blas/ext/base/gapxsumkbn2' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumkbn2( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.js index 55e82cac6478..ef371725254c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumkbn2 = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumkbn2 = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.ndarray.js index 9c6070fbb786..8a4159d23f1a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumkbn2 = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumkbn2 = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/repl.txt index f69626a2c3f7..5daecc930a59 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each strided array element and computes the sum using a - second-order iterative Kahan–Babuška algorithm. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each strided array element and computes the sum + using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,28 +37,25 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each strided array element and computes the sum using a - second-order iterative Kahan–Babuška algorithm and alternative indexing - semantics. + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each strided array element and computes the sum + using a second-order iterative Kahan–Babuška algorithm and alternative + indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -67,15 +64,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -92,8 +89,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/types/index.d.ts index cad9b6abc9e4..e17d4a7be343 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/docs/types/index.d.ts @@ -27,12 +27,12 @@ import { NumericArray } from '@stdlib/types/array'; */ interface Routine { /** - * Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. + * Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -41,16 +41,16 @@ interface Routine { * var v = gapxsumkbn2( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: NumericArray, stride: number ): number; + ( N: number, alpha: number, x: NumericArray, strideX: number ): number; /** - * Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. + * Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/examples/index.js index 56408527a658..f754cf87be9f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumkbn2 = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumkbn2( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/index.js index e47ed0666fa1..3dd2b20a0ef7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. +* Add a scalar constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. * * @module @stdlib/blas/ext/base/gapxsumkbn2 * @@ -27,19 +27,16 @@ * var gapxsumkbn2 = require( '@stdlib/blas/ext/base/gapxsumkbn2' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumkbn2( N, 5.0, x, 1 ); +* var v = gapxsumkbn2( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gapxsumkbn2 = require( '@stdlib/blas/ext/base/gapxsumkbn2' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 ); +* var v = gapxsumkbn2.ndarray( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/main.js index e4523d252596..60ac0e7c0777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/main.js @@ -20,13 +20,14 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * ## Method * @@ -37,63 +38,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumkbn2( N, 5.0, x, 1 ); +* var v = gapxsumkbn2( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function gapxsumkbn2( N, alpha, x, stride ) { - var sum; - var ccs; - var ix; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return alpha + x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = alpha + x[ ix ]; - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c = (sum-t) + v; - } else { - c = (v-t) + sum; - } - sum = t; - t = cs + c; - if ( abs( cs ) >= abs( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - ix += stride; - } - return sum + cs + ccs; +function gapxsumkbn2( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/ndarray.js index 8b6947efd432..045c6ad7dc92 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/lib/ndarray.js @@ -26,7 +26,7 @@ var abs = require( '@stdlib/math/base/special/abs' ); // MAIN // /** -* Adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * ## Method * @@ -37,22 +37,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumkbn2( N, 5.0, x, 2, 1 ); +* var v = gapxsumkbn2( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function gapxsumkbn2( N, alpha, x, stride, offset ) { +function gapxsumkbn2( N, alpha, x, strideX, offsetX ) { var sum; var ccs; var ix; @@ -66,10 +63,10 @@ function gapxsumkbn2( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return alpha + x[ 0 ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * ( alpha + x[ ix ] ); } - ix = offset; sum = 0.0; ccs = 0.0; // second order correction term for lost low order bits cs = 0.0; // first order correction term for lost low order bits @@ -90,7 +87,7 @@ function gapxsumkbn2( N, alpha, x, stride, offset ) { } cs = t; ccs += cc; - ix += stride; + ix += strideX; } return sum + cs + ccs; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/package.json b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/package.json index dd38caa15a5b..0a9dfd7023eb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gapxsumkbn2", "version": "0.0.0", - "description": "Add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.", + "description": "Add a scalar constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.main.js index aca949c5845e..9eb4802bc36e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.main.js @@ -140,14 +140,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumkbn2( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.ndarray.js index 6c1e0eaf6b88..1f7bf25a6f4d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumkbn2/test/test.ndarray.js @@ -139,14 +139,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumkbn2( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/README.md index a79be6a84319..7c6b99ebe5af 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/README.md @@ -20,7 +20,7 @@ limitations under the License. # gapxsumors -> Add a constant to each strided array element and compute the sum using ordinary recursive summation. +> Add a scalar constant to each strided array element and compute the sum using ordinary recursive summation.
@@ -36,15 +36,14 @@ limitations under the License. var gapxsumors = require( '@stdlib/blas/ext/base/gapxsumors' ); ``` -#### gapxsumors( N, alpha, x, stride ) +#### gapxsumors( N, alpha, x, strideX ) -Adds a constant to each strided array element and computes the sum using ordinary recursive summation. +Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumors( N, 5.0, x, 1 ); +var v = gapxsumors( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumors( N, 5.0, x, 2 ); +var v = gapxsumors( 4, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gapxsumors( N, 5.0, x1, 2 ); +var v = gapxsumors( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### gapxsumors.ndarray( N, alpha, x, stride, offset ) +#### gapxsumors.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. +Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumors.ndarray( N, 5.0, x, 1, 0 ); +var v = gapxsumors.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumors.ndarray( N, 5.0, x, 2, 1 ); +var v = gapxsumors.ndarray( 4, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -134,18 +123,12 @@ var v = gapxsumors.ndarray( N, 5.0, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumors = require( '@stdlib/blas/ext/base/gapxsumors' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumors( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js index f44aa320d8b2..8884e5a6381a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumors = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumors = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js index 64d4e7fd4df1..68402416b5aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/repl.txt index ed12670ff1de..10e7c551114c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each strided array element and computes the sum using - ordinary recursive summation. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each strided array element and computes the sum + using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,27 +37,24 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each strided array element and computes the sum using - ordinary recursive summation and alternative indexing semantics. + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each strided array element and computes the sum + using ordinary recursive summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -66,15 +63,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -91,8 +88,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/types/index.d.ts index b5dd156bb983..b75a10f3e60f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/docs/types/index.d.ts @@ -27,12 +27,12 @@ import { NumericArray } from '@stdlib/types/array'; */ interface Routine { /** - * Adds a constant to each strided array element and computes the sum using ordinary recursive summation. + * Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -41,16 +41,16 @@ interface Routine { * var v = gapxsumors( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: NumericArray, stride: number ): number; + ( N: number, alpha: number, x: NumericArray, strideX: number ): number; /** - * Adds a constant to each strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. + * Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = gapxsumors.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/examples/index.js index 07f86556ab1b..8410c2ca8431 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumors = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumors( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/index.js index a70c48f27988..0ab8269f877f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each strided array element and compute the sum using ordinary recursive summation. +* Add a scalar constant to each strided array element and compute the sum using ordinary recursive summation. * * @module @stdlib/blas/ext/base/gapxsumors * @@ -27,19 +27,16 @@ * var gapxsumors = require( '@stdlib/blas/ext/base/gapxsumors' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumors( N, 5.0, x, 1 ); +* var v = gapxsumors( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gapxsumors = require( '@stdlib/blas/ext/base/gapxsumors' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumors.ndarray( N, 5.0, x, 2, 1 ); +* var v = gapxsumors.ndarray( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/main.js index 383768ea5dd9..cf0608e0d8f6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/main.js @@ -18,46 +18,31 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** -* Adds a constant to each strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumors( N, 5.0, x, 1 ); +* var v = gapxsumors( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function gapxsumors( N, alpha, x, stride ) { - var sum; - var ix; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return alpha + x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - for ( i = 0; i < N; i++ ) { - sum += alpha + x[ ix ]; - ix += stride; - } - return sum; +function gapxsumors( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/ndarray.js index dcc55d4082f5..f12eff019fbb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/lib/ndarray.js @@ -21,25 +21,22 @@ // MAIN // /** -* Adds a constant to each strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each strided array element and computes the sum using ordinary recursive summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumors( N, 5.0, x, 2, 1 ); +* var v = gapxsumors( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function gapxsumors( N, alpha, x, stride, offset ) { +function gapxsumors( N, alpha, x, strideX, offsetX ) { var sum; var ix; var i; @@ -47,14 +44,14 @@ function gapxsumors( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return alpha + x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * ( alpha + x[ ix ] ); } - ix = offset; sum = 0.0; for ( i = 0; i < N; i++ ) { sum += alpha + x[ ix ]; - ix += stride; + ix += strideX; } return sum; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/package.json b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/package.json index 9fc5d2d92216..2c84a5937479 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gapxsumors", "version": "0.0.0", - "description": "Add a constant to each strided array element and compute the sum using ordinary recursive summation.", + "description": "Add a scalar constant to each strided array element and compute the sum using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.main.js index 6282fefc209d..5e5f5a33f797 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.main.js @@ -140,14 +140,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumors( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.ndarray.js index b94a3e501a36..1ee4065a41fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumors/test/test.ndarray.js @@ -139,14 +139,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumors( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/README.md index 59b57d225f79..4f11f7b8c11c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/README.md @@ -20,7 +20,7 @@ limitations under the License. # gapxsumpw -> Add a constant to each strided array element and compute the sum using pairwise summation. +> Add a scalar constant to each strided array element and compute the sum using pairwise summation.
@@ -36,15 +36,14 @@ limitations under the License. var gapxsumpw = require( '@stdlib/blas/ext/base/gapxsumpw' ); ``` -#### gapxsumpw( N, alpha, x, stride ) +#### gapxsumpw( N, alpha, x, strideX ) -Adds a constant to each strided array element and computes the sum using pairwise summation. +Adds a scalar constant to each strided array element and computes the sum using pairwise summation. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumpw( N, 5.0, x, 1 ); +var v = gapxsumpw( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumpw( N, 5.0, x, 2 ); +var v = gapxsumpw( 4, 5.0, x, 2 ); // returns 25.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gapxsumpw( N, 5.0, x1, 2 ); +var v = gapxsumpw( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### gapxsumpw.ndarray( N, alpha, x, stride, offset ) +#### gapxsumpw.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each strided array element and computes the sum using pairwise summation and alternative indexing semantics. +Adds a scalar constant to each strided array element and computes the sum using pairwise summation and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gapxsumpw.ndarray( N, 5.0, x, 1, 0 ); +var v = gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gapxsumpw.ndarray( N, 5.0, x, 2, 1 ); +var v = gapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); // returns 25.0 ``` @@ -134,18 +123,12 @@ var v = gapxsumpw.ndarray( N, 5.0, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumpw = require( '@stdlib/blas/ext/base/gapxsumpw' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumpw( x.length, 5.0, x, 1 ); @@ -176,10 +159,10 @@ console.log( v ); ## See Also -- [`@stdlib/blas/ext/base/dapxsumpw`][@stdlib/blas/ext/base/dapxsumpw]: adds a constant to each double-precision floating-point strided array element and computes the sum using pairwise summation. -- [`@stdlib/blas/ext/base/gapxsum`][@stdlib/blas/ext/base/gapxsum]: adds a constant to each strided array element and computes the sum. +- [`@stdlib/blas/ext/base/dapxsumpw`][@stdlib/blas/ext/base/dapxsumpw]: add a scalar constant to each double-precision floating-point strided array element and compute the sum using pairwise summation. +- [`@stdlib/blas/ext/base/gapxsum`][@stdlib/blas/ext/base/gapxsum]: add a scalar constant to each strided array element and compute the sum. - [`@stdlib/blas/ext/base/gsumpw`][@stdlib/blas/ext/base/gsumpw]: calculate the sum of strided array elements using pairwise summation. -- [`@stdlib/blas/ext/base/sapxsumpw`][@stdlib/blas/ext/base/sapxsumpw]: adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +- [`@stdlib/blas/ext/base/sapxsumpw`][@stdlib/blas/ext/base/sapxsumpw]: add a scalar constant to each single-precision floating-point strided array element and compute the sum using pairwise summation.
diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js index 3c710d05a949..64cc580ff61c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumpw = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumpw = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js index 9e569679a088..fbc1487ee865 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gapxsumpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gapxsumpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/repl.txt index b99c648f572c..18cb55bc324d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each strided array element and computes the sum using - pairwise summation. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each strided array element and computes the sum + using pairwise summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,27 +37,24 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each strided array element and computes the sum using - pairwise summation and alternative indexing semantics. + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each strided array element and computes the sum + using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -66,15 +63,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -91,8 +88,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/types/index.d.ts index 5941546c17f3..a31b1a049578 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/docs/types/index.d.ts @@ -27,12 +27,12 @@ import { NumericArray } from '@stdlib/types/array'; */ interface Routine { /** - * Adds a constant to each strided array element and computes the sum using pairwise summation. + * Adds a scalar constant to each strided array element and computes the sum using pairwise summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -41,16 +41,16 @@ interface Routine { * var v = gapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: NumericArray, stride: number ): number; + ( N: number, alpha: number, x: NumericArray, strideX: number ): number; /** - * Adds a constant to each strided array element and computes the sum using pairwise summation and alternative indexing semantics. + * Adds a scalar constant to each strided array element and computes the sum using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each strided array element and computes the sum using pairwise summation. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/examples/index.js index 6cd2f4972201..4e70e384d243 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gapxsumpw = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gapxsumpw( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/index.js index 0e51f2493dfb..ed2ab1529371 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each strided array element and compute the sum using pairwise summation. +* Add a scalar constant to each strided array element and compute the sum using pairwise summation. * * @module @stdlib/blas/ext/base/gapxsumpw * @@ -27,19 +27,16 @@ * var gapxsumpw = require( '@stdlib/blas/ext/base/gapxsumpw' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumpw( N, 5.0, x, 1 ); +* var v = gapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gapxsumpw = require( '@stdlib/blas/ext/base/gapxsumpw' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumpw.ndarray( N, 5.0, x, 2, 1 ); +* var v = gapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/main.js index e961348295f4..bd1bf98b6b42 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/main.js @@ -20,13 +20,14 @@ // MODULES // -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each strided array element and computes the sum using pairwise summation. * * ## Method * @@ -37,44 +38,19 @@ var sum = require( './ndarray.js' ); * - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gapxsumpw( N, 5.0, x, 1 ); +* var v = gapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function gapxsumpw( N, alpha, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return alpha + x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - s += alpha + x[ ix ]; - ix += stride; - } - return s; - } - return sum( N, alpha, x, stride, ix ); +function gapxsumpw( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/ndarray.js index 84399ffb95b3..d22debfff295 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/lib/ndarray.js @@ -32,7 +32,7 @@ var BLOCKSIZE = 128; // MAIN // /** -* Adds a constant to each strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each strided array element and computes the sum using pairwise summation. * * ## Method * @@ -43,22 +43,19 @@ var BLOCKSIZE = 128; * - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gapxsumpw( N, 5.0, x, 2, 1 ); +* var v = gapxsumpw( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function gapxsumpw( N, alpha, x, stride, offset ) { +function gapxsumpw( N, alpha, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -76,57 +73,57 @@ function gapxsumpw( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return alpha + x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * ( alpha + x[ ix ] ); } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; for ( i = 0; i < N; i++ ) { s += alpha + x[ ix ]; - ix += stride; + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... s0 = alpha + x[ ix ]; - s1 = alpha + x[ ix+stride ]; - s2 = alpha + x[ ix+(2*stride) ]; - s3 = alpha + x[ ix+(3*stride) ]; - s4 = alpha + x[ ix+(4*stride) ]; - s5 = alpha + x[ ix+(5*stride) ]; - s6 = alpha + x[ ix+(6*stride) ]; - s7 = alpha + x[ ix+(7*stride) ]; - ix += 8 * stride; + s1 = alpha + x[ ix+strideX ]; + s2 = alpha + x[ ix+(2*strideX) ]; + s3 = alpha + x[ ix+(3*strideX) ]; + s4 = alpha + x[ ix+(4*strideX) ]; + s5 = alpha + x[ ix+(5*strideX) ]; + s6 = alpha + x[ ix+(6*strideX) ]; + s7 = alpha + x[ ix+(7*strideX) ]; + ix += 8 * strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { s0 += alpha + x[ ix ]; - s1 += alpha + x[ ix+stride ]; - s2 += alpha + x[ ix+(2*stride) ]; - s3 += alpha + x[ ix+(3*stride) ]; - s4 += alpha + x[ ix+(4*stride) ]; - s5 += alpha + x[ ix+(5*stride) ]; - s6 += alpha + x[ ix+(6*stride) ]; - s7 += alpha + x[ ix+(7*stride) ]; - ix += 8 * stride; + s1 += alpha + x[ ix+strideX ]; + s2 += alpha + x[ ix+(2*strideX) ]; + s3 += alpha + x[ ix+(3*strideX) ]; + s4 += alpha + x[ ix+(4*strideX) ]; + s5 += alpha + x[ ix+(5*strideX) ]; + s6 += alpha + x[ ix+(6*strideX) ]; + s7 += alpha + x[ ix+(7*strideX) ]; + ix += 8 * strideX; } // Pairwise sum the accumulators: - s = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); + s = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); // Clean-up loop... for ( i; i < N; i++ ) { s += alpha + x[ ix ]; - ix += stride; + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return gapxsumpw( n, alpha, x, stride, ix ) + gapxsumpw( N-n, alpha, x, stride, ix+(n*stride) ); // eslint-disable-line max-len + return gapxsumpw( n, alpha, x, strideX, ix ) + gapxsumpw( N-n, alpha, x, strideX, ix+(n*strideX) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/package.json b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/package.json index 01a8549e8771..ef64511038c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gapxsumpw", "version": "0.0.0", - "description": "Add a constant to each strided array element and compute the sum using pairwise summation.", + "description": "Add a scalar constant to each strided array element and compute the sum using pairwise summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.main.js index af26c87982cc..b632213c42a0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.main.js @@ -148,14 +148,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumpw( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.ndarray.js index c16425e6b932..074753c77cda 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gapxsumpw/test/test.ndarray.js @@ -147,14 +147,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gapxsumpw( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/README.md index 5aee47372758..85affbbbdbe2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/README.md @@ -51,7 +51,7 @@ The [_L1_ norm][l1norm] is defined as var gasumpw = require( '@stdlib/blas/ext/base/gasumpw' ); ``` -#### gasumpw( N, x, stride ) +#### gasumpw( N, x, strideX ) Computes the sum of absolute values ([_L1_ norm][l1norm]) of strided array elements using pairwise summation. @@ -66,17 +66,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of absolute values of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gasumpw( N, x, 2 ); +var v = gasumpw( 4, x, 2 ); // returns 9.0 ``` @@ -86,18 +83,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gasumpw( N, x1, 2 ); +var v = gasumpw( 4, x1, 2 ); // returns 9.0 ``` -#### gasumpw.ndarray( N, x, stride, offset ) +#### gasumpw.ndarray( N, x, strideX, offsetX ) Computes the sum of absolute values ([_L1_ norm][l1norm]) of strided array elements using pairwise summation and alternative indexing semantics. @@ -110,17 +104,14 @@ var v = gasumpw.ndarray( x.length, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gasumpw.ndarray( N, x, 2, 1 ); +var v = gasumpw.ndarray( 4, x, 2, 1 ); // returns 9.0 ``` @@ -147,18 +138,12 @@ var v = gasumpw.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gasumpw = require( '@stdlib/blas/ext/base/gasumpw' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gasumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js index 3e7d5701555e..031effd504e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gasumpw = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gasumpw = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js index 12f2f54bbb2a..168961466f27 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gasumpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gasumpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/repl.txt index 8583ca8b2314..fa7ba9062114 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of absolute values (L1 norm) of strided array elements using pairwise summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,27 +34,24 @@ > {{alias}}( x.length, x, 1 ) 5.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 5.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) 5.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of absolute values (L1 norm) of strided array elements using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 5.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/types/index.d.ts index bf08c8d03c77..783274e040b6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gasumpw( x.length, x, 1 ); * // returns 5.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of absolute values (L1 norm) of strided array elements using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gasumpw.ndarray( x.length, x, 1, 0 ); * // returns 5.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/examples/index.js index c0fe41dcf24c..8c0a902bdc2e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gasumpw = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gasumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/index.js index faa8afe8bbb8..911e670b4599 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/index.js @@ -32,13 +32,11 @@ * // returns 5.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gasumpw = require( '@stdlib/blas/ext/base/gasumpw' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gasumpw.ndarray( N, x, 2, 1 ); +* var v = gasumpw.ndarray( 4, x, 2, 1 ); * // returns 9.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/main.js index 61049f1f182a..0a44a735b7bc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,7 +39,7 @@ var sum = require( './ndarray.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example @@ -48,32 +48,8 @@ var sum = require( './ndarray.js' ); * var v = gasumpw( x.length, x, 1 ); * // returns 5.0 */ -function gasumpw( N, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return abs( x[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - s += abs( x[ ix ] ); - ix += stride; - } - return s; - } - return sum( N, x, stride, ix ); +function gasumpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/ndarray.js index e6e6ddd476c5..310df05fb9b0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/lib/ndarray.js @@ -45,20 +45,17 @@ var BLOCKSIZE = 128; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gasumpw( N, x, 2, 1 ); +* var v = gasumpw( 4, x, 2, 1 ); * // returns 9.0 */ -function gasumpw( N, x, stride, offset ) { +function gasumpw( N, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -76,57 +73,57 @@ function gasumpw( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return abs( x[ offset ] ); + ix = offsetX; + if ( strideX === 0 ) { + return N * ( abs( x[ix] ) ); } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; for ( i = 0; i < N; i++ ) { s += abs( x[ ix ] ); - ix += stride; + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... s0 = abs( x[ ix ] ); - s1 = abs( x[ ix+stride ] ); - s2 = abs( x[ ix+(2*stride) ] ); - s3 = abs( x[ ix+(3*stride) ] ); - s4 = abs( x[ ix+(4*stride) ] ); - s5 = abs( x[ ix+(5*stride) ] ); - s6 = abs( x[ ix+(6*stride) ] ); - s7 = abs( x[ ix+(7*stride) ] ); - ix += 8 * stride; + s1 = abs( x[ ix+strideX ] ); + s2 = abs( x[ ix+(2*strideX) ] ); + s3 = abs( x[ ix+(3*strideX) ] ); + s4 = abs( x[ ix+(4*strideX) ] ); + s5 = abs( x[ ix+(5*strideX) ] ); + s6 = abs( x[ ix+(6*strideX) ] ); + s7 = abs( x[ ix+(7*strideX) ] ); + ix += 8 * strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { s0 += abs( x[ ix ] ); - s1 += abs( x[ ix+stride ] ); - s2 += abs( x[ ix+(2*stride) ] ); - s3 += abs( x[ ix+(3*stride) ] ); - s4 += abs( x[ ix+(4*stride) ] ); - s5 += abs( x[ ix+(5*stride) ] ); - s6 += abs( x[ ix+(6*stride) ] ); - s7 += abs( x[ ix+(7*stride) ] ); - ix += 8 * stride; + s1 += abs( x[ ix+strideX ] ); + s2 += abs( x[ ix+(2*strideX) ] ); + s3 += abs( x[ ix+(3*strideX) ] ); + s4 += abs( x[ ix+(4*strideX) ] ); + s5 += abs( x[ ix+(5*strideX) ] ); + s6 += abs( x[ ix+(6*strideX) ] ); + s7 += abs( x[ ix+(7*strideX) ] ); + ix += 8 * strideX; } // Pairwise sum the accumulators: - s = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); + s = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); // Clean-up loop... for ( i; i < N; i++ ) { s += abs( x[ ix ] ); - ix += stride; + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return gasumpw( n, x, stride, ix ) + gasumpw( N-n, x, stride, ix+(n*stride) ); // eslint-disable-line max-len + return gasumpw( n, x, strideX, ix ) + gasumpw( N-n, x, strideX, ix+(n*strideX) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.main.js index 615be9289d7f..c220a3a7b5db 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.main.js @@ -157,14 +157,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gasumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.ndarray.js index bac41dce68f3..001032894b27 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gasumpw/test/test.ndarray.js @@ -156,14 +156,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gasumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/README.md b/lib/node_modules/@stdlib/blas/ext/base/gcusum/README.md index 072bdd52f4e9..407f8da6f29a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/README.md @@ -59,21 +59,17 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -var v = gcusum( N, 0.0, x, 2, y, 1 ); +var v = gcusum( 4, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,7 +79,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -93,9 +88,7 @@ var y0 = new Float64Array( x0.length ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -var N = floor( x0.length / 2 ); - -gcusum( N, 0.0, x1, -2, y1, 1 ); +gcusum( 4, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -116,17 +109,13 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element in the strided input array starting from the second element and to store in the last `N` elements of the strided output array starting from the last element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); +gcusum.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -152,20 +141,14 @@ gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusum = require( '@stdlib/blas/ext/base/gcusum' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.js index 77506e349178..afbae7937d09 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusum = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusum = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.ndarray.js index 17fa4ebd3cd0..0f3d84c1d643 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/benchmark/benchmark.ndarray.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusum = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusum = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/repl.txt index 4de7e9c5c4b5..269232641429 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/repl.txt @@ -2,8 +2,8 @@ {{alias}}( N, sum, x, strideX, y, strideY ) Computes the cumulative sum of strided array elements. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,13 +22,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Array|TypedArray Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -43,11 +43,10 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 0.0, x, 2, y, 2 ) + > {{alias}}( 3, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -55,19 +54,19 @@ > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] + {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of strided array elements using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -81,7 +80,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -90,7 +89,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -106,14 +105,13 @@ > var x = [ 1.0, -2.0, 2.0 ]; > var y = [ 0.0, 0.0, 0.0 ]; > {{alias}}.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ) - [ 1.0, -1.0, 1.0 ] + [ 1.0, -1.0, 1.0 ] // Advanced indexing: > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) - [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] + > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/types/index.d.ts index 9e7eedcd66d1..4cac18e67988 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/docs/types/index.d.ts @@ -32,9 +32,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -52,10 +52,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusum/examples/index.js index 06a3950f14e8..f7af9b58d875 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusum = require( './../lib' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/index.js index f0d62888ee69..0771fda9a67c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/index.js @@ -38,9 +38,8 @@ * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusum.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusum.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/main.js index 1f51cd6bca57..d5ef736a75d1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var gcusumkbn = require( '@stdlib/blas/ext/base/gcusumkbn' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,9 +32,9 @@ var gcusumkbn = require( '@stdlib/blas/ext/base/gcusumkbn' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {NumericArray} output array * * @example @@ -44,7 +45,9 @@ var gcusumkbn = require( '@stdlib/blas/ext/base/gcusumkbn' ); * // returns [ 1.0, -1.0, 1.0 ] */ function gcusum( N, sum, x, strideX, y, strideY ) { - return gcusumkbn( N, sum, x, strideX, y, strideY ); + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, sum, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/ndarray.js index 3e2f15ba2b57..e9dad6d1f71a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusum/lib/ndarray.js @@ -31,21 +31,18 @@ var gcusumkbn = require( '@stdlib/blas/ext/base/gcusumkbn' ).ndarray; * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {NumericArray} output array * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusum( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusum( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function gcusum( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/README.md index a1212ae6b0d5..f7d91d8a1853 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/README.md @@ -59,21 +59,17 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -var v = gcusumkbn( N, 0.0, x, 2, y, 1 ); +var v = gcusumkbn( 4, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,7 +79,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -93,9 +88,7 @@ var y0 = new Float64Array( x0.length ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -var N = floor( x0.length / 2 ); - -gcusumkbn( N, 0.0, x1, -2, y1, 1 ); +gcusumkbn( 4, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -116,17 +109,13 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element in the strided input array starting from the second element and to store in the last `N` elements of the strided output array starting from the last element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); +gcusumkbn.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -152,20 +141,15 @@ gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumkbn = require( '@stdlib/blas/ext/base/gcusumkbn' ); -var y; -var x; -var i; +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js index e284a3506fa9..593979631297 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var gcusumkbn = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumkbn = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js index 0be383435519..26974b7cc027 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/benchmark/benchmark.ndarray.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var gcusumkbn = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumkbn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/repl.txt index 0c379f4f9bff..9dad6dd9f89f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of strided array elements using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Array|TypedArray Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -44,11 +44,10 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 0.0, x, 2, y, 2 ) + > {{alias}}( 3, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -56,19 +55,19 @@ > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] + {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -82,7 +81,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -91,7 +90,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -112,8 +111,7 @@ // Advanced indexing: > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) + > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/types/index.d.ts index eb821d4a5fa7..03a5c842cccc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/docs/types/index.d.ts @@ -32,9 +32,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -52,10 +52,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/examples/index.js index 557a1316954c..9f7dcf49da63 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/examples/index.js @@ -18,20 +18,15 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumkbn = require( './../lib' ); -var y; -var x; -var i; +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/index.js index 2131bbb3829f..5445901e9261 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/index.js @@ -33,14 +33,12 @@ * // y => [ 1.0, -1.0, 1.0 ] * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gcusumkbn = require( '@stdlib/blas/ext/base/gcusumkbn' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumkbn.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/main.js index 6270d431ae02..03ff7b8bdd55 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,9 +40,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {NumericArray} output array * * @example @@ -52,43 +53,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * // returns [ 1.0, -1.0, 1.0 ] */ function gcusumkbn( N, sum, x, strideX, y, strideY ) { - var ix; - var iy; - var s; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - s = sum; - c = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = s + v; - if ( abs( s ) >= abs( v ) ) { - c += (s-t) + v; - } else { - c += (v-t) + s; - } - s = t; - y[ iy ] = s + c; - ix += strideX; - iy += strideY; - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, sum, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/ndarray.js index 65064a686467..346e4d33317f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn/lib/ndarray.js @@ -39,21 +39,18 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {NumericArray} output array * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumkbn( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumkbn( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function gcusumkbn( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/README.md index 7a662798cd91..d91a5a5af5e2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/README.md @@ -59,21 +59,17 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -var v = gcusumkbn2( N, 0.0, x, 2, y, 1 ); +var v = gcusumkbn2( 4, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,7 +79,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -93,9 +88,7 @@ var y0 = new Float64Array( x0.length ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -var N = floor( x0.length / 2 ); - -gcusumkbn2( N, 0.0, x1, -2, y1, 1 ); +gcusumkbn2( 4, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -116,17 +109,13 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element in the strided input array starting from the second element and to store in the last `N` elements of the strided output array starting from the last element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); +gcusumkbn2.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -152,20 +141,14 @@ gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumkbn2 = require( '@stdlib/blas/ext/base/gcusumkbn2' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js index f2df7232bb92..ea7e0232ceaa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusumkbn2 = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumkbn2 = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js index b1d8df7fedfa..f13401fd9831 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/benchmark/benchmark.ndarray.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusumkbn2 = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumkbn2 = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/repl.txt index cb80f70df98a..2b273b222e27 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Array|TypedArray Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -44,11 +44,10 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 0.0, x, 2, y, 2 ) + > {{alias}}( 3, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -56,19 +55,19 @@ > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] + {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -82,7 +81,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -91,7 +90,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -107,14 +106,13 @@ > var x = [ 1.0, -2.0, 2.0 ]; > var y = [ 0.0, 0.0, 0.0 ]; > {{alias}}.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ) - [ 1.0, -1.0, 1.0 ] + [ 1.0, -1.0, 1.0 ] // Advanced indexing: > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) - [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] + > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/types/index.d.ts index 773d9f71b0f0..d295706b2420 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/docs/types/index.d.ts @@ -32,9 +32,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -52,10 +52,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/examples/index.js index cd0693af2302..96a82104dc63 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumkbn2 = require( './../lib' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/index.js index 8c841ac321b8..d7bb8be5eb8a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/index.js @@ -33,14 +33,12 @@ * // y => [ 1.0, -1.0, 1.0 ] * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gcusumkbn2 = require( '@stdlib/blas/ext/base/gcusumkbn2' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumkbn2.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/main.js index e2ef6a26c249..2ba2615da8f8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,9 +40,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {NumericArray} output array * * @example @@ -52,54 +53,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * // returns [ 1.0, -1.0, 1.0 ] */ function gcusumkbn2( N, sum, x, strideX, y, strideY ) { - var ccs; - var ix; - var iy; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c = (sum-t) + v; - } else { - c = (v-t) + sum; - } - sum = t; - t = cs + c; - if ( abs( cs ) >= abs( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - - y[ iy ] = sum + cs + ccs; - ix += strideX; - iy += strideY; - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, sum, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/ndarray.js index d027b1a83ac2..762d2127c58b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumkbn2/lib/ndarray.js @@ -39,21 +39,18 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {NumericArray} output array * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumkbn2( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumkbn2( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function gcusumkbn2( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/README.md index 6e308f32fa16..db158d4d278d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/README.md @@ -59,21 +59,17 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -var v = gcusumors( N, 0.0, x, 2, y, 1 ); +var v = gcusumors( 4, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,7 +79,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -93,9 +88,7 @@ var y0 = new Float64Array( x0.length ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -var N = floor( x0.length / 2 ); - -gcusumors( N, 0.0, x1, -2, y1, 1 ); +gcusumors( 4, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -116,17 +109,13 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element in the strided input array starting from the second element and to store in the last `N` elements of the strided output array starting from the last element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); +gcusumors.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -153,20 +142,14 @@ gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumors = require( '@stdlib/blas/ext/base/gcusumors' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js index eda927c462f3..dff253b7b838 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusumors = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumors = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js index 1eced635eed1..f601f47fbb80 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/benchmark/benchmark.ndarray.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusumors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/repl.txt index 939326f94081..3169844d5d68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of strided array elements using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Array|TypedArray Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -44,11 +44,10 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 0.0, x, 2, y, 2 ) + > {{alias}}( 3, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -56,19 +55,19 @@ > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] + {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of strided array elements using ordinary recursive summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -82,7 +81,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -91,7 +90,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -107,14 +106,13 @@ > var x = [ 1.0, -2.0, 2.0 ]; > var y = [ 0.0, 0.0, 0.0 ]; > {{alias}}.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ) - [ 1.0, -1.0, 1.0 ] + [ 1.0, -1.0, 1.0 ] // Advanced indexing: > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) - [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] + > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/types/index.d.ts index 660216be4cee..2293d86f9e0a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/docs/types/index.d.ts @@ -32,9 +32,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -52,10 +52,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/examples/index.js index b7a3aeb1d242..c796ff223c18 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumors = require( './../lib' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/index.js index 5da055078314..40e535d1bee4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/index.js @@ -33,14 +33,12 @@ * // y => [ 1.0, -1.0, 1.0 ] * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gcusumors = require( '@stdlib/blas/ext/base/gcusumors' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumors.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumors.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/main.js index d2bb4f993871..8b02f86fd222 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/main.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -26,9 +32,9 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {NumericArray} output array * * @example @@ -39,30 +45,9 @@ * // returns [ 1.0, -1.0, 1.0 ] */ function gcusumors( N, sum, x, strideX, y, strideY ) { - var ix; - var iy; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - for ( i = 0; i < N; i++ ) { - sum += x[ ix ]; - y[ iy ] = sum; - ix += strideX; - iy += strideY; - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, sum, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/ndarray.js index 1c30e219b977..6ccc85c6392e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumors/lib/ndarray.js @@ -26,21 +26,18 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {NumericArray} output array * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumors( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumors( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function gcusumors( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/README.md index dd4c707a395e..d440bee86270 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/README.md @@ -59,21 +59,17 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -var v = gcusumpw( N, 0.0, x, 2, y, 1 ); +var v = gcusumpw( 4, 0.0, x, 2, y, 1 ); // y => [ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] ``` @@ -83,7 +79,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial arrays... var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); @@ -93,9 +88,7 @@ var y0 = new Float64Array( x0.length ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element -var N = floor( x0.length / 2 ); - -gcusumpw( N, 0.0, x1, -2, y1, 1 ); +gcusumpw( 4, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` @@ -116,17 +109,13 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element in the strided input array starting from the second element and to store in the last `N` elements of the strided output array starting from the last element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -var N = floor( x.length / 2 ); - -gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); +gcusumpw.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ``` @@ -153,20 +142,14 @@ gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumpw = require( '@stdlib/blas/ext/base/gcusumpw' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js index c491c0a3ebf4..149f9e0a7c29 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusumpw = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumpw = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js index e659b738022c..e86f62a2888d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/benchmark/benchmark.ndarray.js @@ -21,14 +21,22 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var zeros = require( '@stdlib/array/zeros' ); var pkg = require( './../package.json' ).name; var gcusumpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -39,16 +47,8 @@ var gcusumpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = []; - y = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - y.push( 0.0 ); - } + var x = uniform( len, -100, 100, options ); + var y = zeros( len, options.dtype ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/repl.txt index bd21e4402526..0f17bb5a27fe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of strided array elements using pairwise summation. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Array|TypedArray Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -44,11 +44,10 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 0.0, x, 2, y, 2 ) + > {{alias}}( 3, 0.0, x, 2, y, 2 ) [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -56,19 +55,19 @@ > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] + {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of strided array elements using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -82,7 +81,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -91,7 +90,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -107,14 +106,13 @@ > var x = [ 1.0, -2.0, 2.0 ]; > var y = [ 0.0, 0.0, 0.0 ]; > {{alias}}.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ) - [ 1.0, -1.0, 1.0 ] + [ 1.0, -1.0, 1.0 ] // Advanced indexing: > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ) - [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] + > {{alias}}.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 ) + [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/types/index.d.ts index 4d0f899b3f8d..b020bdf932f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/docs/types/index.d.ts @@ -32,9 +32,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -52,10 +52,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/examples/index.js index 2016694832eb..89cdf6a1784d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var gcusumpw = require( './../lib' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var y = new Float64Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/index.js index 11d05f1d7c18..4c370143c183 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/index.js @@ -33,12 +33,10 @@ * // y => [ 1.0, -1.0, 1.0 ] * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gcusumpw = require( '@stdlib/blas/ext/base/gcusumpw' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * * gcusumpw.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/main.js index 2c55cd977042..da9687412d34 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var cusum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,9 +40,9 @@ var cusum = require( './ndarray.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {NumericArray} output array * * @example @@ -52,23 +53,9 @@ var cusum = require( './ndarray.js' ); * // returns [ 1.0, -1.0, 1.0 ] */ function gcusumpw( N, sum, x, strideX, y, strideY ) { - var ix; - var iy; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - return cusum( N, sum, x, strideX, ix, y, strideY, iy ); + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, sum, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/ndarray.js index e15c065af56f..a8ddbf1fc7b4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gcusumpw/lib/ndarray.js @@ -45,21 +45,18 @@ var BLOCKSIZE = 128; * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {NumericArray} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {NumericArray} output array * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; * var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; -* var N = floor( x.length / 2 ); * -* gcusumpw( N, 0.0, x, 2, 1, y, 1, 0 ); +* gcusumpw( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function gcusumpw( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/README.md index 47f81ebe3805..bc2f09f11a9e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/README.md @@ -30,9 +30,9 @@ limitations under the License. var gfillBy = require( '@stdlib/blas/ext/base/gfill-by' ); ``` -#### gfillBy( N, x, stride, clbk\[, thisArg] ) +#### gfillBy( N, x, strideX, clbk\[, thisArg] ) -Fills a strided array `x` according to a provided callback function. +Fills a strided array according to a provided callback function. ```javascript function fill( v, i ) { @@ -48,17 +48,17 @@ gfillBy( x.length, x, 1, fill ); The function has the following parameters: - **N**: number of indexed elements. -- **x**: input array. -- **stride**: index increment. +- **x**: input array. +- **strideX**: stride length. - **clbk**: callback function. - **thisArg**: execution context (_optional_). -The invoked callback is provided four arguments: +The callback function is provided the following arguments: -- **value**: array element. +- **value**: current array element. - **aidx**: array index. - **sidx**: strided index (`offset + aidx*stride`). -- **array**: input array/collection. +- **array**: the input array. To set the callback execution context, provide a `thisArg`. @@ -81,19 +81,16 @@ var cnt = context.count; // returns 8 ``` -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to fill every other element +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to fill every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - function fill( v, i ) { return v * i; } var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; -var N = floor( x.length / 2 ); -gfillBy( N, x, 2, fill ); +gfillBy( 4, x, 2, fill ); // x => [ 0.0, 1.0, 3.0, -5.0, 8.0, 0.0, -3.0, -3.0 ] ``` @@ -101,7 +98,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); function fill( v, i ) { return v * i; @@ -112,16 +108,15 @@ var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); // Create an offset view... var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length/2 ); // Fill every other element... -gfillBy( N, x1, 2, fill ); +gfillBy( 3, x1, 2, fill ); // x0 => [ 1.0, 0.0, 3.0, -4.0, 5.0, -12.0 ] ``` -#### gfillBy.ndarray( N, x, stride, offset, clbk\[, thisArg] ) +#### gfillBy.ndarray( N, x, strideX, offsetX, clbk\[, thisArg] ) -Fills a strided array `x` according to a provided callback function and using alternative indexing semantics. +Fills a strided array according to a provided callback function and using alternative indexing semantics. ```javascript function fill( v, i ) { @@ -136,9 +131,9 @@ gfillBy.ndarray( x.length, x, 1, 0, fill ); The function has the following additional parameters: -- **offset**: starting index. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of `x` +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: ```javascript function fill( v, i ) { @@ -174,26 +169,14 @@ gfillBy.ndarray( 3, x, 1, x.length-3, fill ); ```javascript -var round = require( '@stdlib/math/base/special/round' ); -var randu = require( '@stdlib/random/base/randu' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var Float64Array = require( '@stdlib/array/float64' ); var gfillBy = require( '@stdlib/blas/ext/base/gfill-by' ); -function fill() { - var rand = round( randu()*100.0 ); - var sign = randu(); - if ( sign < 0.5 ) { - sign = -1.0; - } else { - sign = 1.0; - } - return sign * rand; -} - var x = new Float64Array( 10 ); console.log( x ); -gfillBy( x.length, x, 1, fill ); +gfillBy( x.length, x, 1, discreteUniform( -100, 100 ) ); console.log( x ); ``` diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/repl.txt index 6a9e76775f60..7888808c44a2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, x, stride, clbk[, thisArg] ) +{{alias}}( N, x, strideX, clbk[, thisArg] ) Fills a strided array according to a provided callback function. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. @@ -12,7 +12,7 @@ The callback function is provided four arguments: - - value: array element. + - value: current array element. - aidx: array index. - sidx: strided index (offset + aidx*stride). - array: the input array. @@ -28,8 +28,8 @@ x: ArrayLikeObject Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. clbk: Function Callback function. @@ -40,7 +40,7 @@ Returns ------- x: ArrayLikeObject - Input array `x`. + Input array. Examples -------- @@ -50,28 +50,26 @@ > {{alias}}( x.length, x, 1, fill ) [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, fill ) + > {{alias}}( 3, x, 2, fill ) [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, fill ) + > {{alias}}( 3, x1, 2, fill ) [ 5.0, 3.0, 5.0, 5.0, 5.0 ] > x0 [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ] -{{alias}}.ndarray( N, x, stride, offset, clbk[, thisArg] ) +{{alias}}.ndarray( N, x, strideX, offsetX, clbk[, thisArg] ) Fills a strided array according to a provided callback function and using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -82,11 +80,11 @@ x: ArrayLikeObject Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. - offset: integer - Starting index of `x`. + offsetX: integer + Starting index. clbk: Function Callback function. @@ -97,7 +95,7 @@ Returns ------- x: ArrayLikeObject - Input array `x`. + Input array. Examples -------- @@ -109,8 +107,7 @@ // Using an index offset: > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, fill ) + > {{alias}}.ndarray( 3, x, 2, 1, fill ) [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/types/index.d.ts index 8f7efefe5fe4..656fb4f3160c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/docs/types/index.d.ts @@ -98,8 +98,8 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param clbk - callback + * @param strideX - stride length + * @param clbk - callback function * @param thisArg - execution context * @returns `x` * @@ -113,7 +113,7 @@ interface Routine { * gfillBy( x.length, x, 1, fill ); * // x => [ 5.0, 5.0, 5.0, 0.0, 5.0, 5.0, 5.0, 5.0 ] */ - ( N: number, x: Collection, stride: number, clbk: Callback, thisArg?: ThisParameterType> ): Collection; + ( N: number, x: Collection, strideX: number, clbk: Callback, thisArg?: ThisParameterType> ): Collection; /** * Fills a strided array according to a provided callback function and using alternative indexing semantics. @@ -131,9 +131,9 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index - * @param clbk - callback + * @param strideX - stride length + * @param offsetX - starting index + * @param clbk - callback function * @param thisArg - execution context * @returns `x` * @@ -147,7 +147,7 @@ interface Routine { * gfillBy.ndarray( x.length, x, 1, 0, fill ); * // x => [ 5.0, 5.0, 5.0, 0.0, 5.0, 5.0, 5.0, 5.0 ] */ - ndarray( N: number, x: Collection, stride: number, offset: number, clbk: Callback, thisArg?: ThisParameterType> ): Collection; + ndarray( N: number, x: Collection, strideX: number, offsetX: number, clbk: Callback, thisArg?: ThisParameterType> ): Collection; } /** @@ -166,8 +166,8 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length -* @param clbk - callback +* @param strideX - stride length +* @param clbk - callback function * @param thisArg - execution context * @returns `x` * diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/examples/index.js index 3377025ad13c..a4bd6b6a33f3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/examples/index.js @@ -18,24 +18,12 @@ 'use strict'; -var round = require( '@stdlib/math/base/special/round' ); -var randu = require( '@stdlib/random/base/randu' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var Float64Array = require( '@stdlib/array/float64' ); var gfillBy = require( './../lib' ); -function fill() { - var rand = round( randu()*100.0 ); - var sign = randu(); - if ( sign < 0.5 ) { - sign = -1.0; - } else { - sign = 1.0; - } - return sign * rand; -} - var x = new Float64Array( 10 ); console.log( x ); -gfillBy( x.length, x, 1, fill ); +gfillBy( x.length, x, 1, discreteUniform( -100, 100 ) ); console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/accessors.js index 4bc24a1cb009..6465058b2ff0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/accessors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/accessors.js @@ -28,9 +28,9 @@ * @param {Object} x - input array object * @param {Collection} x.data - input array data * @param {Array} x.accessors - array element accessors -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index -* @param {Callback} clbk - callback +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @param {Callback} clbk - callback function * @param {*} thisArg - execution context * @returns {Object} input array object * @@ -63,7 +63,7 @@ * var view = reinterpret64( x.data, 0 ); * // view => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] */ -function gfillBy( N, x, stride, offset, clbk, thisArg ) { +function gfillBy( N, x, strideX, offsetX, clbk, thisArg ) { var xbuf; var set; var get; @@ -77,10 +77,10 @@ function gfillBy( N, x, stride, offset, clbk, thisArg ) { get = x.accessors[ 0 ]; set = x.accessors[ 1 ]; - ix = offset; + ix = offsetX; for ( i = 0; i < N; i++ ) { set( xbuf, ix, clbk.call( thisArg, get( xbuf, ix ), i, ix, x ) ); - ix += stride; + ix += strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/main.js index 7bcd62d0e229..1ab9a636f1ca 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); -var accessors = require( './accessors.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,8 +31,8 @@ var accessors = require( './accessors.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Collection} x - input array -* @param {integer} stride - index increment -* @param {Callback} clbk - callback +* @param {integer} strideX - stride length +* @param {Callback} clbk - callback function * @param {*} [thisArg] - execution context * @returns {Collection} input array * @@ -46,29 +46,8 @@ var accessors = require( './accessors.js' ); * gfillBy( x.length, x, 1, fill ); * // x => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] */ -function gfillBy( N, x, stride, clbk, thisArg ) { - var ix; - var o; - var i; - - if ( N <= 0 ) { - return x; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - o = arraylike2object( x ); - if ( o.accessorProtocol ) { - accessors( N, o, stride, ix, clbk, thisArg ); - return o.data; - } - for ( i = 0; i < N; i++ ) { - x[ ix ] = clbk.call( thisArg, x[ ix ], i, ix, x ); - ix += stride; - } - return x; +function gfillBy( N, x, strideX, clbk, thisArg ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), clbk, thisArg ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/ndarray.js index fc0448641d7f..9b8e89b2b5ef 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-by/lib/ndarray.js @@ -31,9 +31,9 @@ var accessors = require( './accessors.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Collection} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index -* @param {Callback} clbk - callback +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @param {Callback} clbk - callback function * @param {*} [thisArg] - execution context * @returns {Collection} input array * @@ -47,7 +47,7 @@ var accessors = require( './accessors.js' ); * gfillBy( 3, x, 1, x.length-3, fill ); * // x => [ 1.0, -2.0, 3.0, 5.0, 5.0, 5.0 ] */ -function gfillBy( N, x, stride, offset, clbk, thisArg ) { +function gfillBy( N, x, strideX, offsetX, clbk, thisArg ) { var ix; var o; var i; @@ -57,13 +57,13 @@ function gfillBy( N, x, stride, offset, clbk, thisArg ) { } o = arraylike2object( x ); if ( o.accessorProtocol ) { - accessors( N, o, stride, offset, clbk, thisArg ); + accessors( N, o, strideX, offsetX, clbk, thisArg ); return o.data; } - ix = offset; + ix = offsetX; for ( i = 0; i < N; i++ ) { x[ ix ] = clbk.call( thisArg, x[ ix ], i, ix, x ); - ix += stride; + ix += strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfill/README.md index 941ea9fc0e5e..d9f66d3d61d9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/README.md @@ -30,9 +30,9 @@ limitations under the License. var gfill = require( '@stdlib/blas/ext/base/gfill' ); ``` -#### gfill( N, alpha, x, stride ) +#### gfill( N, alpha, x, strideX ) -Fills a strided array `x` with a specified scalar constant `alpha`. +Fills a strided array with a specified scalar constant. ```javascript var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; @@ -46,17 +46,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **alpha**: scalar constant. - **x**: input array. -- **stride**: index increment. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to fill every other element +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to fill every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; -var N = floor( x.length / 2 ); -gfill( N, 5.0, x, 2 ); +gfill( 4, 5.0, x, 2 ); // x => [ 5.0, 1.0, 5.0, -5.0, 5.0, 0.0, 5.0, -3.0 ] ``` @@ -64,23 +61,21 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial array... var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); // Create an offset view... var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length/2 ); // Fill every other element... -gfill( N, 5.0, x1, 2 ); +gfill( 3, 5.0, x1, 2 ); // x0 => [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ] ``` -#### gfill.ndarray( N, alpha, x, stride, offset ) +#### gfill.ndarray( N, alpha, x, strideX, offsetX ) -Fills a strided array `x` with a specified scalar constant `alpha` using alternative indexing semantics. +Fills a strided array with a specified scalar constant using alternative indexing semantics. ```javascript var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; @@ -91,9 +86,9 @@ gfill.ndarray( x.length, 5.0, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of `x` +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: ```javascript var x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; @@ -125,15 +120,12 @@ gfill.ndarray( 3, 5.0, x, 1, x.length-3 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gfill = require( '@stdlib/blas/ext/base/gfill' ); -var x = new Float64Array( 10 ); -var i; -for ( i = 0; i < x.length; i++ ) { - x[ i ] = discreteUniform( -100, 100 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); gfill( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.js index a05478082b6a..cbffef414d02 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gfill = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gfill = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.ndarray.js index 2f27e35112f7..06c7d889bbc9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/benchmark/benchmark.ndarray.js @@ -21,11 +21,18 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; -var gfill = require( './../lib/main.js' ).ndarray; +var gfill = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; // FUNCTIONS // @@ -38,13 +45,7 @@ var gfill = require( './../lib/main.js' ).ndarray; * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/repl.txt index ec2109992757..f15e3a00ded1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, alpha, x, stride ) - Fills a strided array with a specified scalar value. +{{alias}}( N, alpha, x, strideX ) + Fills a strided array with a specified scalar constant. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. @@ -16,18 +16,18 @@ Number of indexed elements. alpha: any - Constant. + Scalar constant. x: ArrayLikeObject Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. Returns ------- x: ArrayLikeObject - Input array `x`. + Input array. Examples -------- @@ -36,29 +36,27 @@ > {{alias}}( x.length, 5.0, x, 1 ) [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 5.0, x, 2 ) + > {{alias}}( 3, 5.0, x, 2 ) [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 5.0, x1, 2 ) + > {{alias}}( 3, 5.0, x1, 2 ) [ 5.0, 3.0, 5.0, 5.0, 5.0 ] > x0 [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ] -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Fills a strided array with a specified scalar value using alternative +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Fills a strided array with a specified scalar constant using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameter supports indexing semantics based on a starting + index. Parameters ---------- @@ -66,21 +64,21 @@ Number of indexed elements. alpha: any - Constant. + Scalar constant. x: ArrayLikeObject Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. - offset: integer - Starting index of `x`. + offsetX: integer + Starting index. Returns ------- x: ArrayLikeObject - Input array `x`. + Input array. Examples -------- @@ -91,8 +89,7 @@ // Using an index offset: > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/index.d.ts index 62517e66a40a..a364ac91a61c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/index.d.ts @@ -20,19 +20,38 @@ /// -import { Collection } from '@stdlib/types/array'; +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; /** * Interface describing `gfill`. */ interface Routine { /** - * Fills a strided array with a specified scalar value. + * Fills a strided array with a specified scalar constant. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length + * @returns `x` + * + * @example + * var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); + * + * var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + * + * gfill( x.length, 5.0, toAccessorArray( x ), 1 ); + * // x => [ 5.0, 5.0, 5.0, 0.0, 5.0, 5.0, 5.0, 5.0 ] + */ + ( N: number, alpha: T, x: AccessorArrayLike, strideX: number ): AccessorArrayLike; + + /** + * Fills a strided array with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length * @returns `x` * * @example @@ -41,16 +60,36 @@ interface Routine { * gfill( x.length, 5.0, x, 1 ); * // x => [ 5.0, 5.0, 5.0, 0.0, 5.0, 5.0, 5.0, 5.0 ] */ - ( N: number, alpha: T, x: Collection, stride: number ): Collection; + ( N: number, alpha: T, x: Collection, strideX: number ): Collection; + + /** + * Fills a strided array with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); + * + * var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + * + * gfill.ndarray( x.length, 5.0, toAccessorArray( x ), 1, 0 ); + * // x => [ 5.0, 5.0, 5.0, 0.0, 5.0, 5.0, 5.0, 5.0 ] + */ + ndarray( N: number, alpha: T, x: AccessorArrayLike, strideX: number, offsetX: number ): AccessorArrayLike; /** - * Fills a strided array with a specified scalar value using alternative indexing semantics. + * Fills a strided array with a specified scalar constant using alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns `x` * * @example @@ -59,16 +98,16 @@ interface Routine { * gfill.ndarray( x.length, 5.0, x, 1, 0 ); * // x => [ 5.0, 5.0, 5.0, 0.0, 5.0, 5.0, 5.0, 5.0 ] */ - ndarray( N: number, alpha: T, x: Collection, stride: number, offset: number ): Collection; + ndarray( N: number, alpha: T, x: Collection, strideX: number, offsetX: number ): Collection; } /** -* Fills a strided array with a specified scalar value. +* Fills a strided array with a specified scalar constant. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns `x` * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/test.ts index 49e6f891929a..1cb6d039054e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/test.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/docs/types/test.ts @@ -16,6 +16,7 @@ * limitations under the License. */ +import AccessorArray = require( '@stdlib/array/base/accessor' ); import gfill = require( './index' ); @@ -26,6 +27,7 @@ import gfill = require( './index' ); const x = new Float64Array( 10 ); gfill( x.length, 5.0, x, 1 ); // $ExpectType Collection + gfill( x.length, 5.0, new AccessorArray( x ), 1 ); // $ExpectType AccessorArrayLike } // The compiler throws an error if the function is provided a first argument which is not a number... @@ -84,6 +86,7 @@ import gfill = require( './index' ); const x = new Float64Array( 10 ); gfill.ndarray( x.length, 5.0, x, 1, 0 ); // $ExpectType Collection + gfill.ndarray( x.length, 5.0, new AccessorArray( x ), 1, 0 ); // $ExpectType AccessorArrayLike } // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill/examples/index.js index c425be3a422b..bfb935521b34 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/examples/index.js @@ -18,15 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gfill = require( './../lib' ); -var x = new Float64Array( 10 ); -var i; -for ( i = 0; i < x.length; i++ ) { - x[ i ] = discreteUniform( -100, 100 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); gfill( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/accessors.js index 754240cbe30c..703662b08264 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/accessors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/accessors.js @@ -25,12 +25,12 @@ * * @private * @param {PositiveInteger} N - number of indexed elements -* @param {*} alpha - scalar +* @param {*} alpha - scalar constant * @param {Object} x - input array object * @param {Collection} x.data - input array data * @param {Array} x.accessors - array element accessors -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Object} input array object * * @example @@ -54,9 +54,9 @@ * gfill( data.length, alpha, x, 1, 0 ); * * var view = reinterpret64( x.data, 0 ); -* // view => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] +* // returns [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] */ -function gfill( N, alpha, x, stride, offset ) { +function gfill( N, alpha, x, strideX, offsetX ) { var xbuf; var set; var ix; @@ -68,10 +68,10 @@ function gfill( N, alpha, x, stride, offset ) { // Cache a reference to the element accessor: set = x.accessors[ 1 ]; - ix = offset; + ix = offsetX; for ( i = 0; i < N; i++ ) { set( xbuf, ix, alpha ); - ix += stride; + ix += strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/main.js index f4ec682c81c1..bdd504c34edd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/main.js @@ -20,13 +20,8 @@ // MODULES // -var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); -var accessors = require( './accessors.js' ); - - -// VARIABLES // - -var M = 8; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -35,9 +30,9 @@ var M = 8; * Fills a strided array with a specified scalar constant. * * @param {PositiveInteger} N - number of indexed elements -* @param {*} alpha - scalar +* @param {*} alpha - scalar constant * @param {Collection} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {Collection} input array * * @example @@ -46,60 +41,8 @@ var M = 8; * gfill( x.length, 5.0, x, 1 ); * // x => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] */ -function gfill( N, alpha, x, stride ) { - var ix; - var i; - var m; - var o; - - if ( N <= 0 ) { - return x; - } - o = arraylike2object( x ); - if ( o.accessorProtocol ) { - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - accessors( N, alpha, o, stride, ix ); - return o.data; - } - // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { - m = N % M; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - x[ i ] = alpha; - } - } - if ( N < M ) { - return x; - } - for ( i = m; i < N; i += M ) { - x[ i ] = alpha; - x[ i+1 ] = alpha; - x[ i+2 ] = alpha; - x[ i+3 ] = alpha; - x[ i+4 ] = alpha; - x[ i+5 ] = alpha; - x[ i+6 ] = alpha; - x[ i+7 ] = alpha; - } - return x; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - x[ ix ] = alpha; - ix += stride; - } - return x; +function gfill( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/ndarray.js index dd50ce87cabb..a226a2ec6d2b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill/lib/ndarray.js @@ -35,10 +35,10 @@ var M = 8; * Fills a strided array with a specified scalar constant. * * @param {PositiveInteger} N - number of indexed elements -* @param {*} alpha - scalar +* @param {*} alpha - scalar constant * @param {Collection} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Collection} input array * * @example @@ -47,7 +47,7 @@ var M = 8; * gfill( 3, 5.0, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, 5.0, 5.0, 5.0 ] */ -function gfill( N, alpha, x, stride, offset ) { +function gfill( N, alpha, x, strideX, offsetX ) { var ix; var m; var o; @@ -58,20 +58,20 @@ function gfill( N, alpha, x, stride, offset ) { } o = arraylike2object( x ); if ( o.accessorProtocol ) { - accessors( N, alpha, o, stride, offset ); + accessors( N, alpha, o, strideX, offsetX ); return o.data; } - ix = offset; + ix = offsetX; // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { + if ( strideX === 1 ) { m = N % M; // If we have a remainder, run a clean-up loop... if ( m > 0 ) { for ( i = 0; i < m; i++ ) { x[ ix ] = alpha; - ix += stride; + ix += strideX; } } if ( N < M ) { @@ -92,7 +92,7 @@ function gfill( N, alpha, x, stride, offset ) { } for ( i = 0; i < N; i++ ) { x[ ix ] = alpha; - ix += stride; + ix += strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/README.md index 2c082e484954..d8d36cad837f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/README.md @@ -52,20 +52,17 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **out**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array] whose first element is the sum and whose second element is the number of non-NaN elements. -- **strideOut**: index increment for `out`. +- **strideOut**: stride length for `out`. -The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ]; var out = [ 0.0, 0 ]; -var N = floor( x.length / 2 ); -var v = gnannsumkbn( N, x, 2, out, 1 ); +var v = gnannsumkbn( 4, x, 2, out, 1 ); // returns [ 5.0, 2 ] ``` @@ -75,7 +72,6 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element @@ -83,9 +79,7 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd var out0 = new Float64Array( 4 ); var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element -var N = floor( x0.length / 2 ); - -var v = gnannsumkbn( N, x1, 2, out1, 1 ); +var v = gnannsumkbn( 4, x1, 2, out1, 1 ); // returns [ 5.0, 4 ] ``` @@ -106,16 +100,13 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetOut**: starting index for `out`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ]; var out = [ 0.0, 0.0, 0.0, 0 ]; -var N = floor( x.length / 2 ); -var v = gnannsumkbn.ndarray( N, x, 2, 1, out, 2, 1 ); +var v = gnannsumkbn.ndarray( 4, x, 2, 1, out, 2, 1 ); // returns [ 0.0, 5.0, 0.0, 4 ] ``` @@ -140,22 +131,20 @@ var v = gnannsumkbn.ndarray( N, x, 2, 1, out, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var Float64Array = require( '@stdlib/array/float64' ); var gnannsumkbn = require( '@stdlib/blas/ext/base/gnannsumkbn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var out = new Float64Array( 2 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.js index 16729be1aa14..5032733667b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.js @@ -21,15 +21,31 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/base/zeros' ); var pkg = require( './../package.json' ).name; var gnannsumkbn = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,19 +54,8 @@ var gnannsumkbn = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var out; - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } - out = [ 0.0, 0 ]; + var out = zeros( 2 ); + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.ndarray.js index fdffbb52fa7c..e745ede588ee 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/benchmark/benchmark.ndarray.js @@ -21,15 +21,31 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/base/zeros' ); var pkg = require( './../package.json' ).name; var gnannsumkbn = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,19 +54,8 @@ var gnannsumkbn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var out; - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } - out = [ 0.0, 0 ]; + var out = zeros( 2 ); + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/repl.txt index 37e78bd71688..ff1eb7a20322 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/repl.txt @@ -3,7 +3,7 @@ Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements are accessed at + The `N` and stride parameters determine which elements are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -20,13 +20,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. out: Array|TypedArray Output array. strideOut: integer - Index increment for `out`. + Stride length for `out`. Returns ------- @@ -42,28 +42,27 @@ > {{alias}}( x.length, x, 1, out, 1 ) [ 1.0, 3 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; > out = [ 0.0, 0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, out, 1 ) + > {{alias}}( 4, x, 2, out, 1 ) [ 1.0, 3 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); > out = [ 0.0, 0 ]; - > {{alias}}( N, x1, 2, out, 1 ) + > {{alias}}( 4, x1, 2, out, 1 ) [ 1.0, 3 ] + {{alias}}.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut ) Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on a starting + indices. Parameters ---------- @@ -74,7 +73,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -83,7 +82,7 @@ Output array. strideOut: integer - Index increment for `out`. + Stride length for `out`. offsetOut: integer Starting index for `out`. @@ -104,9 +103,8 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); > out = [ 0.0, 0 ]; - > {{alias}}.ndarray( N, x, 2, 1, out, 1, 0 ) + > {{alias}}.ndarray( 4, x, 2, 1, out, 1, 0 ) [ 1.0, 3 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/types/index.d.ts index e38292bfc73c..ccec623bb8d4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/docs/types/index.d.ts @@ -31,9 +31,9 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param out - output array whose first element is the sum and whose second element is the number of non-NaN elements - * @param strideOut - `out` stride length + * @param strideOut - stride length for `out` * @returns output array * * @example @@ -50,11 +50,11 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param strideX - `x` stride length - * @param offsetX - `x` starting index + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` * @param out - output array whose first element is the sum and whose second element is the number of non-NaN elements - * @param strideOut - `out` stride length - * @param offsetOut - `out` starting index + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` * @returns output array * * @example @@ -72,9 +72,9 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param out - output array whose first element is the sum and whose second element is the number of non-NaN elements -* @param strideOut - `out` stride length +* @param strideOut - stride length for `out` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/examples/index.js index 3695ba3f287e..8b293afebf6a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/examples/index.js @@ -18,25 +18,22 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var Float64Array = require( '@stdlib/array/float64' ); var gnannsumkbn = require( './../lib' ); -var out; -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); -out = new Float64Array( 2 ); +var out = new Float64Array( 2 ); gnannsumkbn( x.length, x, 1, out, 1 ); console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/index.js index 8a2ceed5040f..5d63097f7793 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/index.js @@ -33,15 +33,12 @@ * // returns [ 1.0, 3 ] * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gnannsumkbn = require( '@stdlib/blas/ext/base/gnannsumkbn' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; * var out = [ 0.0, 0 ]; * -* var N = floor( x.length / 2 ); -* -* var v = gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 ); +* var v = gnannsumkbn.ndarray( 5, x, 2, 1, out, 1, 0 ); * // returns [ 5.0, 4 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/main.js index da1eca5a14d2..c65bfa3179d7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,9 +39,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NumericArray} out - output array -* @param {integer} strideOut - `out` stride length +* @param {integer} strideOut - stride length for `out` * @returns {NumericArray} output array * * @example @@ -52,60 +52,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * // returns [ 1.0, 3 ] */ function gnannsumkbn( N, x, strideX, out, strideOut ) { - var sum; - var ix; - var io; - var v; - var t; - var c; - var n; - var i; - - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideOut < 0 ) { - io = -strideOut; - } else { - io = 0; - } - sum = 0.0; - if ( N <= 0 ) { - out[ io ] = sum; - out[ io+strideOut ] = 0; - return out; - } - if ( N === 1 || strideX === 0 ) { - if ( isnan( x[ ix ] ) ) { - out[ io ] = sum; - out[ io+strideOut ] = 0; - return out; - } - out[ io ] = x[ ix ]; - out[ io+strideOut ] = 1; - return out; - } - c = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( isnan( v ) === false ) { - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c += (sum-t) + v; - } else { - c += (v-t) + sum; - } - sum = t; - n += 1; - } - ix += strideX; - } - out[ io ] = sum + c; - out[ io+strideOut ] = n; - return out; + var ix = stride2offset( N, strideX ); + var io = stride2offset( 2, strideOut ); + return ndarray( N, x, strideX, ix, out, strideOut, io ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/ndarray.js index 976fa79aa64c..1c2cc2d86869 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/lib/ndarray.js @@ -39,51 +39,44 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} strideX - `x` stride length -* @param {NonNegativeInteger} offsetX - `x` starting index +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` * @param {NumericArray} out - output array -* @param {integer} strideOut - `out` stride length -* @param {NonNegativeInteger} offsetOut - `out` starting index +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` * @returns {NumericArray} output array * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; * var out = [ 0.0, 0 ]; * -* var N = floor( x.length / 2 ); -* -* var v = gnannsumkbn( N, x, 2, 1, out, 1, 0 ); +* var v = gnannsumkbn( 5, x, 2, 1, out, 1, 0 ); * // returns [ 5.0, 4 ] */ function gnannsumkbn( N, x, strideX, offsetX, out, strideOut, offsetOut ) { var sum; var ix; - var io; var v; var t; var c; var n; var i; - ix = offsetX; - io = offsetOut; - sum = 0.0; if ( N <= 0 ) { - out[ io ] = sum; - out[ io+strideOut ] = 0; + out[ offsetOut ] = sum; + out[ offsetOut+strideOut ] = 0; return out; } - if ( N === 1 || strideX === 0 ) { + ix = offsetX; + if ( strideX === 0 ) { if ( isnan( x[ ix ] ) ) { - out[ io ] = sum; - out[ io+strideOut ] = 0; + out[ offsetOut ] = sum; + out[ offsetOut+strideOut ] = 0; return out; } - out[ io ] = x[ ix ]; - out[ io+strideOut ] = 1; + out[ offsetOut ] = x[ ix ] * N; + out[ offsetOut+strideOut ] = N; return out; } c = 0.0; @@ -102,8 +95,8 @@ function gnannsumkbn( N, x, strideX, offsetX, out, strideOut, offsetOut ) { } ix += strideX; } - out[ io ] = sum + c; - out[ io+strideOut ] = n; + out[ offsetOut ] = sum + c; + out[ offsetOut+strideOut ] = n; return out; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.main.js index e72184b62b7c..42f172749130 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var gnannsumkbn = require( './../lib' ); @@ -163,7 +162,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a sum equ tape( 'the function supports `stride` parameters', function test( t ) { var expected; var out; - var N; var x; var v; @@ -181,8 +179,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { ]; out = [ 0.0, 0.0, 0.0, 0.0 ]; - N = floor( x.length / 2 ); - v = gnannsumkbn( N, x, 2, out, 2 ); + v = gnannsumkbn( 5, x, 2, out, 2 ); expected = [ 5.0, 0.0, 4.0, 0.0 ]; t.deepEqual( v, expected, 'returns expected value' ); @@ -193,7 +190,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var expected; var out; - var N; var x; var v; @@ -211,8 +207,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { ]; out = [ 0.0, 0.0, 0.0, 0.0 ]; - N = floor( x.length / 2 ); - v = gnannsumkbn( N, x, -2, out, -2 ); + v = gnannsumkbn( 5, x, -2, out, -2 ); expected = [ 4.0, 0.0, 5.0, 0.0 ]; t.deepEqual( v, expected, 'returns expected value' ); @@ -220,7 +215,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns a sum equal to the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the of the first element repeated N times', function test( t ) { var expected; var out; var x; @@ -231,7 +226,24 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns a sum out = [ 0.0, 0.0 ]; v = gnannsumkbn( x.length, x, 0, out, 1 ); - expected = [ 1.0, 1.0 ]; + expected = [ 5.0, 5.0 ]; + t.deepEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is `NaN`, the function returns `0.0`', function test( t ) { + var expected; + var out; + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + out = [ 0.0, 0.0 ]; + v = gnannsumkbn( x.length, x, 0, out, 1 ); + + expected = [ 0.0, 0.0 ]; t.deepEqual( v, expected, 'returns expected value' ); t.end(); @@ -244,7 +256,6 @@ tape( 'the function supports view offsets', function test( t ) { var out1; var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -264,9 +275,8 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at the 3rd element - N = floor(x1.length / 2); - v = gnannsumkbn( N, x1, 2, out1, 1 ); + v = gnannsumkbn( 5, x1, 2, out1, 1 ); expected0 = new Float64Array( [ 0.0, 0.0, 5.0, 4.0 ] ); expected1 = new Float64Array( [ 5.0, 4.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.ndarray.js index d1b61d27cea5..b3fb5364bf72 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnannsumkbn/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var gnannsumkbn = require( './../lib/ndarray.js' ); @@ -162,7 +161,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports a `stride` parameter', function test( t ) { var expected; var out; - var N; var x; var v; @@ -180,8 +178,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { ]; out = [ 0.0, 0.0, 0.0, 0.0 ]; - N = floor( x.length / 2 ); - v = gnannsumkbn( N, x, 2, 0, out, 2, 0 ); + v = gnannsumkbn( 5, x, 2, 0, out, 2, 0 ); expected = [ 5.0, 0.0, 4.0, 0.0 ]; t.deepEqual( v, expected, 'returns expected value' ); @@ -192,7 +189,6 @@ tape( 'the function supports a `stride` parameter', function test( t ) { tape( 'the function supports a negative `stride` parameter', function test( t ) { var expected; var out; - var N; var x; var v; @@ -210,8 +206,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) ]; out = [ 0.0, 0.0, 0.0, 0.0 ]; - N = floor( x.length / 2 ); - v = gnannsumkbn( N, x, -2, 8, out, -2, 2 ); + v = gnannsumkbn( 5, x, -2, 8, out, -2, 2 ); expected = [ 4.0, 0.0, 5.0, 0.0 ]; t.deepEqual( v, expected, 'returns expected value' ); @@ -219,7 +214,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the of the first element repeated N times', function test( t ) { var expected; var out; var x; @@ -230,7 +225,24 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f out = [ 0.0, 0.0 ]; v = gnannsumkbn( x.length, x, 0, 0, out, 1, 0 ); - expected = [ 1.0, 1.0 ]; + expected = [ 5.0, 5.0 ]; + t.deepEqual( v, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is `NaN`, the function returns `0.0`', function test( t ) { + var expected; + var out; + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + out = [ 0.0, 0.0 ]; + v = gnannsumkbn( x.length, x, 0, 0, out, 1, 0 ); + + expected = [ 0.0, 0.0 ]; t.deepEqual( v, expected, 'returns expected value' ); t.end(); @@ -239,7 +251,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports `offset` parameters', function test( t ) { var expected; var out; - var N; var x; var v; @@ -256,9 +267,8 @@ tape( 'the function supports `offset` parameters', function test( t ) { NaN // 4 ]; out = [ 0.0, 0.0, 0.0, 0.0 ]; - N = floor( x.length / 2 ); - v = gnannsumkbn( N, x, 2, 1, out, 2, 1 ); + v = gnannsumkbn( 5, x, 2, 1, out, 2, 1 ); expected = [ 0.0, 5.0, 0.0, 4.0 ]; t.deepEqual( v, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/README.md b/lib/node_modules/@stdlib/blas/ext/base/gnansum/README.md index e5633c61288d..28db46a2bc14 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/README.md @@ -36,15 +36,14 @@ limitations under the License. var gnansum = require( '@stdlib/blas/ext/base/gnansum' ); ``` -#### gnansum( N, x, stride ) +#### gnansum( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansum( N, x, 1 ); +var v = gnansum( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansum( N, x, 2 ); +var v = gnansum( 5, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gnansum( N, x1, 2 ); +var v = gnansum( 4, x1, 2 ); // returns 5.0 ``` -#### gnansum.ndarray( N, x, stride, offset ) +#### gnansum.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansum.ndarray( N, x, 1, 0 ); +var v = gnansum.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansum.ndarray( N, x, 2, 1 ); +var v = gnansum.ndarray( 5, x, 2, 1 ); // returns 5.0 ``` @@ -133,22 +122,19 @@ var v = gnansum.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansum = require( '@stdlib/blas/ext/base/gnansum' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansum( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js index e8cc021f82c2..5c5f93acf142 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansum = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansum = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js index 07b61901f659..f32bc963a92e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansum = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansum = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/repl.txt index aa43e88482c7..1a7705a47342 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -18,8 +18,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -33,27 +33,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 4, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -64,10 +61,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -84,8 +81,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 4, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/types/index.d.ts index cb5796faea13..84c857bb4938 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gnansum( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements, ignoring `NaN` values and using alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gnansum.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/examples/index.js index 047107965f13..69ab51c5e86e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansum = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansum( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/index.js index 78cb0dc81fef..d019191583dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/index.js @@ -27,19 +27,16 @@ * var gnansum = require( '@stdlib/blas/ext/base/gnansum' ); * * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansum( N, x, 1 ); +* var v = gnansum( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gnansum = require( '@stdlib/blas/ext/base/gnansum' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = gnansum.ndarray( N, x, 2, 1 ); +* var v = gnansum.ndarray( 5, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/main.js index 743a3cc7c439..3ba56f36de42 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,18 +31,17 @@ var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansum( N, x, 1 ); +* var v = gnansum( x.length, x, 1 ); * // returns 1.0 */ -function gnansum( N, x, stride ) { - return gnansumkbn( N, x, stride ); +function gnansum( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/ndarray.js index cee37bac3c59..1214bf8521ff 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/lib/ndarray.js @@ -30,21 +30,18 @@ var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gnansum( N, x, 2, 1 ); +* var v = gnansum( 4, x, 2, 1 ); * // returns 5.0 */ -function gnansum( N, x, stride, offset ) { - return gnansumkbn( N, x, stride, offset ); +function gnansum( N, x, strideX, offsetX ) { + return gnansumkbn( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.main.js index 23111ac5ffe8..a91b06293bbe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var gnansum = require( './../lib' ); @@ -102,7 +101,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -119,15 +117,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansum( N, x, 2 ); + v = gnansum( 5, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -144,21 +140,32 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansum( N, x, -2 ); + v = gnansum( 5, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansum( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansum( x.length, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); @@ -166,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -184,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gnansum( N, x1, 2 ); + v = gnansum( 5, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.ndarray.js index f8d2b8419148..6f9179b4d2c8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansum/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var gnansum = require( './../lib/ndarray.js' ); @@ -101,7 +100,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -118,15 +116,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansum( N, x, 2, 0 ); + v = gnansum( 5, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -143,27 +139,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansum( N, x, -2, 8 ); + v = gnansum( 5, x, -2, 8 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansum( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansum( x.length, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -179,9 +185,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = gnansum( N, x, 2, 1 ); + v = gnansum( 5, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/README.md index 4855f7fc32f2..44cf778d0f5b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/README.md @@ -36,15 +36,14 @@ limitations under the License. var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); ``` -#### gnansumkbn( N, x, stride ) +#### gnansumkbn( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumkbn( N, x, 1 ); +var v = gnansumkbn( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumkbn( N, x, 2 ); +var v = gnansumkbn( 5, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gnansumkbn( N, x1, 2 ); +var v = gnansumkbn( 4, x1, 2 ); // returns 5.0 ``` -#### gnansumkbn.ndarray( N, x, stride, offset ) +#### gnansumkbn.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumkbn.ndarray( N, x, 1, 0 ); +var v = gnansumkbn.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumkbn.ndarray( N, x, 2, 1 ); +var v = gnansumkbn.ndarray( 5, x, 2, 1 ); // returns 5.0 ``` @@ -133,22 +122,19 @@ var v = gnansumkbn.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumkbn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js index 5c1931e65e01..27514b9b14d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumkbn = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumkbn = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js index b743cfae9ba8..6099a3a7ecb6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumkbn = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumkbn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/repl.txt index 7fb38fa10ead..03f368e8ad1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,28 +34,25 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 4, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameter supports indexing semantics based on a starting + index. Parameters ---------- @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 4, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/types/index.d.ts index c35907302665..bb55e943bc42 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gnansumkbn( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements, ignoring `NaN` values and using an improved Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gnansumkbn.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/examples/index.js index 63f9431aa22e..1b2d1e1d5df2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var gnansumkbn = require( './../lib' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumkbn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/index.js index 976c188e2318..88b2be4d9dfa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/index.js @@ -27,19 +27,16 @@ * var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); * * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumkbn( N, x, 1 ); +* var v = gnansumkbn( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gnansumkbn = require( '@stdlib/blas/ext/base/gnansumkbn' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumkbn.ndarray( N, x, 2, 1 ); +* var v = gnansumkbn.ndarray( 5, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/main.js index 0f3e7a4c8422..0089b14fea73 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,54 +39,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumkbn( N, x, 1 ); +* var v = gnansumkbn( x.length, x, 1 ); * // returns 1.0 */ -function gnansumkbn( N, x, stride ) { - var sum; - var ix; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ 0 ] ) ) { - return 0.0; - } - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - c = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( isnan( v ) === false ) { - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c += (sum-t) + v; - } else { - c += (v-t) + sum; - } - sum = t; - } - ix += stride; - } - return sum + c; +function gnansumkbn( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/ndarray.js index 6ad940ed5be7..581410120e63 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/lib/ndarray.js @@ -39,20 +39,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumkbn( N, x, 2, 1 ); +* var v = gnansumkbn( 4, x, 2, 1 ); * // returns 5.0 */ -function gnansumkbn( N, x, stride, offset ) { +function gnansumkbn( N, x, strideX, offsetX ) { var sum; var ix; var v; @@ -63,13 +60,13 @@ function gnansumkbn( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ offset ] ) ) { + ix = offsetX; + if ( strideX === 0 ) { + if ( isnan( x[ ix ] ) ) { return 0.0; } - return x[ offset ]; + return N * x[ ix ]; } - ix = offset; sum = 0.0; c = 0.0; for ( i = 0; i < N; i++ ) { @@ -83,7 +80,7 @@ function gnansumkbn( N, x, stride, offset ) { } sum = t; } - ix += stride; + ix += strideX; } return sum + c; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.main.js index 81f28a75aaaa..93412d9bc358 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var gnansumkbn = require( './../lib' ); @@ -102,7 +101,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -119,15 +117,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumkbn( N, x, 2 ); + v = gnansumkbn( 5, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -144,21 +140,32 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumkbn( N, x, -2 ); + v = gnansumkbn( 5, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumkbn( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumkbn( x.length, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); @@ -166,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -184,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gnansumkbn( N, x1, 2 ); + v = gnansumkbn( 5, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.ndarray.js index 463338080baa..5ef59c5892db 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var gnansumkbn = require( './../lib/ndarray.js' ); @@ -101,7 +100,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -118,15 +116,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumkbn( N, x, 2, 0 ); + v = gnansumkbn( 5, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -143,27 +139,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumkbn( N, x, -2, 8 ); + v = gnansumkbn( 5, x, -2, 8 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumkbn( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumkbn( x.length, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -179,9 +185,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = gnansumkbn( N, x, 2, 1 ); + v = gnansumkbn( 5, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/README.md index b3556d9cf6ec..d27596f23764 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/README.md @@ -36,15 +36,14 @@ limitations under the License. var gnansumkbn2 = require( '@stdlib/blas/ext/base/gnansumkbn2' ); ``` -#### gnansumkbn2( N, x, stride ) +#### gnansumkbn2( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumkbn2( N, x, 1 ); +var v = gnansumkbn2( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumkbn2( N, x, 2 ); +var v = gnansumkbn2( 5, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gnansumkbn2( N, x1, 2 ); +var v = gnansumkbn2( 4, x1, 2 ); // returns 5.0 ``` -#### gnansumkbn2.ndarray( N, x, stride, offset ) +#### gnansumkbn2.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumkbn2.ndarray( N, x, 1, 0 ); +var v = gnansumkbn2.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumkbn2.ndarray( N, x, 2, 1 ); +var v = gnansumkbn2.ndarray( 5, x, 2, 1 ); // returns 5.0 ``` @@ -133,22 +122,19 @@ var v = gnansumkbn2.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansumkbn2 = require( '@stdlib/blas/ext/base/gnansumkbn2' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js index 809e7ed517ee..d88d8cbe937f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumkbn2 = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumkbn2 = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js index 1e49f9d343b8..118d8e0dc9ac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumkbn2 = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumkbn2 = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/repl.txt index d07302742133..67d538b3dd8a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,28 +34,25 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 4, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -66,10 +63,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 4, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/types/index.d.ts index 5da01246333c..c7f1de9324d8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gnansumkbn2( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gnansumkbn2.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/examples/index.js index c92c67bc5e9c..fadc6162a5f0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var gnansumkbn2 = require( './../lib' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var gnansumkbn2 = require( '@stdlib/blas/ext/base/gnansumkbn2' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/index.js index ecafea2ef182..706090a51b1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/index.js @@ -27,19 +27,16 @@ * var gnansumkbn2 = require( '@stdlib/blas/ext/base/gnansumkbn2' ); * * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumkbn2( N, x, 1 ); +* var v = gnansumkbn2( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gnansumkbn2 = require( '@stdlib/blas/ext/base/gnansumkbn2' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumkbn2.ndarray( N, x, 2, 1 ); +* var v = gnansumkbn2.ndarray( 5, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/main.js index 70f41b142fa4..1014794a3008 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,66 +39,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumkbn2( N, x, 1 ); +* var v = gnansumkbn2( x.length, x, 1 ); * // returns 1.0 */ -function gnansumkbn2( N, x, stride ) { - var sum; - var ccs; - var ix; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ 0 ] ) ) { - return 0.0; - } - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( isnan( v ) === false ) { - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c = (sum-t) + v; - } else { - c = (v-t) + sum; - } - sum = t; - t = cs + c; - if ( abs( cs ) >= abs( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - } - ix += stride; - } - return sum + cs + ccs; +function gnansumkbn2( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/ndarray.js index 2eff8dfb04ee..9a6efa538350 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/lib/ndarray.js @@ -39,20 +39,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumkbn2( N, x, 2, 1 ); +* var v = gnansumkbn2( 4, x, 2, 1 ); * // returns 5.0 */ -function gnansumkbn2( N, x, stride, offset ) { +function gnansumkbn2( N, x, strideX, offsetX ) { var sum; var ccs; var ix; @@ -66,13 +63,13 @@ function gnansumkbn2( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ offset ] ) ) { + ix = offsetX; + if ( strideX === 0 ) { + if ( isnan( x[ ix ] ) ) { return 0.0; } - return x[ offset ]; + return N * x[ ix ]; } - ix = offset; sum = 0.0; ccs = 0.0; // second order correction term for lost low order bits cs = 0.0; // first order correction term for lost low order bits @@ -95,7 +92,7 @@ function gnansumkbn2( N, x, stride, offset ) { cs = t; ccs += cc; } - ix += stride; + ix += strideX; } return sum + cs + ccs; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.main.js index 499a81fba060..951898d41296 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var gnansumkbn2 = require( './../lib' ); @@ -102,7 +101,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -119,15 +117,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumkbn2( N, x, 2 ); + v = gnansumkbn2( 5, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -144,21 +140,32 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumkbn2( N, x, -2 ); + v = gnansumkbn2( 5, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumkbn2( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumkbn2( x.length, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); @@ -166,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -184,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gnansumkbn2( N, x1, 2 ); + v = gnansumkbn2( 5, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.ndarray.js index a403de537710..4f47cddca8c6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumkbn2/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var gnansumkbn2 = require( './../lib/ndarray.js' ); @@ -101,7 +100,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -118,15 +116,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumkbn2( N, x, 2, 0 ); + v = gnansumkbn2( 5, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -143,27 +139,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumkbn2( N, x, -2, 8 ); + v = gnansumkbn2( 5, x, -2, 8 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumkbn2( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumkbn2( x.length, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -179,9 +185,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = gnansumkbn2( N, x, 2, 1 ); + v = gnansumkbn2( 5, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/README.md index 61e9bd52e8af..ce3e9ab39b06 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/README.md @@ -36,15 +36,14 @@ limitations under the License. var gnansumors = require( '@stdlib/blas/ext/base/gnansumors' ); ``` -#### gnansumors( N, x, stride ) +#### gnansumors( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumors( N, x, 1 ); +var v = gnansumors( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumors( N, x, 2 ); +var v = gnansumors( 5, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gnansumors( N, x1, 2 ); +var v = gnansumors( 4, x1, 2 ); // returns 5.0 ``` -#### gnansumors.ndarray( N, x, stride, offset ) +#### gnansumors.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumors.ndarray( N, x, 1, 0 ); +var v = gnansumors.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumors.ndarray( N, x, 2, 1 ); +var v = gnansumors.ndarray( 5, x, 2, 1 ); // returns 5.0 ``` @@ -134,22 +123,19 @@ var v = gnansumors.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansumors = require( '@stdlib/blas/ext/base/gnansumors' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js index 37f92bbb98c9..05eb87ec8e9f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumors = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumors = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js index 089664e9163d..a2accc5c6ead 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumors = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/repl.txt index 16a5c9a454e8..f99e4fe8bd11 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,27 +34,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 4, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 4, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/types/index.d.ts index 143ef7c7ad65..dbabe3b7d1d9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gnansumors( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements, ignoring `NaN` values and using ordinary recursive summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gnansumors.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/examples/index.js index 8f3186f54941..0300e968049a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansumors = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/index.js index 2247de83bd26..4cc491fd9841 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/index.js @@ -27,19 +27,16 @@ * var gnansumors = require( '@stdlib/blas/ext/base/gnansumors' ); * * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumors( N, x, 1 ); +* var v = gnansumors( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gnansumors = require( '@stdlib/blas/ext/base/gnansumors' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumors.ndarray( N, x, 2, 1 ); +* var v = gnansumors.ndarray( 5, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/main.js index d58ccbb4127b..5e7742c0d02d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,43 +31,17 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumors( N, x, 1 ); +* var v = gnansumors( x.length, x, 1 ); * // returns 1.0 */ -function gnansumors( N, x, stride ) { - var ix; - var s; - var i; - - s = 0.0; - if ( N <= 0 ) { - return s; - } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ 0 ] ) ) { - return s; - } - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - if ( isnan( x[ ix ] ) === false ) { - s += x[ ix ]; - } - ix += stride; - } - return s; +function gnansumors( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/ndarray.js index 45529e5abaf2..a61dc7ca7582 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/lib/ndarray.js @@ -30,42 +30,39 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumors( N, x, 2, 1 ); +* var v = gnansumors( 4, x, 2, 1 ); * // returns 5.0 */ -function gnansumors( N, x, stride, offset ) { +function gnansumors( N, x, strideX, offsetX ) { + var sum; var ix; - var s; var i; - s = 0.0; if ( N <= 0 ) { - return s; + return 0.0; } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ offset ] ) ) { - return s; + ix = offsetX; + if ( strideX === 0 ) { + if ( isnan( x[ ix ] ) ) { + return 0.0; } - return x[ offset ]; + return N * x[ ix ]; } - ix = offset; + sum = 0.0; for ( i = 0; i < N; i++ ) { if ( isnan( x[ ix ] ) === false ) { - s += x[ ix ]; + sum += x[ ix ]; } - ix += stride; + ix += strideX; } - return s; + return sum; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.main.js index 1558559014bf..69e3b49ab95f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var gnansumors = require( './../lib' ); @@ -102,7 +101,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -119,15 +117,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumors( N, x, 2 ); + v = gnansumors( 5, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -144,21 +140,32 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumors( N, x, -2 ); + v = gnansumors( 5, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumors( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumors( x.length, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); @@ -166,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -184,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gnansumors( N, x1, 2 ); + v = gnansumors( 5, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.ndarray.js index 761ad2c2909c..bdc2a24686fe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumors/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var gnansumors = require( './../lib/ndarray.js' ); @@ -101,7 +100,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -118,15 +116,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumors( N, x, 2, 0 ); + v = gnansumors( 5, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -143,27 +139,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumors( N, x, -2, 8 ); + v = gnansumors( 5, x, -2, 8 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumors( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumors( x.length, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -179,9 +185,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = gnansumors( N, x, 2, 1 ); + v = gnansumors( 5, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/README.md index ba6486d03d90..19c1498a2011 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/README.md @@ -36,15 +36,14 @@ limitations under the License. var gnansumpw = require( '@stdlib/blas/ext/base/gnansumpw' ); ``` -#### gnansumpw( N, x, stride ) +#### gnansumpw( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and using pairwise summation. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumpw( N, x, 1 ); +var v = gnansumpw( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumpw( N, x, 2 ); +var v = gnansumpw( 5, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gnansumpw( N, x1, 2 ); +var v = gnansumpw( 4, x1, 2 ); // returns 5.0 ``` -#### gnansumpw.ndarray( N, x, stride, offset ) +#### gnansumpw.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var N = x.length; -var v = gnansumpw.ndarray( N, x, 1, 0 ); +var v = gnansumpw.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -var N = floor( x.length / 2 ); -var v = gnansumpw.ndarray( N, x, 2, 1 ); +var v = gnansumpw.ndarray( 5, x, 2, 1 ); // returns 5.0 ``` @@ -134,22 +123,19 @@ var v = gnansumpw.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansumpw = require( '@stdlib/blas/ext/base/gnansumpw' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js index ce42f3b791c6..83e7842d675e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumpw = require( './../lib/main.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumpw = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js index 597eb77fd41a..7409d4584a7f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var gnansumpw = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) > 0 ) { + return uniform( -10.0, 10.0 ); + } + return NaN; +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var gnansumpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*10.0 ) - 20.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/repl.txt index 30200e4f4534..5c9de3ce3ea9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements, ignoring `NaN` values and pairwise summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,27 +34,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 4, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 4, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/types/index.d.ts index fe95b3e0ee49..573c6e737764 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gnansumpw( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gnansumpw.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/examples/index.js index 50cf98cecd26..b187a5138b28 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var gnansumpw = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( randu()*100.0 ); +function rand() { + if ( bernoulli( 0.7 ) > 0 ) { + return discreteUniform( 0, 100 ); } + return NaN; } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = gnansumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/index.js index 5591d393a7e3..8b4bacf3b375 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/index.js @@ -27,19 +27,16 @@ * var gnansumpw = require( '@stdlib/blas/ext/base/gnansumpw' ); * * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumpw( N, x, 1 ); +* var v = gnansumpw( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gnansumpw = require( '@stdlib/blas/ext/base/gnansumpw' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumpw.ndarray( N, x, 2, 1 ); +* var v = gnansumpw.ndarray( 5, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/main.js index 1aaa814d0ec6..8607cc223f28 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/main.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,47 +39,17 @@ var sum = require( './ndarray.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, NaN, 2.0 ]; -* var N = x.length; * -* var v = gnansumpw( N, x, 1 ); +* var v = gnansumpw( x.length, x, 1 ); * // returns 1.0 */ -function gnansumpw( N, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ 0 ] ) ) { - return 0.0; - } - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - if ( isnan( x[ ix ] ) === false ) { - s += x[ ix ]; - } - ix += stride; - } - return s; - } - return sum( N, x, stride, ix ); +function gnansumpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/ndarray.js index e68a689285ee..aa943fb02989 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/lib/ndarray.js @@ -45,20 +45,17 @@ var BLOCKSIZE = 128; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gnansumpw( N, x, 2, 1 ); +* var v = gnansumpw( 4, x, 2, 1 ); * // returns 5.0 */ -function gnansumpw( N, x, stride, offset ) { +function gnansumpw( N, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -76,13 +73,13 @@ function gnansumpw( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ offset ] ) ) { + ix = offsetX; + if ( strideX === 0 ) { + if ( isnan( x[ ix ] ) ) { return 0.0; } - return x[ offset ]; + return N * x[ ix ]; } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; @@ -90,64 +87,64 @@ function gnansumpw( N, x, stride, offset ) { if ( isnan( x[ ix ] ) === false ) { s += x[ ix ]; } - ix += stride; + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... s0 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s1 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s2 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s3 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s4 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s5 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s6 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s7 = ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { s0 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s1 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s2 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s3 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s4 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s5 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s6 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; s7 += ( isnan( x[ ix ] ) ) ? 0.0 : x[ ix ]; - ix += stride; + ix += strideX; } // Pairwise sum the accumulators: - s = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); + s = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); // Clean-up loop... for ( i; i < N; i++ ) { if ( isnan( x[ ix ] ) === false ) { s += x[ ix ]; } - ix += stride; + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return gnansumpw( n, x, stride, ix ) + gnansumpw( N-n, x, stride, ix+(n*stride) ); // eslint-disable-line max-len + return gnansumpw( n, x, strideX, ix ) + gnansumpw( N-n, x, strideX, ix+(n*strideX) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.main.js index 8ac174d65774..05d111fdd3c3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var Float64Array = require( '@stdlib/array/float64' ); var gnansumpw = require( './../lib' ); @@ -121,7 +120,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -138,15 +136,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumpw( N, x, 2 ); + v = gnansumpw( 5, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -163,21 +159,32 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumpw( N, x, -2 ); + v = gnansumpw( 5, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumpw( x.length, x, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); @@ -185,7 +192,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -203,9 +209,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gnansumpw( N, x1, 2 ); + v = gnansumpw( 5, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.ndarray.js index 379228c45622..8ce44606fcb1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gnansumpw/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var gnansumpw = require( './../lib/ndarray.js' ); @@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = gnansumpw( N, x, 2, 0 ); + v = gnansumpw( 5, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -162,27 +158,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gnansumpw( N, x, -2, 8 ); + v = gnansumpw( 5, x, -2, 8 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gnansumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0` and the first element is NaN, the function returns 0', function test( t ) { + var x; + var v; + + x = [ NaN, -2.0, -4.0, 5.0, 3.0 ]; + + v = gnansumpw( x.length, x, 0, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -198,9 +204,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = gnansumpw( N, x, 2, 1 ); + v = gnansumpw( 5, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/README.md b/lib/node_modules/@stdlib/blas/ext/base/grev/README.md index a5b0319ad45c..15c6b56d9c06 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/README.md @@ -30,9 +30,9 @@ limitations under the License. var grev = require( '@stdlib/blas/ext/base/grev' ); ``` -#### grev( N, x, stride ) +#### grev( N, x, strideX ) -Reverses a strided array `x` in-place. +Reverses a strided array in-place. ```javascript var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; @@ -45,17 +45,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input array. -- **stride**: index increment. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to reverse every other element +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to reverse every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; -var N = floor( x.length / 2 ); -grev( N, x, 2 ); +grev( 4, x, 2 ); // x => [ -1.0, 1.0, 4.0, -5.0, 3.0, 0.0, -2.0, -3.0 ] ``` @@ -63,23 +60,21 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); // Initial array... var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); // Create an offset view... var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length/2 ); // Reverse every other element... -grev( N, x1, 2 ); +grev( 3, x1, 2 ); // x0 => [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ] ``` -#### grev.ndarray( N, x, stride, offset ) +#### grev.ndarray( N, x, strideX, offsetX ) -Reverses a strided array `x` in-place using alternative indexing semantics. +Reverses a strided array in-place using alternative indexing semantics. ```javascript var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; @@ -90,9 +85,9 @@ grev.ndarray( x.length, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of `x` +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: ```javascript var x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js index c33cfd3f85b1..ef86bbce04b9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -38,13 +38,9 @@ var grev = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100.0, 100.0, { + 'dtype': 'generic' + }); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js index 58cebefa6da5..aefe6de84251 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/benchmark/benchmark.ndarray.js @@ -21,11 +21,11 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; -var grev = require( './../lib/main.js' ).ndarray; +var grev = require( './../lib/ndarray.js' ); // FUNCTIONS // @@ -38,13 +38,9 @@ var grev = require( './../lib/main.js' ).ndarray; * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*20.0 ) - 10.0 ); - } + var x = uniform( len, -100.0, 100.0, { + 'dtype': 'generic' + }); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/grev/docs/repl.txt index 0d0044d38c57..f636ca039180 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Reverses a strided array in-place. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use typed array views. @@ -18,8 +18,8 @@ x: ArrayLikeObject Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. Returns ------- @@ -33,27 +33,25 @@ > {{alias}}( x.length, x, 1 ) [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2 ) + > {{alias}}( 3, x, 2 ) [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ] // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2 ) + > {{alias}}( 3, x1, 2 ) [ -6.0, 3.0, -4.0, 5.0, -2.0 ] > x0 [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ] -{{alias}}.ndarray( N, x, stride, offset ) +{{alias}}.ndarray( N, x, strideX, offsetX ) Reverses a strided array in-place using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -64,11 +62,11 @@ x: ArrayLikeObject Input array. - stride: integer - Index increment for `x`. + strideX: integer + Stride length. - offset: integer - Starting index of `x`. + offsetX: integer + Starting index. Returns ------- @@ -84,8 +82,7 @@ // Using an index offset: > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/grev/docs/types/index.d.ts index 762ecf267f56..ffa60cddb187 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -40,15 +40,15 @@ interface Routine { * grev( x.length, x, 1 ); * // x => [ -3.0, -1.0, 0.0, 4.0, -5.0, 3.0, 1.0, -2.0 ] */ - ( N: number, x: Collection, stride: number ): Collection; + ( N: number, x: Collection, strideX: number ): Collection; /** * Reverses a strided array in-place. using alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns `x` * * @example @@ -57,7 +57,7 @@ interface Routine { * grev.ndarray( x.length, x, 1, 0 ); * // x => [ -3.0, -1.0, 0.0, 4.0, -5.0, 3.0, 1.0, -2.0 ] */ - ndarray( N: number, x: Collection, stride: number, offset: number ): Collection; + ndarray( N: number, x: Collection, strideX: number, offsetX: number ): Collection; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns `x` * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/grev/lib/accessors.js index 386a2858e1f9..88d17d206c3a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/lib/accessors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/lib/accessors.js @@ -34,8 +34,8 @@ var floor = require( '@stdlib/math/base/special/floor' ); * @param {Object} x - input array object * @param {Collection} x.data - input array data * @param {Array} x.accessors - array element accessors -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Object} input array object * * @example @@ -63,7 +63,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); * var view = reinterpret64( x.data, 0 ); * // view => [ -1.0, -3.0, 4.0, 0.0, 3.0, -5.0, -2.0, 1.0 ] */ -function grev( N, x, stride, offset ) { +function grev( N, x, strideX, offsetX ) { var xbuf; var set; var get; @@ -81,14 +81,14 @@ function grev( N, x, stride, offset ) { set = x.accessors[ 1 ]; n = floor( N/2 ); - ix = offset; - iy = ix + ((N-1)*stride); + ix = offsetX; + iy = ix + ( ( N - 1 ) * strideX ); for ( i = 0; i < n; i++ ) { tmp = get( xbuf, ix ); set( xbuf, ix, get( xbuf, iy ) ); set( xbuf, iy, tmp ); - ix += stride; - iy -= stride; + ix += strideX; + iy -= strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/grev/lib/main.js index 1f5fa21f832f..4b78158809ab 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/lib/main.js @@ -20,14 +20,8 @@ // MODULES // -var floor = require( '@stdlib/math/base/special/floor' ); -var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); -var accessors = require( './accessors.js' ); - - -// VARIABLES // - -var M = 3; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -37,7 +31,7 @@ var M = 3; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {NumericArray} input array * * @example @@ -46,78 +40,8 @@ var M = 3; * grev( x.length, x, 1 ); * // x => [ -3.0, -1.0, 0.0, 4.0, -5.0, 3.0, 1.0, -2.0 ] */ -function grev( N, x, stride ) { - var tmp; - var ix; - var iy; - var o; - var m; - var n; - var i; - - if ( N <= 0 ) { - return x; - } - o = arraylike2object( x ); - if ( o.accessorProtocol ) { - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - accessors( N, o, stride, ix ); - return o.data; - } - n = floor( N/2 ); - - // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { - m = n % M; - iy = N - 1; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( ix = 0; ix < m; ix++ ) { - tmp = x[ ix ]; - x[ ix ] = x[ iy ]; - x[ iy ] = tmp; - iy -= 1; - } - } - if ( n < M ) { - return x; - } - for ( ix = m; ix < n; ix += M ) { - tmp = x[ ix ]; - x[ ix ] = x[ iy ]; - x[ iy ] = tmp; - - tmp = x[ ix+1 ]; - x[ ix+1 ] = x[ iy-1 ]; - x[ iy-1 ] = tmp; - - tmp = x[ ix+2 ]; - x[ ix+2 ] = x[ iy-2 ]; - x[ iy-2 ] = tmp; - - iy -= M; - } - return x; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - iy = ix + ((N-1)*stride); - for ( i = 0; i < n; i++ ) { - tmp = x[ ix ]; - x[ ix ] = x[ iy ]; - x[ iy ] = tmp; - ix += stride; - iy -= stride; - } - return x; +function grev( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/grev/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/grev/lib/ndarray.js index f798489b3087..e1330fa896c6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/grev/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/grev/lib/ndarray.js @@ -37,8 +37,8 @@ var M = 3; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {NumericArray} input array * * @example @@ -47,7 +47,7 @@ var M = 3; * grev( 3, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, -6.0, 5.0, -4.0 ] */ -function grev( N, x, stride, offset ) { +function grev( N, x, strideX, offsetX ) { var tmp; var ix; var iy; @@ -61,14 +61,14 @@ function grev( N, x, stride, offset ) { } o = arraylike2object( x ); if ( o.accessorProtocol ) { - accessors( N, o, stride, offset ); + accessors( N, o, strideX, offsetX ); return o.data; } n = floor( N/2 ); - ix = offset; + ix = offsetX; // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { + if ( strideX === 1 ) { m = n % M; iy = ix + N - 1; @@ -78,8 +78,8 @@ function grev( N, x, stride, offset ) { tmp = x[ ix ]; x[ ix ] = x[ iy ]; x[ iy ] = tmp; - ix += stride; - iy -= stride; + ix += strideX; + iy -= strideX; } } if ( n < M ) { @@ -103,13 +103,13 @@ function grev( N, x, stride, offset ) { } return x; } - iy = ix + ((N-1)*stride); + iy = ix + ( ( N - 1 ) * strideX ); for ( i = 0; i < n; i++ ) { tmp = x[ ix ]; x[ ix ] = x[ iy ]; x[ iy ] = tmp; - ix += stride; - iy -= stride; + ix += strideX; + iy -= strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/README.md index c02bc168f0ae..b8a8a8be14c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/README.md @@ -36,15 +36,14 @@ limitations under the License. var gsumkbn = require( '@stdlib/blas/ext/base/gsumkbn' ); ``` -#### gsumkbn( N, x, stride ) +#### gsumkbn( N, x, strideX ) Computes the sum of strided array elements using an improved Kahan–Babuška algorithm. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumkbn( N, x, 1 ); +var v = gsumkbn( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gsumkbn( N, x, 2 ); +var v = gsumkbn( 4, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gsumkbn( N, x1, 2 ); +var v = gsumkbn( 4, x1, 2 ); // returns 5.0 ``` -#### gsumkbn.ndarray( N, x, stride, offset ) +#### gsumkbn.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumkbn.ndarray( N, x, 1, 0 ); +var v = gsumkbn.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gsumkbn.ndarray( N, x, 2, 1 ); +var v = gsumkbn.ndarray( 4, x, 2, 1 ); // returns 5.0 ``` @@ -133,18 +122,12 @@ var v = gsumkbn.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumkbn = require( '@stdlib/blas/ext/base/gsumkbn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumkbn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js index 0ab2da088da9..727fad4f71c4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumkbn = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumkbn = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js index 80aff19d1300..3ef511ab4268 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumkbn = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumkbn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/repl.txt index 0ab5828a8982..11d7cb2b8d70 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,27 +34,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/types/index.d.ts index 6ca1865df3f3..792287095aeb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gsumkbn( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gsumkbn.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/examples/index.js index 489283d40505..ef0130017bab 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumkbn = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumkbn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/index.js index 2db0728b24cc..6f33c27a4566 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/index.js @@ -27,19 +27,16 @@ * var gsumkbn = require( '@stdlib/blas/ext/base/gsumkbn' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumkbn( N, x, 1 ); +* var v = gsumkbn( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gsumkbn = require( '@stdlib/blas/ext/base/gsumkbn' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumkbn.ndarray( N, x, 2, 1 ); +* var v = gsumkbn.ndarray( 4, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/main.js index c146bf68e92b..e6010846c835 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,49 +39,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumkbn( N, x, 1 ); +* var v = gsumkbn( x.length, x, 1 ); * // returns 1.0 */ -function gsumkbn( N, x, stride ) { - var sum; - var ix; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - c = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c += (sum-t) + v; - } else { - c += (v-t) + sum; - } - sum = t; - ix += stride; - } - return sum + c; +function gsumkbn( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/ndarray.js index 56a88141c8db..d5d61c0452fe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/lib/ndarray.js @@ -38,20 +38,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumkbn( N, x, 2, 1 ); +* var v = gsumkbn( 4, x, 2, 1 ); * // returns 5.0 */ -function gsumkbn( N, x, stride, offset ) { +function gsumkbn( N, x, strideX, offsetX ) { var sum; var ix; var v; @@ -62,10 +59,10 @@ function gsumkbn( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; sum = 0.0; c = 0.0; for ( i = 0; i < N; i++ ) { @@ -77,7 +74,7 @@ function gsumkbn( N, x, stride, offset ) { c += (v-t) + sum; } sum = t; - ix += stride; + ix += strideX; } return sum + c; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.main.js index 9fa8b96610ea..850eccf77999 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var gsumkbn = require( './../lib' ); @@ -95,7 +94,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -110,15 +108,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn( N, x, 2 ); + v = gsumkbn( 4, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -133,21 +129,20 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn( N, x, -2 ); + v = gsumkbn( 4, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumkbn( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); @@ -155,7 +150,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -171,9 +165,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gsumkbn( N, x1, 2 ); + v = gsumkbn( 4, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.ndarray.js index 3a8af0e63075..3eef113e18fc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var gsumkbn = require( './../lib/ndarray.js' ); @@ -94,7 +93,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -109,15 +107,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn( N, x, 2, 0 ); + v = gsumkbn( 4, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -132,27 +128,25 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn( N, x, -2, 6 ); + v = gsumkbn( 4, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumkbn( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -166,9 +160,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]; - N = floor( x.length / 2 ); - v = gsumkbn( N, x, 2, 1 ); + v = gsumkbn( 4, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/README.md index a5f21c5005fe..3b8154e30e0e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/README.md @@ -36,15 +36,14 @@ limitations under the License. var gsumkbn2 = require( '@stdlib/blas/ext/base/gsumkbn2' ); ``` -#### gsumkbn2( N, x, stride ) +#### gsumkbn2( N, x, strideX ) Computes the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumkbn2( N, x, 1 ); +var v = gsumkbn2( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gsumkbn2( N, x, 2 ); +var v = gsumkbn2( 4, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gsumkbn2( N, x1, 2 ); +var v = gsumkbn2( 4, x1, 2 ); // returns 5.0 ``` -#### gsumkbn2.ndarray( N, x, stride, offset ) +#### gsumkbn2.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumkbn2.ndarray( N, x, 1, 0 ); +var v = gsumkbn2.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gsumkbn2.ndarray( N, x, 2, 1 ); +var v = gsumkbn2.ndarray( 4, x, 2, 1 ); // returns 5.0 ``` @@ -133,18 +122,12 @@ var v = gsumkbn2.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumkbn2 = require( '@stdlib/blas/ext/base/gsumkbn2' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js index 26f6f9d82172..1e5bdccbb002 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumkbn2 = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumkbn2 = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js index df2d56c12dfd..46b132d35ac1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumkbn2 = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumkbn2 = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/repl.txt index a61b5a69caff..693e00569a99 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,27 +34,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/types/index.d.ts index d74432975d29..3261965b1b8d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gsumkbn2( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gsumkbn2.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/examples/index.js index 7f8d48c4ed46..717ced0c1ec2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumkbn2 = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumkbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/index.js index 5181d9324c48..0b453539d3af 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/index.js @@ -27,19 +27,16 @@ * var gsumkbn2 = require( '@stdlib/blas/ext/base/gsumkbn2' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumkbn2( N, x, 1 ); +* var v = gsumkbn2( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gsumkbn2 = require( '@stdlib/blas/ext/base/gsumkbn2' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumkbn2.ndarray( N, x, 2, 1 ); +* var v = gsumkbn2.ndarray( 4, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/main.js index a52edc223707..d453c794ded9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,61 +39,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumkbn2( N, x, 1 ); +* var v = gsumkbn2( x.length, x, 1 ); * // returns 1.0 */ -function gsumkbn2( N, x, stride ) { - var sum; - var ccs; - var ix; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = sum + v; - if ( abs( sum ) >= abs( v ) ) { - c = (sum-t) + v; - } else { - c = (v-t) + sum; - } - sum = t; - t = cs + c; - if ( abs( cs ) >= abs( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - ix += stride; - } - return sum + cs + ccs; +function gsumkbn2( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/ndarray.js index 595fa2b765ad..8f27c12b53e3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/lib/ndarray.js @@ -38,20 +38,17 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumkbn2( N, x, 2, 1 ); +* var v = gsumkbn2( 4, x, 2, 1 ); * // returns 5.0 */ -function gsumkbn2( N, x, stride, offset ) { +function gsumkbn2( N, x, strideX, offsetX ) { var sum; var ccs; var ix; @@ -65,10 +62,10 @@ function gsumkbn2( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; sum = 0.0; ccs = 0.0; // second order correction term for lost low order bits cs = 0.0; // first order correction term for lost low order bits @@ -89,7 +86,7 @@ function gsumkbn2( N, x, stride, offset ) { } cs = t; ccs += cc; - ix += stride; + ix += strideX; } return sum + cs + ccs; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.main.js index 55c146330eb6..53d5401653da 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var gsumkbn2 = require( './../lib' ); @@ -95,7 +94,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -110,15 +108,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn2( N, x, 2 ); + v = gsumkbn2( 4, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -133,21 +129,20 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn2( N, x, -2 ); + v = gsumkbn2( 4, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumkbn2( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); @@ -155,7 +150,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -171,9 +165,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gsumkbn2( N, x1, 2 ); + v = gsumkbn2( 4, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.ndarray.js index c238735b790c..a6b0b7f76d9a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumkbn2/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var gsumkbn2 = require( './../lib/ndarray.js' ); @@ -94,7 +93,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -109,15 +107,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn2( N, x, 2, 0 ); + v = gsumkbn2( 4, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -132,27 +128,25 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumkbn2( N, x, -2, 6 ); + v = gsumkbn2( 4, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumkbn2( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -166,9 +160,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]; - N = floor( x.length / 2 ); - v = gsumkbn2( N, x, 2, 1 ); + v = gsumkbn2( 4, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/gsumors/README.md index 5c9f837a28e0..e180a88b651e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/README.md @@ -36,15 +36,14 @@ limitations under the License. var gsumors = require( '@stdlib/blas/ext/base/gsumors' ); ``` -#### gsumors( N, x, stride ) +#### gsumors( N, x, strideX ) Computes the sum of strided array elements using ordinary recursive summation. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumors( N, x, 1 ); +var v = gsumors( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gsumors( N, x, 2 ); +var v = gsumors( 4, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gsumors( N, x1, 2 ); +var v = gsumors( 4, x1, 2 ); // returns 5.0 ``` -#### gsumors.ndarray( N, x, stride, offset ) +#### gsumors.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using ordinary recursive summation and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumors.ndarray( N, x, 1, 0 ); +var v = gsumors.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gsumors.ndarray( N, x, 2, 1 ); +var v = gsumors.ndarray( 4, x, 2, 1 ); // returns 5.0 ``` @@ -121,6 +110,7 @@ var v = gsumors.ndarray( N, x, 2, 1 ); - If `N <= 0`, both functions return `0.0`. - Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation is acceptable; in all other cases, exercise due caution. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). - Depending on the environment, the typed versions ([`dsumors`][@stdlib/blas/ext/base/dsumors], [`ssumors`][@stdlib/blas/ext/base/ssumors], etc.) are likely to be significantly more performant.
@@ -134,18 +124,12 @@ var v = gsumors.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumors = require( '@stdlib/blas/ext/base/gsumors' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumors( x.length, x, 1 ); @@ -183,6 +167,8 @@ console.log( v ); [mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + [@stdlib/blas/ext/base/dsumors]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dsumors diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js index e44baae57ada..8c8569fa7c1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumors = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumors = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js index 3137bb3c8756..e02cb4d4cf9f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/repl.txt index bc444de93ba4..4b70411c19f9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,27 +34,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using ordinary recursive summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,10 +62,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/index.d.ts index 49ef98625baf..b39d58be2a83 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/index.d.ts @@ -20,7 +20,12 @@ /// -import { NumericArray } from '@stdlib/types/array'; +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; /** * Interface describing `gsumors`. @@ -31,7 +36,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +45,15 @@ interface Routine { * var v = gsumors( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: InputArray, strideX: number ): number; /** * Computes the sum of strided array elements using ordinary recursive summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +62,7 @@ interface Routine { * var v = gsumors.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: InputArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +70,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/test.ts index eadcbc7e6605..6592dca8534b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/test.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/docs/types/test.ts @@ -16,6 +16,7 @@ * limitations under the License. */ +import AccessorArray = require( '@stdlib/array/base/accessor' ); import gsumors = require( './index' ); @@ -26,6 +27,7 @@ import gsumors = require( './index' ); const x = new Float64Array( 10 ); gsumors( x.length, x, 1 ); // $ExpectType number + gsumors( x.length, new AccessorArray( x ), 1 ); // $ExpectType number } // The compiler throws an error if the function is provided a first argument which is not a number... @@ -85,6 +87,7 @@ import gsumors = require( './index' ); const x = new Float64Array( 10 ); gsumors.ndarray( x.length, x, 1, 0 ); // $ExpectType number + gsumors.ndarray( x.length, new AccessorArray( x ), 1, 0 ); // $ExpectType number } // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/examples/index.js index 10b952560fd5..b07cc49084ce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumors = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/accessors.js new file mode 100644 index 000000000000..67771275a2a7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/accessors.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Computes the sum of strided array elements using ordinary recursive summation. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {number} sum +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = toAccessorArray( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* +* var v = gsumors( 4, arraylike2object( x ), 2, 1 ); +* // returns 5.0 +*/ +function gsumors( N, x, strideX, offsetX ) { + var xbuf; + var get; + var ix; + var s; + var i; + + // Cache reference to array data: + xbuf = x.data; + + // Cache a reference to the element accessor: + get = x.accessors[ 0 ]; + + ix = offsetX; + if ( strideX === 0 ) { + return N * get( xbuf, ix ); + } + s = 0.0; + for ( i = 0; i < N; i++ ) { + s += get( xbuf, ix ); + ix += strideX; + } + return s; +} + + +// EXPORTS // + +module.exports = gsumors; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/index.js index 5a179a1ff795..a3638810c056 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/index.js @@ -27,19 +27,16 @@ * var gsumors = require( '@stdlib/blas/ext/base/gsumors' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumors( N, x, 1 ); +* var v = gsumors( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gsumors = require( '@stdlib/blas/ext/base/gsumors' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumors.ndarray( N, x, 2, 1 ); +* var v = gsumors.ndarray( 4, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/main.js index c9f5d676000c..83c47f0a9373 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/main.js @@ -18,9 +18,10 @@ 'use strict'; -// VARIABLES // +// MODULES // -var M = 6; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,57 +31,17 @@ var M = 6; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumors( N, x, 1 ); +* var v = gsumors( x.length, x, 1 ); * // returns 1.0 */ -function gsumors( N, x, stride ) { - var ix; - var m; - var s; - var i; - - s = 0.0; - if ( N <= 0 ) { - return s; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - // If the stride is equal to `1`, use unrolled loops... - if ( stride === 1 ) { - m = N % M; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - s += x[ i ]; - } - } - if ( N < M ) { - return s; - } - for ( i = m; i < N; i += M ) { - s += x[i] + x[i+1] + x[i+2] + x[i+3] + x[i+4] + x[i+5]; - } - return s; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - s += x[ ix ]; - ix += stride; - } - return s; +function gsumors( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/ndarray.js index 7cfa91e0e46f..2e9db4e54743 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/lib/ndarray.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + // VARIABLES // var M = 6; @@ -30,43 +36,45 @@ var M = 6; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumors( N, x, 2, 1 ); +* var v = gsumors( 4, x, 2, 1 ); * // returns 5.0 */ -function gsumors( N, x, stride, offset ) { +function gsumors( N, x, strideX, offsetX ) { var ix; var m; var s; + var o; var i; s = 0.0; if ( N <= 0 ) { return s; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + return accessors( N, o, strideX, offsetX ); + } + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; // If the stride is equal to `1`, use unrolled loops... - if ( stride === 1 ) { + if ( strideX === 1 ) { m = N % M; // If we have a remainder, run a clean-up loop... if ( m > 0 ) { for ( i = 0; i < m; i++ ) { s += x[ ix ]; - ix += stride; + ix += strideX; } } if ( N < M ) { @@ -80,7 +88,7 @@ function gsumors( N, x, stride, offset ) { } for ( i = 0; i < N; i++ ) { s += x[ ix ]; - ix += stride; + ix += strideX; } return s; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.main.js index 376ffe054bce..c71faee0cba2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.main.js @@ -21,8 +21,8 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); var Float64Array = require( '@stdlib/array/float64' ); var gsumors = require( './../lib' ); @@ -67,6 +67,33 @@ tape( 'the function calculates the sum of all strided array elements', function t.end(); }); +tape( 'the function calculates the sum of all strided array elements (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0, 0.0, -3.0, 3.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, -8.0, 'returns expected value' ); + + x = [ NaN, 4.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ 1.0, 1.0e100, 1.0, -1.0e100 ]; + v = gsumors( x.length, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0.0`', function test( t ) { var x; var v; @@ -95,7 +122,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -110,15 +136,34 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumors( N, x, 2 ); + v = gsumors( 4, x, 2 ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + v = gsumors( 4, toAccessorArray( x ), 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -133,21 +178,41 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumors( N, x, -2 ); + v = gsumors( 4, x, -2 ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = gsumors( 4, toAccessorArray( x ), -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumors( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); @@ -155,7 +220,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -171,9 +235,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gsumors( N, x1, 2 ); + v = gsumors( 4, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.ndarray.js index 6ab3872f7900..37597eeb8456 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumors/test/test.ndarray.js @@ -21,8 +21,8 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); var gsumors = require( './../lib/ndarray.js' ); @@ -66,6 +66,33 @@ tape( 'the function calculates the sum of all strided array elements', function t.end(); }); +tape( 'the function calculates the sum of all strided array elements (accessors)', function test( t ) { + var x; + var v; + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0, 0.0, -3.0, 3.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 3.0, 'returns expected value' ); + + x = [ -4.0, -4.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, -8.0, 'returns expected value' ); + + x = [ NaN, 4.0 ]; + v = gsumors( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ 1.0, 1.0e100, 1.0, -1.0e100 ]; + v = gsumors( x.length, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0.0`', function test( t ) { var x; var v; @@ -94,7 +121,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -109,15 +135,34 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumors( N, x, 2, 0 ); + v = gsumors( 4, x, 2, 0 ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + v = gsumors( 4, toAccessorArray( x ), 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -132,27 +177,46 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumors( N, x, -2, 6 ); + v = gsumors( 4, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = gsumors( 4, toAccessorArray( x ), -2, 6 ); + + t.strictEqual( v, 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumors( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -166,9 +230,29 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]; - N = floor( x.length / 2 ); - v = gsumors( N, x, 2, 1 ); + v = gsumors( 4, x, 2, 1 ); + t.strictEqual( v, 5.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + + v = gsumors( 4, toAccessorArray( x ), 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/README.md index 6761c1510b75..6180eba328e2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/README.md @@ -36,15 +36,14 @@ limitations under the License. var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ); ``` -#### gsumpw( N, x, stride ) +#### gsumpw( N, x, strideX ) Computes the sum of strided array elements using pairwise summation. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumpw( N, x, 1 ); +var v = gsumpw( x.length, x, 1 ); // returns 1.0 ``` @@ -52,17 +51,14 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the gsumpw of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ]; -var N = floor( x.length / 2 ); -var v = gsumpw( N, x, 2 ); +var v = gsumpw( 4, x, 2 ); // returns 5.0 ``` @@ -72,42 +68,35 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = gsumpw( N, x1, 2 ); +var v = gsumpw( 4, x1, 2 ); // returns 5.0 ``` -#### gsumpw.ndarray( N, x, stride, offset ) +#### gsumpw.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using pairwise summation and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, 2.0 ]; -var N = x.length; -var v = gsumpw.ndarray( N, x, 1, 0 ); +var v = gsumpw.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other element starting from the second element: ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = gsumpw.ndarray( N, x, 2, 1 ); +var v = gsumpw.ndarray( 4, x, 2, 1 ); // returns 5.0 ``` @@ -134,18 +123,12 @@ var v = gsumpw.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.js index 0cbbdae1f151..1d11248c7631 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumpw = require( './../lib/main.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumpw = require( './../lib/main.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.ndarray.js index 3d59be8f2eb5..8fe3f267e2bd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/benchmark/benchmark.ndarray.js @@ -21,13 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var gsumpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var gsumpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - x.push( ( randu()*10.0 ) - 20.0 ); - } + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/repl.txt index 2defa985eb45..822329805f51 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of strided array elements using pairwise summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -18,8 +18,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -33,27 +33,24 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -1.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of strided array elements using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -64,10 +61,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -84,8 +81,7 @@ // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -1.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/types/index.d.ts index ba4683be6b7d..aad0cc753de4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/docs/types/index.d.ts @@ -31,7 +31,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -40,15 +40,15 @@ interface Routine { * var v = gsumpw( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: NumericArray, stride: number ): number; + ( N: number, x: NumericArray, strideX: number ): number; /** * Computes the sum of strided array elements using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = gsumpw.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, x: NumericArray, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/examples/index.js index 77e2022e86cb..51bf4f8a69ce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var gsumpw = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); console.log( x ); var v = gsumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/index.js index c62ccbdee843..229a4b11a815 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/index.js @@ -27,19 +27,16 @@ * var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ); * * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumpw( N, x, 1 ); +* var v = gsumpw( x.length, x, 1 ); * // returns 1.0 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumpw.ndarray( N, x, 2, 1 ); +* var v = gsumpw.ndarray( 4, x, 2, 1 ); * // returns 5.0 */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/main.js index a82cda55ae36..da5e4fbbc04a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/main.js @@ -20,7 +20,8 @@ // MODULES // -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,42 +39,17 @@ var sum = require( './ndarray.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var x = [ 1.0, -2.0, 2.0 ]; -* var N = x.length; * -* var v = gsumpw( N, x, 1 ); +* var v = gsumpw( x.length, x, 1 ); * // returns 1.0 */ -function gsumpw( N, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - s += x[ ix ]; - ix += stride; - } - return s; - } - return sum( N, x, stride, ix ); +function gsumpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/ndarray.js index 04c36cde0078..6c433c5d65f9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/lib/ndarray.js @@ -44,20 +44,17 @@ var BLOCKSIZE = 128; * * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -* var N = floor( x.length / 2 ); * -* var v = gsumpw( N, x, 2, 1 ); +* var v = gsumpw( 4, x, 2, 1 ); * // returns 5.0 */ -function gsumpw( N, x, stride, offset ) { +function gsumpw( N, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -75,57 +72,57 @@ function gsumpw( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + ix = offsetX; + if ( strideX === 0 ) { + return N * x[ ix ]; } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; for ( i = 0; i < N; i++ ) { s += x[ ix ]; - ix += stride; + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... s0 = x[ ix ]; - s1 = x[ ix+stride ]; - s2 = x[ ix+(2*stride) ]; - s3 = x[ ix+(3*stride) ]; - s4 = x[ ix+(4*stride) ]; - s5 = x[ ix+(5*stride) ]; - s6 = x[ ix+(6*stride) ]; - s7 = x[ ix+(7*stride) ]; - ix += 8 * stride; + s1 = x[ ix+strideX ]; + s2 = x[ ix+(2*strideX) ]; + s3 = x[ ix+(3*strideX) ]; + s4 = x[ ix+(4*strideX) ]; + s5 = x[ ix+(5*strideX) ]; + s6 = x[ ix+(6*strideX) ]; + s7 = x[ ix+(7*strideX) ]; + ix += 8 * strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { s0 += x[ ix ]; - s1 += x[ ix+stride ]; - s2 += x[ ix+(2*stride) ]; - s3 += x[ ix+(3*stride) ]; - s4 += x[ ix+(4*stride) ]; - s5 += x[ ix+(5*stride) ]; - s6 += x[ ix+(6*stride) ]; - s7 += x[ ix+(7*stride) ]; - ix += 8 * stride; + s1 += x[ ix+strideX ]; + s2 += x[ ix+(2*strideX) ]; + s3 += x[ ix+(3*strideX) ]; + s4 += x[ ix+(4*strideX) ]; + s5 += x[ ix+(5*strideX) ]; + s6 += x[ ix+(6*strideX) ]; + s7 += x[ ix+(7*strideX) ]; + ix += 8 * strideX; } // Pairwise sum the accumulators: - s = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); + s = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); // Clean-up loop... for ( i; i < N; i++ ) { s += x[ ix ]; - ix += stride; + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return gsumpw( n, x, stride, ix ) + gsumpw( N-n, x, stride, ix+(n*stride) ); + return gsumpw( n, x, strideX, ix ) + gsumpw( N-n, x, strideX, ix+(n*strideX) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.main.js index ff9f6391d9f6..2aea27f8afbd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.main.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var gsumpw = require( './../lib' ); @@ -103,7 +102,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -118,15 +116,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumpw( N, x, 2 ); + v = gsumpw( 4, x, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -141,21 +137,20 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumpw( N, x, -2 ); + v = gsumpw( 4, x, -2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); @@ -163,7 +158,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -179,9 +173,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = gsumpw( N, x1, 2 ); + v = gsumpw( 4, x1, 2 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.ndarray.js index ce8a24431dea..021815a2a0cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gsumpw/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var gsumpw = require( './../lib/ndarray.js' ); @@ -102,7 +101,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -117,15 +115,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]; - N = floor( x.length / 2 ); - v = gsumpw( N, x, 2, 0 ); + v = gsumpw( 4, x, 2, 0 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -140,27 +136,25 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]; - N = floor( x.length / 2 ); - v = gsumpw( N, x, -2, 6 ); + v = gsumpw( 4, x, -2, 6 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ]; v = gsumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -174,9 +168,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]; - N = floor( x.length / 2 ); - v = gsumpw( N, x, 2, 1 ); + v = gsumpw( 4, x, 2, 1 ); t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md index d5021571d5ea..438f5be61036 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/README.md @@ -20,7 +20,7 @@ limitations under the License. # sapx -> Add a constant to each element in a single-precision floating-point strided array. +> Add a scalar constant to each element in a single-precision floating-point strided array.
@@ -30,9 +30,9 @@ limitations under the License. var sapx = require( '@stdlib/blas/ext/base/sapx' ); ``` -#### sapx( N, alpha, x, stride ) +#### sapx( N, alpha, x, strideX ) -Adds a constant `alpha` to each element in a single-precision floating-point strided array `x`. +Adds a scalar constant to each element in a single-precision floating-point strided array. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -48,9 +48,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment. +- **strideX**: stride length. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to add a constant to every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -77,9 +77,9 @@ sapx( 3, 5.0, x1, 2 ); // x0 => [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] ``` -#### sapx.ndarray( N, alpha, x, stride, offset ) +#### sapx.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant `alpha` to each element in a single-precision floating-point strided array `x` using alternative indexing semantics. +Adds a scalar constant to each element in a single-precision floating-point strided array using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -92,9 +92,9 @@ sapx.ndarray( x.length, 5.0, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -126,11 +126,12 @@ sapx.ndarray( 3, 5.0, x, 1, x.length-3 ); ```javascript -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapx = require( '@stdlib/blas/ext/base/sapx' ); -var x = filledarrayBy( 10, 'float32', uniform( -100.0, 100.0 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); sapx( x.length, 5.0, x, 1 ); @@ -141,6 +142,125 @@ console.log( x ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sapx.h" +``` + +#### stdlib_strided_sapx( N, alpha, \*X, strideX ) + +Adds a scalar constant to each element in a single-precision floating-point strided array. + +```c +float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +stdlib_strided_sapx( 4, 5.0f, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_sapx( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sapx_ndarray( N, alpha, \*X, strideX, offsetX ) + +Adds a scalar constant to each element in a single-precision floating-point strided array using alternative indexing semantics. + +```c +float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +stdlib_strided_sapx_ndarray( 4, 5.0f, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_sapx_ndarray( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sapx.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Add a constant to each element: + stdlib_strided_sapx( N, 5.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js index ffd0ff4adca6..8f3b1f96a94a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapx = require( './../lib/sapx.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js index c0d5da977159..86badb8b1007 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapx = tryRequire( resolve( __dirname, './../lib/sapx.native.js' ) ); var opts = { 'skip': ( sapx instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js index b98d981d2b07..50c4b3da2e68 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapx = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js index 650ac428642a..d0963eedb4e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapx = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sapx instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/c/benchmark.length.c index 0b4366bbe756..ae841c296048 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; double t; @@ -105,7 +105,40 @@ static double benchmark( int iterations, int len ) { } t = tic(); for ( i = 0; i < iterations; i++ ) { - c_sapx( len, 5.0f, x, 1 ); + // cppcheck-suppress uninitvar + stdlib_strided_sapx( len, 5.0f, x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_sapx_ndarray( len, 5.0f, x, 1, 0 ); if ( x[ 0 ] != x[ 0 ] ) { printf( "should not return NaN\n" ); break; @@ -140,7 +173,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt index 42e084cc080c..f62676a59287 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/repl.txt @@ -1,7 +1,7 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each element in a single-precision floating-point strided - array. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each element in a single-precision floating-point + strided array. The `N` and stride parameters determine which elements in the strided array are accessed at runtime. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,7 +37,7 @@ > {{alias}}( x.length, 5.0, x, 1 ) [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); > {{alias}}( 3, 5.0, x, 2 ) [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ] @@ -51,13 +51,13 @@ [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ] -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each element in a single-precision floating-point strided - array using alternative indexing semantics. +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each element in a single-precision floating-point + strided array using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameter supports indexing semantics based on a starting + index. Parameters ---------- @@ -65,15 +65,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/types/index.d.ts index 7d857c2b98d9..a3ff0738d11c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/docs/types/index.d.ts @@ -23,12 +23,12 @@ */ interface Routine { /** - * Adds a constant to each element in a single-precision floating-point strided array. + * Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns `x` * * @example @@ -39,16 +39,16 @@ interface Routine { * sapx( x.length, 5.0, x, 1 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ - ( N: number, alpha: number, x: Float32Array, stride: number ): Float32Array; + ( N: number, alpha: number, x: Float32Array, strideX: number ): Float32Array; /** - * Adds a constant to each element in a single-precision floating-point strided array using alternative indexing semantics. + * Adds a scalar constant to each element in a single-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns `x` * * @example @@ -59,16 +59,16 @@ interface Routine { * sapx.ndarray( x.length, 5.0, x, 1, 0 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ - ndarray( N: number, alpha: number, x: Float32Array, stride: number, offset: number ): Float32Array; + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; } /** -* Adds a constant to each element in a single-precision floating-point strided array. +* Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns `x` * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/c/example.c index d92581131043..b1e0e48c8206 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/c/example.c @@ -21,16 +21,16 @@ int main( void ) { // Create a strided array: - float x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - int N = 8; + // Specify the number of indexed elements: + const int N = 8; // Specify a stride: - int strideX = 1; + const int strideX = 1; // Add a constant to each element: - c_sapx( N, 5.0f, x, strideX ); + stdlib_strided_sapx( N, 5.0f, x, strideX ); // Print the result: for ( int i = 0; i < 8; i++ ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js index 3e9bf3a73c87..2460d9142b8e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/examples/index.js @@ -18,12 +18,12 @@ 'use strict'; -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapx = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', uniform( -100.0, 100.0 ) ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); sapx( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/include/stdlib/blas/ext/base/sapx.h b/lib/node_modules/@stdlib/blas/ext/base/sapx/include/stdlib/blas/ext/base/sapx.h index 91ed15d0035a..1ef08133e787 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/include/stdlib/blas/ext/base/sapx.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/include/stdlib/blas/ext/base/sapx.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SAPX_H #define STDLIB_BLAS_EXT_BASE_SAPX_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -29,9 +29,14 @@ extern "C" { #endif /** -* Adds a constant to each element in a single-precision floating-point strided array. +* Adds a scalar constant to each element in a single-precision floating-point strided array. */ -void c_sapx( const int64_t N, const float alpha, float *X, const int64_t stride ); +void API_SUFFIX(stdlib_strided_sapx)( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX ); + +/** +* Adds a scalar constant to each element in a single-precision floating-point strided array using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_sapx_ndarray)( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/index.js index 1428e568d469..35147f913034 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each element in a single-precision floating-point strided array. +* Add a scalar constant to each element in a single-precision floating-point strided array. * * @module @stdlib/blas/ext/base/sapx * diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.js index 85ec6e02d6e4..90a8da4d6790 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.js @@ -26,25 +26,24 @@ var M = 5; // MAIN // /** -* Adds a constant to each element in a single-precision floating-point strided array. +* Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - scalar +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Float32Array} input array * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); -* var alpha = 5.0; * -* sapx( 3, alpha, x, 1, x.length-3 ); +* sapx( 3, 5.0, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, 1.0, 10.0, -1.0 ] */ -function sapx( N, alpha, x, stride, offset ) { +function sapx( N, alpha, x, strideX, offsetX ) { var ix; var m; var i; @@ -52,17 +51,17 @@ function sapx( N, alpha, x, stride, offset ) { if ( N <= 0 || alpha === 0.0 ) { return x; } - ix = offset; + ix = offsetX; // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { + if ( strideX === 1 ) { m = N % M; // If we have a remainder, run a clean-up loop... if ( m > 0 ) { for ( i = 0; i < m; i++ ) { x[ ix ] += alpha; - ix += stride; + ix += strideX; } } if ( N < M ) { @@ -80,7 +79,7 @@ function sapx( N, alpha, x, stride, offset ) { } for ( i = 0; i < N; i++ ) { x[ ix ] += alpha; - ix += stride; + ix += strideX; } return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.native.js index 21a3eee655e9..efaff76ccd2d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/ndarray.native.js @@ -20,37 +20,31 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './sapx.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each element in a single-precision floating-point strided array. +* Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - scalar +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - index increment -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {Float32Array} input array * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); -* var alpha = 5.0; * -* sapx( 3, alpha, x, 1, x.length-3 ); +* sapx( 3, 5.0, x, 1, x.length-3 ); * // x => [ 1.0, -2.0, 3.0, 1.0, 10.0, -1.0 ] */ -function sapx( N, alpha, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - addon( N, alpha, view, stride ); +function sapx( N, alpha, x, strideX, offsetX ) { + addon.ndarray( N, alpha, x, strideX, offsetX ); return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.js index 16d0874abb34..80f34e493382 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.js @@ -18,20 +18,21 @@ 'use strict'; -// VARIABLES // +// MODULES // -var M = 5; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each element in a single-precision floating-point strided array. +* Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - scalar +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {Float32Array} input array * * @example @@ -42,46 +43,8 @@ var M = 5; * sapx( x.length, 5.0, x, 1 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ -function sapx( N, alpha, x, stride ) { - var ix; - var i; - var m; - - if ( N <= 0 || alpha === 0.0 ) { - return x; - } - // Use loop unrolling if the stride is equal to `1`... - if ( stride === 1 ) { - m = N % M; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - x[ i ] += alpha; - } - } - if ( N < M ) { - return x; - } - for ( i = m; i < N; i += M ) { - x[ i ] += alpha; - x[ i+1 ] += alpha; - x[ i+2 ] += alpha; - x[ i+3 ] += alpha; - x[ i+4 ] += alpha; - } - return x; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - x[ ix ] += alpha; - ix += stride; - } - return x; +function sapx( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.native.js index 5d44d3d8a12a..d48177ff9009 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/lib/sapx.native.js @@ -26,12 +26,12 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each element in a single-precision floating-point strided array. +* Adds a scalar constant to each element in a single-precision floating-point strided array. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - scalar +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - index increment +* @param {integer} strideX - stride length * @returns {Float32Array} input array * * @example @@ -42,8 +42,8 @@ var addon = require( './../src/addon.node' ); * sapx( x.length, 5.0, x, 1 ); * // x => [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ] */ -function sapx( N, alpha, x, stride ) { - addon( N, alpha, x, stride ); +function sapx( N, alpha, x, strideX ) { + addon( N, alpha, x, strideX ); return x; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sapx/manifest.json index 7cef12cf17e3..10733716c85b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/manifest.json @@ -28,50 +28,52 @@ { "task": "build", "src": [ - "./src/sapx.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-float", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] }, { "task": "benchmark", "src": [ - "./src/sapx.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", "src": [ - "./src/sapx.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/package.json b/lib/node_modules/@stdlib/blas/ext/base/sapx/package.json index f67f02f104bf..be34a4c10c5e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/sapx", "version": "0.0.0", - "description": "Add a constant to each element in a single-precision floating-point strided array.", + "description": "Add a scalar constant to each element in a single-precision floating-point strided array.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.c index 9acbeab3ad06..38b9d492a592 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/blas/ext/base/sapx.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,10 +36,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ) - c_sapx( N, alpha, X, strideX ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_sapx)( N, alpha, X, strideX ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_sapx_ndarray)( N, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/main.c new file mode 100644 index 000000000000..9a1d3480fac7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/main.c @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapx.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Adds a scalar constant to each element in a single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_sapx)( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_sapx_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Adds a scalar constant to each element in a single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_sapx_ndarray)( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 || alpha == 0.0 ) { + return; + } + ix = offsetX; + + // Use loop unrolling if the stride is equal to `1`... + if ( strideX == 1 ) { + m = N % 5; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + X[ ix ] += alpha; + ix += strideX; + } + } + if ( N < 5 ) { + return; + } + for ( i = m; i < N; i += 5 ) { + X[ ix ] += alpha; + X[ ix+1 ] += alpha; + X[ ix+2 ] += alpha; + X[ ix+3 ] += alpha; + X[ ix+4 ] += alpha; + ix += 5; + } + return; + } + for ( i = 0; i < N; i++ ) { + X[ ix ] += alpha; + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapx/src/sapx.c b/lib/node_modules/@stdlib/blas/ext/base/sapx/src/sapx.c deleted file mode 100644 index 2771b85c8023..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/sapx/src/sapx.c +++ /dev/null @@ -1,70 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/sapx.h" -#include - -/** -* Adds a constant to each element in a single-precision floating-point strided array. -* -* @param N number of indexed elements -* @param alpha scalar -* @param X input array -* @param stride index increment -*/ -void c_sapx( const int64_t N, const float alpha, float *X, const int64_t stride ) { - int64_t ix; - int64_t m; - int64_t i; - - if ( N <= 0 || alpha == 0.0 ) { - return; - } - // Use loop unrolling if the stride is equal to `1`... - if ( stride == 1 ) { - m = N % 5; - - // If we have a remainder, run a clean-up loop... - if ( m > 0 ) { - for ( i = 0; i < m; i++ ) { - X[ i ] += alpha; - } - } - if ( N < 5 ) { - return; - } - for ( i = m; i < N; i += 5 ) { - X[ i ] += alpha; - X[ i+1 ] += alpha; - X[ i+2 ] += alpha; - X[ i+3 ] += alpha; - X[ i+4 ] += alpha; - } - return; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - for ( i = 0; i < N; i++ ) { - X[ ix ] += alpha; - ix += stride; - } - return; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md index 3b335687ccc9..532dfbc81f39 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/README.md @@ -20,7 +20,7 @@ limitations under the License. # sapxsum -> Add a constant to each single-precision floating-point strided array element and compute the sum. +> Add a scalar constant to each single-precision floating-point strided array element and compute the sum.
@@ -36,27 +36,27 @@ limitations under the License. var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ); ``` -#### sapxsum( N, alpha, x, stride ) +#### sapxsum( N, alpha, x, strideX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sapxsum( N, 5.0, x, 1 ); +var v = sapxsum( x.length, 5.0, x, 1 ); // returns 16.0 ``` The function has the following parameters: - **N**: number of indexed elements. +- **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -81,25 +81,24 @@ var v = sapxsum( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### sapxsum.ndarray( N, alpha, x, stride, offset ) +#### sapxsum.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sapxsum.ndarray( N, 5.0, x, 1, 0 ); +var v = sapxsum.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -131,18 +130,141 @@ var v = sapxsum.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var v = sapxsum( x.length, 5.0, x, 1 ); +console.log( v ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sapxsum.h" +``` + +#### stdlib_strided_sapxsum( N, alpha, \*X, strideX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsum( 4, 5.0f, x, 1 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_sapxsum( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sapxsum_ndarray( N, alpha, \*X, strideX, offsetX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsum_ndarray( 4, 5.0f, x, 1, 0 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_sapxsum_ndarray( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sapxsum.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the sum: + float v = stdlib_strided_sapxsum( N, 5.0f, x, strideX ); + + // Print the result: + printf( "Sum: %f\n", v ); +} ```
+
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js index a3794363584e..b57b2cc0bb94 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.js @@ -23,15 +23,16 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var pkg = require( './../package.json' ).name; var sapxsum = require( './../lib/sapxsum.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js index f850b14b21dc..e6410b84f568 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.native.js @@ -24,8 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +35,9 @@ var sapxsum = tryRequire( resolve( __dirname, './../lib/sapxsum.native.js' ) ); var opts = { 'skip': ( sapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js index 8197e74a9950..e349ef03d0f6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.js @@ -23,15 +23,16 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var pkg = require( './../package.json' ).name; var sapxsum = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js index ad9b898716e7..7421e9af74e7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/benchmark.ndarray.native.js @@ -24,8 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,7 +35,9 @@ var sapxsum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sapxsum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/c/benchmark.length.c index be5d510f7f2d..1d2520397265 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sapxsum( len, 5.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sapxsum_ndarray( len, 5.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt index b277320a58d3..fe8db2f64e4f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each single-precision floating-point strided array +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. - The `N` and stride parameters determine which elements in the strided - array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -49,13 +49,13 @@ 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each single-precision floating-point strided array +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the offset parameter supports indexing semantics based on a - starting index. + buffer, the offset parameter supports indexing semantics based on a starting + index. Parameters ---------- @@ -63,15 +63,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/types/index.d.ts index ba777172f308..4cd0ee7d6f30 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/docs/types/index.d.ts @@ -23,12 +23,12 @@ */ interface Routine { /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -39,16 +39,16 @@ interface Routine { * var v = sapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: Float32Array, stride: number ): number; + ( N: number, alpha: number, x: Float32Array, strideX: number ): number; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = sapxsum.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/c/example.c index d77ef9e37850..25cf72b30d14 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/c/example.c @@ -17,22 +17,21 @@ */ #include "stdlib/blas/ext/base/sapxsum.h" -#include #include int main( void ) { // Create a strided array: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - const int64_t N = 4; + // Specify the number of indexed elements: + const int N = 8; - // Specify the stride length: - const int64_t stride = 2; + // Specify a stride: + const int strideX = 1; // Compute the sum: - float v = stdlib_strided_sapxsum( N, 5.0f, x, stride ); + float v = stdlib_strided_sapxsum( N, 5.0f, x, strideX ); // Print the result: - printf( "sum: %f\n", v ); + printf( "Sum: %f\n", v ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js index 9dffd93b0fc8..a188ecdfb3d4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsum = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsum( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include/stdlib/blas/ext/base/sapxsum.h b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include/stdlib/blas/ext/base/sapxsum.h index 2ffe1d15b422..90ef9a49a33e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include/stdlib/blas/ext/base/sapxsum.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/include/stdlib/blas/ext/base/sapxsum.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SAPXSUM_H #define STDLIB_BLAS_EXT_BASE_SAPXSUM_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. */ -float stdlib_strided_sapxsum( const int64_t N, const float alpha, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sapxsum)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sapxsum_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/index.js index 4b3299cf1b73..8ffd46a53178 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each single-precision floating-point strided array element and compute the sum. +* Add a scalar constant to each single-precision floating-point strided array element and compute the sum. * * @module @stdlib/blas/ext/base/sapxsum * @@ -28,9 +28,8 @@ * var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsum( N, 5.0, x, 1 ); +* var v = sapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.js index a1aa827fe731..f91439d0ee00 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.js @@ -26,13 +26,13 @@ var sapxsumkbn = require( '@stdlib/blas/ext/base/sapxsumkbn' ).ndarray; // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -43,8 +43,8 @@ var sapxsumkbn = require( '@stdlib/blas/ext/base/sapxsumkbn' ).ndarray; * var v = sapxsum( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsum( N, alpha, x, stride, offset ) { - return sapxsumkbn( N, alpha, x, stride, offset ); +function sapxsum( N, alpha, x, strideX, offsetX ) { + return sapxsumkbn( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.native.js index 3eea08a9333a..e8c4ec754704 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/ndarray.native.js @@ -20,21 +20,19 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './sapxsum.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -45,11 +43,8 @@ var addon = require( './sapxsum.native.js' ); * var v = sapxsum( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsum( N, alpha, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - return addon( N, alpha, view, stride ); +function sapxsum( N, alpha, x, strideX, offsetX ) { + return addon.ndarray( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.js index 383db5413bf4..68082e4277ce 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.js @@ -20,31 +20,31 @@ // MODULES // -var sapxsumkbn = require( '@stdlib/blas/ext/base/sapxsumkbn' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsum( N, 5.0, x, 1 ); +* var v = sapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsum( N, alpha, x, stride ) { - return sapxsumkbn( N, alpha, x, stride ); +function sapxsum( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.native.js index d8883d0be826..747599450c73 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/lib/sapxsum.native.js @@ -26,25 +26,24 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsum( N, 5.0, x, 1 ); +* var v = sapxsum( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsum( N, alpha, x, stride ) { - return addon( N, alpha, x, stride ); +function sapxsum( N, alpha, x, strideX ) { + return addon( N, alpha, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/manifest.json index c4a950608abe..73be58e72bc1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/manifest.json @@ -28,14 +28,12 @@ { "task": "build", "src": [ - "./src/sapxsum.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/blas/ext/base/sapxsumkbn", @@ -43,39 +41,42 @@ "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-strided-float32array", - "@stdlib/napi/argv-float" + "@stdlib/napi/argv-float", + "@stdlib/napi/create-double", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/sapxsum.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/sapxsumkbn" + "@stdlib/blas/ext/base/sapxsumkbn", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "examples", "src": [ - "./src/sapxsum.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/sapxsumkbn" + "@stdlib/blas/ext/base/sapxsumkbn", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] } ] diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.c index 551bdd7ef326..fd0e466b19b7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/addon.c @@ -17,13 +17,14 @@ */ #include "stdlib/blas/ext/base/sapxsum.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_float.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -38,12 +39,26 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsum)( N, alpha, X, strideX ), v ); + return v; +} - napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_sapxsum( N, alpha, X, strideX ), &v ); - assert( status == napi_ok ); - +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsum_ndarray)( N, alpha, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/main.c new file mode 100644 index 000000000000..918b2fb6a69f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/main.c @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsum.h" +#include "stdlib/blas/ext/base/sapxsumkbn.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsum)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sapxsum_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsum_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return API_SUFFIX(stdlib_strided_sapxsumkbn_ndarray)( N, alpha, X, strideX, offsetX ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/sapxsum.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/sapxsum.c deleted file mode 100644 index 8f92a5add7d2..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/src/sapxsum.c +++ /dev/null @@ -1,34 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/sapxsum.h" -#include "stdlib/blas/ext/base/sapxsumkbn.h" -#include - -/** -* Adds a constant to each single-precision floating-point strided array element and computes the sum. -* -* @param N number of indexed elements -* @param alpha constant -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sapxsum( const int64_t N, const float alpha, const float *X, const int64_t stride ) { - return stdlib_strided_sapxsumkbn( N, alpha, X, stride ); -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js index 6b1841d188ca..e934787b6ee6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsum( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js index 6d6e3d7349d3..41408fb8dde6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.ndarray.native.js @@ -144,14 +144,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsum( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js index e69c204bcc8f..9ffab4c34652 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsum( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js index 5776424c10a5..ea4af83e62e1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsum/test/test.sapxsum.native.js @@ -253,14 +253,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsum( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md index 5be0312c484c..1e7df5811f3a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/README.md @@ -20,7 +20,7 @@ limitations under the License. # sapxsumkbn -> Add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. +> Add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.
@@ -36,16 +36,16 @@ limitations under the License. var sapxsumkbn = require( '@stdlib/blas/ext/base/sapxsumkbn' ); ``` -#### sapxsumkbn( N, alpha, x, stride ) +#### sapxsumkbn( N, alpha, x, strideX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var v = sapxsumkbn( 3, 5.0, x, 1 ); +var v = sapxsumkbn( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -54,9 +54,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in the strided array, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in the strided array: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -81,24 +81,24 @@ var v = sapxsumkbn( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### sapxsumkbn.ndarray( N, alpha, x, stride, offset ) +#### sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var v = sapxsumkbn.ndarray( 3, 5.0, x, 1, 0 ); +var v = sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameter supports indexing semantics based on a starting index. For example, to access every other value in the strided array starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -130,11 +130,12 @@ var v = sapxsumkbn.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumkbn = require( '@stdlib/blas/ext/base/sapxsumkbn' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumkbn( x.length, 5.0, x, 1 ); @@ -145,8 +146,125 @@ console.log( v ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sapxsumkbn.h" +``` + +#### stdlib_strided_sapxsumkbn( N, alpha, \*X, strideX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumkbn( 4, 5.0f, x, 1 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_sapxsumkbn( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sapxsumkbn_ndarray( N, alpha, \*X, strideX, offsetX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumkbn_ndarray( 4, 5.0f, x, 1, 0 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_sapxsumkbn_ndarray( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sapxsumkbn.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the sum: + float v = stdlib_strided_sapxsumkbn( N, 5.0f, x, strideX ); + + // Print the result: + printf( "Sum: %f\n", v ); +} +``` + +
+ + + +
+ + +
## References @@ -166,7 +284,7 @@ console.log( v ); ## See Also - [`@stdlib/blas/ext/base/dapxsumkbn`][@stdlib/blas/ext/base/dapxsumkbn]: add a constant to each double-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. -- [`@stdlib/blas/ext/base/gapxsumkbn`][@stdlib/blas/ext/base/gapxsumkbn]: add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. +- [`@stdlib/blas/ext/base/gapxsumkbn`][@stdlib/blas/ext/base/gapxsumkbn]: add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm. - [`@stdlib/blas/ext/base/sapxsum`][@stdlib/blas/ext/base/sapxsum]: add a constant to each single-precision floating-point strided array element and compute the sum. - [`@stdlib/blas/ext/base/ssumkbn`][@stdlib/blas/ext/base/ssumkbn]: calculate the sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js index 436b3c5fd9b3..ddd3b08cadc9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapxsumkbn = require( './../lib/sapxsumkbn.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js index 6533d38d9263..5572e09688fb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapxsumkbn = tryRequire( resolve( __dirname, './../lib/sapxsumkbn.native.js' var opts = { 'skip': ( sapxsumkbn instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js index 2468257ec2fe..6fae6595da0a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapxsumkbn = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js index bcaf22fbf17a..8d984dfd529a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapxsumkbn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sapxsumkbn instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/c/benchmark.length.c index add3ded77115..bcd662e0208d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sapxsumkbn( len, 5.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sapxsumkbn_ndarray( len, 5.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt index c19a98e099c9..ba6f5607cfec 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/repl.txt @@ -1,10 +1,11 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using an improved Kahan–Babuška algorithm. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using an improved Kahan–Babuška + algorithm. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +18,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,7 +38,7 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > {{alias}}( 3, 5.0, x, 2 ) 16.0 @@ -49,13 +50,13 @@ 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using an improved Kahan–Babuška algorithm and - alternative indexing semantics. +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using an improved Kahan–Babuška + algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -64,15 +65,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/types/index.d.ts index ebc74f68a0a1..e2491570a2db 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/docs/types/index.d.ts @@ -23,12 +23,12 @@ */ interface Routine { /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -39,16 +39,16 @@ interface Routine { * var v = sapxsumkbn( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: Float32Array, stride: number ): number; + ( N: number, alpha: number, x: Float32Array, strideX: number ): number; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/c/example.c index 33da918ff6c0..322d0f7eb21f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/c/example.c @@ -17,22 +17,21 @@ */ #include "stdlib/blas/ext/base/sapxsumkbn.h" -#include #include int main( void ) { // Create a strided array: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - const int64_t N = 4; + // Specify the number of indexed elements: + const int N = 8; - // Specify the stride length: - const int64_t stride = 2; + // Specify a stride: + const int strideX = 1; // Compute the sum: - float v = stdlib_strided_sapxsumkbn( N, 5.0f, x, stride ); + float v = stdlib_strided_sapxsumkbn( N, 5.0f, x, strideX ); // Print the result: - printf( "sum: %f\n", v ); + printf( "Sum: %f\n", v ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js index 085e247e5682..2b521fffb590 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumkbn = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumkbn( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include/stdlib/blas/ext/base/sapxsumkbn.h b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include/stdlib/blas/ext/base/sapxsumkbn.h index 963572af5fed..51ce55594ab2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include/stdlib/blas/ext/base/sapxsumkbn.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/include/stdlib/blas/ext/base/sapxsumkbn.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SAPXSUMKBN_H #define STDLIB_BLAS_EXT_BASE_SAPXSUMKBN_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. */ -float stdlib_strided_sapxsumkbn( const int64_t N, const float alpha, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sapxsumkbn)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sapxsumkbn_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/index.js index d4ce0dc844a0..4dab7c8053ff 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. +* Add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm. * * @module @stdlib/blas/ext/base/sapxsumkbn * @@ -29,7 +29,7 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * -* var v = sapxsumkbn( 3, 5.0, x, 1 ); +* var v = sapxsumkbn( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.js index 041e2736cdb9..4efea2a26f1d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var absf = require( '@stdlib/math/base/special/absf' ); // MAIN // @@ -38,10 +38,10 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -52,7 +52,7 @@ var abs = require( '@stdlib/math/base/special/abs' ); * var v = sapxsumkbn( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumkbn( N, alpha, x, stride, offset ) { +function sapxsumkbn( N, alpha, x, strideX, offsetX ) { var sum; var ix; var v; @@ -63,22 +63,22 @@ function sapxsumkbn( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ offset ] ); + ix = offsetX; + if ( strideX === 0 ) { + return float64ToFloat32( N * float64ToFloat32( alpha + x[ ix ] ) ); } - ix = offset; sum = 0.0; c = 0.0; for ( i = 0; i < N; i++ ) { v = float64ToFloat32( alpha + x[ ix ] ); t = float64ToFloat32( sum + v ); - if ( abs( sum ) >= abs( v ) ) { + if ( absf( sum ) >= absf( v ) ) { c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( sum-t ) + v ) ); // eslint-disable-line max-len } else { c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( v-t ) + sum ) ); // eslint-disable-line max-len } sum = t; - ix += stride; + ix += strideX; } return float64ToFloat32( sum + c ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.native.js index 175f0ba07a78..b3020ed9296a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/ndarray.native.js @@ -20,21 +20,19 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './sapxsumkbn.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -45,13 +43,8 @@ var addon = require( './sapxsumkbn.native.js' ); * var v = sapxsumkbn( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumkbn( N, alpha, x, stride, offset ) { - var view; - - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - - return addon( N, alpha, view, stride ); +function sapxsumkbn( N, alpha, x, strideX, offsetX ) { + return addon.ndarray( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.js index 624c9b8f36bf..d05926aa204d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.js @@ -20,14 +20,14 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * ## Method * @@ -38,9 +38,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example @@ -51,39 +51,8 @@ var abs = require( '@stdlib/math/base/special/abs' ); * var v = sapxsumkbn( 3, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumkbn( N, alpha, x, stride ) { - var sum; - var ix; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - c = 0.0; - for ( i = 0; i < N; i++ ) { - v = float64ToFloat32( alpha + x[ ix ] ); - t = float64ToFloat32( sum + v ); - if ( abs( sum ) >= abs( v ) ) { - c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( sum-t ) + v ) ); // eslint-disable-line max-len - } else { - c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( v-t ) + sum ) ); // eslint-disable-line max-len - } - sum = t; - ix += stride; - } - return float64ToFloat32( sum + c ); +function sapxsumkbn( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.native.js index b0308f139594..ea52c7e8fffe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/lib/sapxsumkbn.native.js @@ -26,12 +26,12 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example @@ -42,8 +42,8 @@ var addon = require( './../src/addon.node' ); * var v = sapxsumkbn( 3, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumkbn( N, alpha, x, stride ) { - return addon( N, alpha, x, stride ); +function sapxsumkbn( N, alpha, x, strideX ) { + return addon( N, alpha, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/manifest.json index 95277788d1ec..4bfa5b940f2f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/manifest.json @@ -28,50 +28,56 @@ { "task": "build", "src": [ - "./src/sapxsumkbn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-float", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf", + "@stdlib/napi/create-double" ] }, { "task": "benchmark", "src": [ - "./src/sapxsumkbn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" + ] }, { "task": "examples", "src": [ - "./src/sapxsumkbn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/package.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/package.json index 9aa91dc16e0d..7b1ee6ab0dc6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/sapxsumkbn", "version": "0.0.0", - "description": "Add a constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.", + "description": "Add a scalar constant to each single-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.c index c0d045f60a73..dee8603f7e4e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/addon.c @@ -17,13 +17,14 @@ */ #include "stdlib/blas/ext/base/sapxsumkbn.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_float.h" #include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -36,14 +37,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumkbn)( N, alpha, X, strideX ), v ); + return v; +} - napi_value v; - napi_status status; - status = napi_create_double( env, (double)stdlib_strided_sapxsumkbn( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumkbn_ndarray)( N, alpha, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/main.c new file mode 100644 index 000000000000..880201e0110e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/main.c @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsumkbn.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/absf.h" + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. +* +* ## Method +* +* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). +* +* ## References +* +* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumkbn)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sapxsumkbn_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). +* +* ## References +* +* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumkbn_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + float sum; + float v; + float t; + float c; + + if ( N <= 0 ) { + return 0.0f; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * ( alpha + X[ ix ] ); + } + sum = 0.0f; + c = 0.0f; + for ( i = 0; i < N; i++ ) { + v = alpha + X[ ix ]; + t = sum + v; + if ( stdlib_base_absf( sum ) >= stdlib_base_absf( v ) ) { + c += (sum-t) + v; + } else { + c += (v-t) + sum; + } + sum = t; + ix += strideX; + } + return sum + c; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/sapxsumkbn.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/sapxsumkbn.c deleted file mode 100644 index 6d9f6c196c1c..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/src/sapxsumkbn.c +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/sapxsumkbn.h" -#include -#include - -/** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using an improved Kahan–Babuška algorithm. -* -* ## Method -* -* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). -* -* ## References -* -* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). -* -* @param N number of indexed elements -* @param alpha constant -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sapxsumkbn( const int64_t N, const float alpha, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - float sum; - float v; - float t; - float c; - - if ( N <= 0 ) { - return 0.0f; - } - if ( N == 1 || stride == 0 ) { - return alpha + X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0f; - c = 0.0f; - for ( i = 0; i < N; i++ ) { - v = alpha + X[ ix ]; - t = sum + v; - if ( fabsf( sum ) >= fabsf( v ) ) { - c += (sum-t) + v; - } else { - c += (v-t) + sum; - } - sum = t; - ix += stride; - } - return sum + c; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js index 9168b052806c..87e422f28eff 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js index 845e5a7d30ce..acdfb80dc169 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.ndarray.native.js @@ -144,14 +144,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js index 7f1726ee0230..fa01aaf22f72 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js index 34b37df19ff3..9472347823f0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn/test/test.sapxsumkbn.native.js @@ -253,14 +253,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/README.md index 034dc4343c27..24d1aee9fcf1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/README.md @@ -20,7 +20,7 @@ limitations under the License. # sapxsumkbn2 -> Add a constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. +> Add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
@@ -36,17 +36,16 @@ limitations under the License. var sapxsumkbn2 = require( '@stdlib/blas/ext/base/sapxsumkbn2' ); ``` -#### sapxsumkbn2( N, alpha, x, stride ) +#### sapxsumkbn2( N, alpha, x, strideX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sapxsumkbn2( N, 5.0, x, 1 ); +var v = sapxsumkbn2( x.length, 5.0, x, 1 ); // returns 16.0 ``` @@ -54,9 +53,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -81,25 +80,24 @@ var v = sapxsumkbn2( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### sapxsumkbn2.ndarray( N, alpha, x, stride, offset ) +#### sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sapxsumkbn2.ndarray( N, 5.0, x, 1, 0 ); +var v = sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -131,11 +129,12 @@ var v = sapxsumkbn2.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumkbn2 = require( '@stdlib/blas/ext/base/sapxsumkbn2' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumkbn2( x.length, 5.0, x, 1 ); @@ -146,8 +145,125 @@ console.log( v ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sapxsumkbn2.h" +``` + +#### stdlib_strided_sapxsumkbn2( N, alpha, \*X, strideX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumkbn2( 4, 5.0f, x, 1 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_sapxsumkbn2( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sapxsumkbn2_ndarray( N, alpha, \*X, strideX, offsetX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumkbn2_ndarray( 4, 5.0f, x, 1, 0 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_sapxsumkbn2_ndarray( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sapxsumkbn2.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the sum: + float v = stdlib_strided_sapxsumkbn2( N, 5.0f, x, strideX ); + + // Print the result: + printf( "Sum: %f\n", v ); +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js index 097ef0f89db9..8b0acb7a170e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapxsumkbn2 = require( './../lib/sapxsumkbn2.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js index 981a97127d15..98fff51fa97c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapxsumkbn2 = tryRequire( resolve( __dirname, './../lib/sapxsumkbn2.native.j var opts = { 'skip': ( sapxsumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js index bfc4fadfe3c0..a0cf86d2b25e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapxsumkbn2 = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js index dd827c8d9400..84bba45cef89 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapxsumkbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sapxsumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/c/benchmark.length.c index 0b14204ec658..b338b06878b3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sapxsumkbn2( len, 5.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sapxsumkbn2_ndarray( len, 5.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/repl.txt index 10e574fca3f6..0e9811bd566c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/repl.txt @@ -1,11 +1,11 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using a second-order iterative Kahan–Babuška - algorithm. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using a second-order iterative + Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in the - strided array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -18,13 +18,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -38,7 +38,7 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > {{alias}}( 3, 5.0, x, 2 ) 16.0 @@ -50,13 +50,13 @@ 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using a second-order iterative Kahan–Babuška - algorithm and alternative indexing semantics. +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using a second-order iterative + Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -65,15 +65,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/types/index.d.ts index c4d69b8427d3..3fdb7e66f42a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/docs/types/index.d.ts @@ -23,12 +23,12 @@ */ interface Routine { /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -39,16 +39,16 @@ interface Routine { * var v = sapxsumkbn2( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: Float32Array, stride: number ): number; + ( N: number, alpha: number, x: Float32Array, strideX: number ): number; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/c/example.c index 6ad10b4e1e4d..220e47f462fc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/c/example.c @@ -17,22 +17,21 @@ */ #include "stdlib/blas/ext/base/sapxsumkbn2.h" -#include #include int main( void ) { // Create a strided array: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - const int64_t N = 4; + // Specify the number of indexed elements: + const int N = 8; - // Specify the stride length: - const int64_t stride = 2; + // Specify a stride: + const int strideX = 1; // Compute the sum: - float v = stdlib_strided_sapxsumkbn2( N, 5.0f, x, stride ); + float v = stdlib_strided_sapxsumkbn2( N, 5.0f, x, strideX ); // Print the result: - printf( "sum: %f\n", v ); + printf( "Sum: %f\n", v ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/index.js index 5bc3a172a1d4..f94fe6e7d57c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumkbn2 = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( -100.0, 100.0 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumkbn2( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/include/stdlib/blas/ext/base/sapxsumkbn2.h b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/include/stdlib/blas/ext/base/sapxsumkbn2.h index bd485bb48c34..35a26c85b33a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/include/stdlib/blas/ext/base/sapxsumkbn2.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/include/stdlib/blas/ext/base/sapxsumkbn2.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SAPXSUMKBN2_H #define STDLIB_BLAS_EXT_BASE_SAPXSUMKBN2_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. */ -float stdlib_strided_sapxsumkbn2( const int64_t N, const float alpha, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sapxsumkbn2)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sapxsumkbn2_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/index.js index bdc3abd5ab2b..156372a8b935 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. +* Add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm. * * @module @stdlib/blas/ext/base/sapxsumkbn2 * diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.js index a192f1839905..a34513909179 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.js @@ -27,7 +27,7 @@ var abs = require( '@stdlib/math/base/special/abs' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * ## Method * @@ -38,10 +38,10 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -52,7 +52,7 @@ var abs = require( '@stdlib/math/base/special/abs' ); * var v = sapxsumkbn2( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumkbn2( N, alpha, x, stride, offset ) { +function sapxsumkbn2( N, alpha, x, strideX, offsetX ) { var sum; var ccs; var ix; @@ -66,10 +66,10 @@ function sapxsumkbn2( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ offset ] ); + ix = offsetX; + if ( strideX === 0 ) { + return float64ToFloat32( N * float64ToFloat32( alpha + x[ ix ] ) ); } - ix = offset; sum = 0.0; ccs = 0.0; // second order correction term for lost low order bits cs = 0.0; // first order correction term for lost low order bits @@ -90,7 +90,7 @@ function sapxsumkbn2( N, alpha, x, stride, offset ) { } cs = t; ccs = float64ToFloat32( ccs+cc ); - ix += stride; + ix += strideX; } return float64ToFloat32( sum + float64ToFloat32( cs+ccs ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.native.js index ee442324445a..c70b00819bac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/ndarray.native.js @@ -20,21 +20,19 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './sapxsumkbn2.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -45,11 +43,8 @@ var addon = require( './sapxsumkbn2.native.js' ); * var v = sapxsumkbn2( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumkbn2( N, alpha, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - return addon( N, alpha, view, stride ); +function sapxsumkbn2( N, alpha, x, strideX, offsetX ) { + return addon.ndarray( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.js index d7f78d5f48a6..7f9dc253cdda 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.js @@ -20,14 +20,14 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * ## Method * @@ -38,65 +38,21 @@ var abs = require( '@stdlib/math/base/special/abs' ); * - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsumkbn2( N, 5.0, x, 1 ); +* var v = sapxsumkbn2( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumkbn2( N, alpha, x, stride ) { - var sum; - var ccs; - var ix; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = float64ToFloat32( alpha + x[ ix ] ); - t = float64ToFloat32( sum+v ); - if ( abs( sum ) >= abs( v ) ) { - c = float64ToFloat32( float64ToFloat32( sum-t ) + v ); - } else { - c = float64ToFloat32( float64ToFloat32( v-t ) + sum ); - } - sum = t; - t = float64ToFloat32( cs+c ); - if ( abs( cs ) >= abs( c ) ) { - cc = float64ToFloat32( float64ToFloat32( cs-t ) + c ); - } else { - cc = float64ToFloat32( float64ToFloat32( c-t ) + cs ); - } - cs = t; - ccs = float64ToFloat32( ccs+cc ); - ix += stride; - } - return float64ToFloat32( sum + float64ToFloat32( cs+ccs ) ); +function sapxsumkbn2( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.native.js index 0fa9e8fed298..1ad03bb8f3c2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/lib/sapxsumkbn2.native.js @@ -26,25 +26,24 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsumkbn2( N, 5.0, x, 1 ); +* var v = sapxsumkbn2( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumkbn2( N, alpha, x, stride ) { - return addon( N, alpha, x, stride ); +function sapxsumkbn2( N, alpha, x, strideX ) { + return addon( N, alpha, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/manifest.json index caeb119f92c3..87473f7a3c2d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/manifest.json @@ -33,9 +33,7 @@ "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", @@ -43,7 +41,10 @@ "@stdlib/napi/argv-int64", "@stdlib/napi/argv-float", "@stdlib/napi/argv-strided-float32array", - "@stdlib/napi/create-double" + "@stdlib/napi/create-double", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" ] }, { @@ -54,11 +55,13 @@ "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" + ] }, { "task": "examples", @@ -68,11 +71,13 @@ "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/package.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/package.json index c4a09119a3af..a679afec9eec 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/sapxsumkbn2", "version": "0.0.0", - "description": "Add a constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.", + "description": "Add a scalar constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/addon.c index 68cf8743a93d..464d8106e7f2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/blas/ext/base/sapxsumkbn2.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1) - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sapxsumkbn2( N, alpha, X, stride ), v ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumkbn2)( N, alpha, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumkbn2_ndarray)( N, alpha, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/main.c index c04137e41636..857046f0ad03 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/main.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/src/main.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2020 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -17,11 +17,12 @@ */ #include "stdlib/blas/ext/base/sapxsumkbn2.h" -#include -#include +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/absf.h" /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm. * * ## Method * @@ -31,15 +32,38 @@ * * - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). * -* @param N number of indexed elements -* @param alpha constant -* @param X input array -* @param stride stride length -* @return output value +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @return output value */ -float stdlib_strided_sapxsumkbn2( const int64_t N, const float alpha, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; +float API_SUFFIX(stdlib_strided_sapxsumkbn2)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sapxsumkbn2_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). +* +* ## References +* +* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumkbn2_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; float sum; float ccs; float cs; @@ -51,13 +75,9 @@ float stdlib_strided_sapxsumkbn2( const int64_t N, const float alpha, const floa if ( N <= 0 ) { return 0.0f; } - if ( N == 1 || stride == 0 ) { - return alpha + X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; + ix = offsetX; + if ( strideX == 0 ) { + return N * ( alpha + X[ ix ] ); } sum = 0.0f; ccs = 0.0f; // second order correction term for lost lower order bits @@ -65,21 +85,21 @@ float stdlib_strided_sapxsumkbn2( const int64_t N, const float alpha, const floa for ( i = 0; i < N; i++ ) { v = alpha + X[ ix ]; t = sum + v; - if ( fabsf( sum ) >= fabsf( v ) ) { + if ( stdlib_base_absf( sum ) >= stdlib_base_absf( v ) ) { c = (sum-t) + v; } else { c = (v-t) + sum; } sum = t; t = cs + c; - if ( fabsf( cs ) >= fabsf( c ) ) { + if ( stdlib_base_absf( cs ) >= stdlib_base_absf( c ) ) { cc = (cs-t) + c; } else { cc = (c-t) + cs; } cs = t; ccs += cc; - ix += stride; + ix += strideX; } return sum + cs + ccs; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.js index 5c28a6a0b0fa..aeb728363ca7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn2( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.native.js index 26b0dd373fdc..2dfbf39d71e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.ndarray.native.js @@ -144,14 +144,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn2( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.js index 9005c44a6610..fcfecc1f93e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn2( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.native.js index 1126ca1d397f..0194b4369983 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumkbn2/test/test.sapxsumkbn2.native.js @@ -253,14 +253,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumkbn2( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/README.md index 804f80b75920..0abb5a891097 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/README.md @@ -20,7 +20,7 @@ limitations under the License. # sapxsumors -> Add a constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation. +> Add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation.
@@ -36,9 +36,9 @@ limitations under the License. var sapxsumors = require( '@stdlib/blas/ext/base/sapxsumors' ); ``` -#### sapxsumors( N, alpha, x, stride ) +#### sapxsumors( N, alpha, x, strideX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -52,10 +52,11 @@ var v = sapxsumors( x.length, 5.0, x, 1 ); The function has the following parameters: - **N**: number of indexed elements. +- **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -80,9 +81,9 @@ var v = sapxsumors( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### sapxsumors.ndarray( N, alpha, x, stride, offset ) +#### sapxsumors.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -95,9 +96,9 @@ var v = sapxsumors.ndarray( x.length, 5.0, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -130,12 +131,13 @@ var v = sapxsumors.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var sapxsumors = require( '@stdlib/blas/ext/base/sapxsumors' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumors( x.length, 5.0, x, 1 ); @@ -146,6 +148,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sapxsumors.h" +``` + +#### stdlib_strided_sapxsumors( N, alpha, \*X, strideX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumors( 4, 5.0f, x, 1 ); +// returns 30.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_sapxsumors( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sapxsumors_ndarray( N, alpha, \*X, strideX, offsetX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumors_ndarray( 4, 5.0f, x, 1, 0 ); +// returns 30.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_sapxsumors_ndarray( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sapxsumors.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the sum: + float v = stdlib_strided_sapxsumors( N, 5.0f, x, strideX ); + + // Print the result: + printf( "Sum: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js index e2e536267536..98d520cbdc14 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapxsumors = require( './../lib/sapxsumors.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js index b234d22157b4..b5f2ca916a59 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapxsumors = tryRequire( resolve( __dirname, './../lib/sapxsumors.native.js' var opts = { 'skip': ( sapxsumors instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js index ded8d1ca0f61..650bd0aaf506 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sapxsumors = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js index 6a005e1a62cd..f46632ba9e49 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var sapxsumors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sapxsumors instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/c/benchmark.length.c index b0e31cd80473..4514ab8bdbdf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sapxsumors( len, 5.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sapxsumors_ndarray( len, 5.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/repl.txt index 1936cee0559d..85989a9bdfcf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using ordinary recursive summation. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,29 +37,25 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using ordinary recursive summation and +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using ordinary recursive summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -68,15 +64,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -93,8 +89,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 5.0, x, 2, 1 ) + > {{alias}}.ndarray( 3, 5.0, x, 2, 1 ) 14.0 See Also diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/types/index.d.ts index f321ad409cb5..18860b460cb9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/docs/types/index.d.ts @@ -23,12 +23,12 @@ */ interface Routine { /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -39,16 +39,16 @@ interface Routine { * var v = sapxsumors( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: Float32Array, stride: number ): number; + ( N: number, alpha: number, x: Float32Array, strideX: number ): number; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = sapxsumors.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/c/example.c index 78cc54d0dd41..2723281a207f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/c/example.c @@ -17,22 +17,21 @@ */ #include "stdlib/blas/ext/base/sapxsumors.h" -#include #include int main( void ) { // Create a strided array: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - const int64_t N = 4; + // Specify the number of indexed elements: + const int N = 8; - // Specify the stride length: - const int64_t stride = 2; + // Specify a stride: + const int strideX = 1; // Compute the sum: - float v = stdlib_strided_sapxsumors( N, 5.0f, x, stride ); + float v = stdlib_strided_sapxsumors( N, 5.0f, x, strideX ); // Print the result: - printf( "sum: %f\n", v ); + printf( "Sum: %f\n", v ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/index.js index d79569cc0357..7d89fed3d6b5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumors = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumors( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/include/stdlib/blas/ext/base/sapxsumors.h b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/include/stdlib/blas/ext/base/sapxsumors.h index 6203f1570b44..ed5f9464f17a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/include/stdlib/blas/ext/base/sapxsumors.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/include/stdlib/blas/ext/base/sapxsumors.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SAPXSUMORS_H #define STDLIB_BLAS_EXT_BASE_SAPXSUMORS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. */ -float stdlib_strided_sapxsumors( const int64_t N, const float alpha, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sapxsumors)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sapxsumors_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/index.js index 8337dd181fda..0d73bea58abd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation. +* Add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation. * * @module @stdlib/blas/ext/base/sapxsumors * @@ -34,7 +34,6 @@ * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var sapxsumors = require( '@stdlib/blas/ext/base/sapxsumors' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.js index 0dc1c6dbc875..21ad1f288eea 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.js @@ -26,25 +26,24 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * * var v = sapxsumors( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumors( N, alpha, x, stride, offset ) { +function sapxsumors( N, alpha, x, strideX, offsetX ) { var sum; var ix; var i; @@ -52,14 +51,14 @@ function sapxsumors( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ 0 ] ); + ix = offsetX; + if ( strideX === 0 ) { + return float64ToFloat32( N * float64ToFloat32( alpha + x[ ix ] ) ); } - ix = offset; sum = 0.0; for ( i = 0; i < N; i++ ) { sum = float64ToFloat32( sum + float64ToFloat32( alpha+x[ ix ] ) ); - ix += stride; + ix += strideX; } return sum; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.native.js index 4d73c87d4a67..a91e66406049 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/ndarray.native.js @@ -20,38 +20,31 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './sapxsumors.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sapxsumors( N, 5.0, x, 2, 1 ); +* var v = sapxsumors( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumors( N, alpha, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - return addon( N, alpha, view, stride ); +function sapxsumors( N, alpha, x, strideX, offsetX ) { + return addon.ndarray( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.js index 5fcfa36f4c99..fab6b509a1bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.js @@ -20,18 +20,19 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example @@ -42,28 +43,8 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * var v = sapxsumors( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumors( N, alpha, x, stride ) { - var sum; - var ix; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - for ( i = 0; i < N; i++ ) { - sum = float64ToFloat32( sum + float64ToFloat32( alpha+x[ ix ] ) ); - ix += stride; - } - return sum; +function sapxsumors( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.native.js index 72233f89ce94..bd1e6ea6b7f4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/lib/sapxsumors.native.js @@ -26,12 +26,12 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example @@ -42,8 +42,8 @@ var addon = require( './../src/addon.node' ); * var v = sapxsumors( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumors( N, alpha, x, stride ) { - return addon( N, alpha, x, stride ); +function sapxsumors( N, alpha, x, strideX ) { + return addon( N, alpha, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/manifest.json index 4cbcc4fe6950..b9ce4f08365b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/manifest.json @@ -28,50 +28,53 @@ { "task": "build", "src": [ - "./src/sapxsumors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-float", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/sapxsumors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] }, { "task": "examples", "src": [ - "./src/sapxsumors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/package.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/package.json index baa5f58af75e..8bee47e776c8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/sapxsumors", "version": "0.0.0", - "description": "Add a constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation.", + "description": "Add a scalar constant to each single-precision floating-point strided array element and compute the sum using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/addon.c index c7df8e36096b..ca870573be01 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/addon.c @@ -17,13 +17,14 @@ */ #include "stdlib/blas/ext/base/sapxsumors.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_float.h" #include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -36,14 +37,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_sapxsumors( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumors)( N, alpha, X, strideX ), v ); + return v; +} +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumors_ndarray)( N, alpha, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/main.c new file mode 100644 index 000000000000..b213d45e8ff5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/main.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsumors.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumors)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sapxsumors_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumors_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + float sum; + + if ( N <= 0 ) { + return 0.0f; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * ( alpha + X[ ix ] ); + } + sum = 0.0f; + for ( i = 0; i < N; i++ ) { + sum += alpha + X[ ix ]; + ix += strideX; + } + return sum; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/sapxsumors.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/sapxsumors.c deleted file mode 100644 index f1a8cb27559b..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/src/sapxsumors.c +++ /dev/null @@ -1,53 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/sapxsumors.h" -#include - -/** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using ordinary recursive summation. -* -* @param N number of indexed elements -* @param alpha constant -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sapxsumors( const int64_t N, const float alpha, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - float sum; - - if ( N <= 0 ) { - return 0.0f; - } - if ( N == 1 || stride == 0 ) { - return alpha + X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0f; - for ( i = 0; i < N; i++ ) { - sum += alpha + X[ ix ]; - ix += stride; - } - return sum; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.js index 1c74fa313a42..739cb722f1f9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumors( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.native.js index 0f84db8210cd..3df9cfbc3f74 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.ndarray.native.js @@ -144,14 +144,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumors( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.js index a86cf7172505..1ca0310af316 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.js @@ -135,14 +135,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumors( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.native.js index da0f4b3a91e9..a6d8585410f6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumors/test/test.sapxsumors.native.js @@ -253,14 +253,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumors( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md index b4ec0a254771..d442e0562055 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/README.md @@ -20,7 +20,7 @@ limitations under the License. # sapxsumpw -> Add a constant to each single-precision floating-point strided array element and compute the sum using pairwise summation. +> Add a scalar constant to each single-precision floating-point strided array element and compute the sum using pairwise summation.
@@ -36,27 +36,27 @@ limitations under the License. var sapxsumpw = require( '@stdlib/blas/ext/base/sapxsumpw' ); ``` -#### sapxsumpw( N, alpha, x, stride ) +#### sapxsumpw( N, alpha, x, strideX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sapxsumpw( N, 5.0, x, 1 ); +var v = sapxsumpw( x.length, 5.0, x, 1 ); // returns 16.0 ``` The function has the following parameters: - **N**: number of indexed elements. +- **alpha**: scalar constant. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **stride**: stride length. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -81,25 +81,24 @@ var v = sapxsumpw( 4, 5.0, x1, 2 ); // returns 25.0 ``` -#### sapxsumpw.ndarray( N, alpha, x, stride, offset ) +#### sapxsumpw.ndarray( N, alpha, x, strideX, offsetX ) -Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sapxsumpw.ndarray( N, 5.0, x, 1, 0 ); +var v = sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 ); // returns 16.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to access every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -131,12 +130,12 @@ var v = sapxsumpw.ndarray( 4, 5.0, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumpw = require( '@stdlib/blas/ext/base/sapxsumpw' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumpw( x.length, 5.0, x, 1 ); @@ -147,8 +146,125 @@ console.log( v ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sapxsumpw.h" +``` + +#### stdlib_strided_sapxsumpw( N, alpha, \*X, strideX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumpw( 4, 5.0f, x, 1 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_sapxsumpw( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sapxsumpw_ndarray( N, alpha, \*X, strideX, offsetX ) + +Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + +float v = stdlib_strided_sapxsumpw_ndarray( 4, 5.0f, x, 1, 0 ); +// returns 30.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_sapxsumpw_ndarray( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sapxsumpw.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the sum: + float v = stdlib_strided_sapxsumpw( N, 5.0f, x, strideX ); + + // Print the result: + printf( "Sum: %f\n", v ); +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js index 1e03ab275c86..411cceebc610 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var sapxsumpw = require( './../lib/sapxsumpw.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,10 +45,7 @@ var sapxsumpw = require( './../lib/sapxsumpw.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js index 756d5a078148..520514c97340 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,6 +35,9 @@ var sapxsumpw = tryRequire( resolve( __dirname, './../lib/sapxsumpw.native.js' ) var opts = { 'skip': ( sapxsumpw instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,10 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js index e680e6575f61..5558078e88e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; var sapxsumpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,10 +45,7 @@ var sapxsumpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js index 00d203a97740..f62b256ca9fd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,6 +35,9 @@ var sapxsumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( sapxsumpw instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,10 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/c/benchmark.length.c index d347bace99ea..178f14510774 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sapxsumpw( len, 5.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sapxsumpw_ndarray( len, 5.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt index 469b9b207f4f..fb126ecf3d70 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, alpha, x, stride ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using pairwise summation. +{{alias}}( N, alpha, x, strideX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using pairwise summation. - The `N` and stride parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,13 +17,13 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,27 +37,25 @@ > {{alias}}( x.length, 5.0, x, 1 ) 16.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var stride = 2; - > {{alias}}( 3, 5.0, x, stride ) + > {{alias}}( 3, 5.0, x, 2 ) 16.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > stride = 2; - > {{alias}}( 3, 5.0, x1, stride ) + > {{alias}}( 3, 5.0, x1, 2 ) 14.0 -{{alias}}.ndarray( N, alpha, x, stride, offset ) - Adds a constant to each single-precision floating-point strided array - element and computes the sum using pairwise summation and alternative +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Adds a scalar constant to each single-precision floating-point strided + array element and computes the sum using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -66,15 +64,15 @@ Number of indexed elements. alpha: number - Constant. + Scalar constant. x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/types/index.d.ts index 6d3d5190de71..30a0802846df 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/docs/types/index.d.ts @@ -23,12 +23,12 @@ */ interface Routine { /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -39,16 +39,16 @@ interface Routine { * var v = sapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 */ - ( N: number, alpha: number, x: Float32Array, stride: number ): number; + ( N: number, alpha: number, x: Float32Array, strideX: number ): number; /** - * Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. + * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements - * @param alpha - constant + * @param alpha - scalar constant * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -59,16 +59,16 @@ interface Routine { * var v = sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 ); * // returns 16.0 */ - ndarray( N: number, alpha: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * @param N - number of indexed elements -* @param alpha - constant +* @param alpha - scalar constant * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/c/example.c index ed7c4a77a0e6..a93d075fc6bb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/c/example.c @@ -17,22 +17,21 @@ */ #include "stdlib/blas/ext/base/sapxsumpw.h" -#include #include int main( void ) { // Create a strided array: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - const int64_t N = 4; + // Specify the number of indexed elements: + const int N = 8; - // Specify the stride length: - const int64_t stride = 2; + // Specify a stride: + const int strideX = 1; // Compute the sum: - float v = stdlib_strided_sapxsumpw( N, 5.0f, x, stride ); + float v = stdlib_strided_sapxsumpw( N, 5.0f, x, strideX ); // Print the result: - printf( "sum: %f\n", v ); + printf( "Sum: %f\n", v ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js index ce7accccd889..aa7262357c1b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/examples/index.js @@ -18,14 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sapxsumpw = require( './../lib' ); -var x; - -x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sapxsumpw( x.length, 5.0, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include/stdlib/blas/ext/base/sapxsumpw.h b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include/stdlib/blas/ext/base/sapxsumpw.h index 46125e9980ef..dcb9d1e328e7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include/stdlib/blas/ext/base/sapxsumpw.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/include/stdlib/blas/ext/base/sapxsumpw.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SAPXSUMPW_H #define STDLIB_BLAS_EXT_BASE_SAPXSUMPW_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. */ -float stdlib_strided_sapxsumpw( const int64_t N, const float alpha, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sapxsumpw)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ); + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sapxsumpw_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/index.js index 9c01c7d56d7f..0ef59d61a28f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Add a constant to each single-precision floating-point strided array element and compute the sum using pairwise summation. +* Add a scalar constant to each single-precision floating-point strided array element and compute the sum using pairwise summation. * * @module @stdlib/blas/ext/base/sapxsumpw * @@ -28,9 +28,8 @@ * var sapxsumpw = require( '@stdlib/blas/ext/base/sapxsumpw' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsumpw( N, 5.0, x, 1 ); +* var v = sapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.js index 2a036cc5a1f4..f3f58f5ad6f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.js @@ -35,7 +35,7 @@ var BLOCKSIZE = 128; // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * ## Method * @@ -46,10 +46,10 @@ var BLOCKSIZE = 128; * - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -60,7 +60,7 @@ var BLOCKSIZE = 128; * var v = sapxsumpw( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumpw( N, alpha, x, stride, offset ) { +function sapxsumpw( N, alpha, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -78,42 +78,42 @@ function sapxsumpw( N, alpha, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ offset ] ); + ix = offsetX; + if ( strideX === 0 ) { + return float64ToFloat32( N * float64ToFloat32( alpha + x[ ix ] ) ); } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; for ( i = 0; i < N; i++ ) { s = float64ToFloat32( s + float64ToFloat32( alpha + x[ ix ] ) ); - ix += stride; + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... s0 = float64ToFloat32( alpha + x[ ix ] ); - s1 = float64ToFloat32( alpha + x[ ix+stride ] ); - s2 = float64ToFloat32( alpha + x[ ix+(2*stride) ] ); - s3 = float64ToFloat32( alpha + x[ ix+(3*stride) ] ); - s4 = float64ToFloat32( alpha + x[ ix+(4*stride) ] ); - s5 = float64ToFloat32( alpha + x[ ix+(5*stride) ] ); - s6 = float64ToFloat32( alpha + x[ ix+(6*stride) ] ); - s7 = float64ToFloat32( alpha + x[ ix+(7*stride) ] ); - ix += 8 * stride; + s1 = float64ToFloat32( alpha + x[ ix+strideX ] ); + s2 = float64ToFloat32( alpha + x[ ix+(2*strideX) ] ); + s3 = float64ToFloat32( alpha + x[ ix+(3*strideX) ] ); + s4 = float64ToFloat32( alpha + x[ ix+(4*strideX) ] ); + s5 = float64ToFloat32( alpha + x[ ix+(5*strideX) ] ); + s6 = float64ToFloat32( alpha + x[ ix+(6*strideX) ] ); + s7 = float64ToFloat32( alpha + x[ ix+(7*strideX) ] ); + ix += 8 * strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { s0 = float64ToFloat32( s0 + float64ToFloat32( alpha + x[ ix ] ) ); - s1 = float64ToFloat32( s1 + float64ToFloat32( alpha + x[ ix+stride ] ) ); - s2 = float64ToFloat32( s2 + float64ToFloat32( alpha + x[ ix+(2*stride) ] ) ); - s3 = float64ToFloat32( s3 + float64ToFloat32( alpha + x[ ix+(3*stride) ] ) ); - s4 = float64ToFloat32( s4 + float64ToFloat32( alpha + x[ ix+(4*stride) ] ) ); - s5 = float64ToFloat32( s5 + float64ToFloat32( alpha + x[ ix+(5*stride) ] ) ); - s6 = float64ToFloat32( s6 + float64ToFloat32( alpha + x[ ix+(6*stride) ] ) ); - s7 = float64ToFloat32( s7 + float64ToFloat32( alpha + x[ ix+(7*stride) ] ) ); - ix += 8 * stride; + s1 = float64ToFloat32( s1 + float64ToFloat32( alpha + x[ ix+strideX ] ) ); + s2 = float64ToFloat32( s2 + float64ToFloat32( alpha + x[ ix+(2*strideX) ] ) ); + s3 = float64ToFloat32( s3 + float64ToFloat32( alpha + x[ ix+(3*strideX) ] ) ); + s4 = float64ToFloat32( s4 + float64ToFloat32( alpha + x[ ix+(4*strideX) ] ) ); + s5 = float64ToFloat32( s5 + float64ToFloat32( alpha + x[ ix+(5*strideX) ] ) ); + s6 = float64ToFloat32( s6 + float64ToFloat32( alpha + x[ ix+(6*strideX) ] ) ); + s7 = float64ToFloat32( s7 + float64ToFloat32( alpha + x[ ix+(7*strideX) ] ) ); + ix += 8 * strideX; } // Pairwise sum the accumulators: s = float64ToFloat32( float64ToFloat32( float64ToFloat32(s0+s1) + float64ToFloat32(s2+s3) ) + float64ToFloat32( float64ToFloat32(s4+s5) + float64ToFloat32(s6+s7) ) ); @@ -121,14 +121,14 @@ function sapxsumpw( N, alpha, x, stride, offset ) { // Clean-up loop... for ( i; i < N; i++ ) { s = float64ToFloat32( s + float64ToFloat32( alpha + x[ ix ] ) ); - ix += stride; + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return float64ToFloat32( sapxsumpw( n, alpha, x, stride, ix ) + sapxsumpw( N-n, alpha, x, stride, ix+(n*stride) ) ); + return float64ToFloat32( sapxsumpw( n, alpha, x, strideX, ix ) + sapxsumpw( N-n, alpha, x, strideX, ix+(n*strideX) ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.native.js index a84faa05e0e2..305809947ddd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/ndarray.native.js @@ -20,20 +20,19 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './sapxsumpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -44,13 +43,8 @@ var addon = require( './sapxsumpw.native.js' ); * var v = sapxsumpw( 4, 5.0, x, 2, 1 ); * // returns 25.0 */ -function sapxsumpw( N, alpha, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, alpha, view, stride ); +function sapxsumpw( N, alpha, x, strideX, offsetX ) { + return addon.ndarray( N, alpha, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.js index 02e9d4ccbd5a..62bdd59f3c7a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.js @@ -20,14 +20,14 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * ## Method * @@ -38,46 +38,21 @@ var sum = require( './ndarray.js' ); * - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsumpw( N, 5.0, x, 1 ); +* var v = sapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumpw( N, alpha, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return float64ToFloat32( alpha + x[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - s = float64ToFloat32( s + float64ToFloat32( alpha + x[ ix ] ) ); - ix += stride; - } - return s; - } - return sum( N, alpha, x, stride, ix ); +function sapxsumpw( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.native.js index 939d4c29ccb4..549ff195a4ec 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/lib/sapxsumpw.native.js @@ -26,25 +26,24 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. * * @param {PositiveInteger} N - number of indexed elements -* @param {number} alpha - constant +* @param {number} alpha - scalar constant * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sapxsumpw( N, 5.0, x, 1 ); +* var v = sapxsumpw( x.length, 5.0, x, 1 ); * // returns 16.0 */ -function sapxsumpw( N, alpha, x, stride ) { - return addon( N, alpha, x, stride ); +function sapxsumpw( N, alpha, x, strideX ) { + return addon( N, alpha, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/manifest.json index cdc880d4dbbb..bdecb363835f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/manifest.json @@ -28,50 +28,53 @@ { "task": "build", "src": [ - "./src/sapxsumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/napi/export", + "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-float", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/sapxsumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] }, { "task": "examples", "src": [ - "./src/sapxsumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/package.json b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/package.json index 1144e51039c5..07c8d4cde7f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/sapxsumpw", "version": "0.0.0", - "description": "Add a constant to each single-precision floating-point strided array element and compute the sum using pairwise summation.", + "description": "Add a scalar constant to each single-precision floating-point strided array element and compute the sum using pairwise summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.c index 79f34333bd90..c21adf10d16d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/addon.c @@ -17,11 +17,13 @@ */ #include "stdlib/blas/ext/base/sapxsumpw.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_float.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" #include /** @@ -35,14 +37,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - - napi_value v; - napi_status status = napi_create_double( env, (double)stdlib_strided_sapxsumpw( N, alpha, X, stride ), &v ); - assert( status == napi_ok ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumpw)( N, alpha, X, strideX ), v ); + return v; +} +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sapxsumpw_ndarray)( N, alpha, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/main.c new file mode 100644 index 000000000000..5111888632fb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/main.c @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sapxsumpw.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumpw)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sapxsumpw_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Adds a scalar constant to each single-precision floating-point strided array element and computes the sum using pairwise summation and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sapxsumpw_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT M; + CBLAS_INT n; + CBLAS_INT i; + float sum; + float s0; + float s1; + float s2; + float s3; + float s4; + float s5; + float s6; + float s7; + + if ( N <= 0 ) { + return 0.0f; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * ( alpha + X[ ix ] ); + } + if ( N < 8 ) { + // Use simple summation... + sum = 0.0f; + for ( i = 0; i < N; i++ ) { + sum += alpha + X[ ix ]; + ix += strideX; + } + return sum; + } + // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) + if ( N <= 128 ) { + // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... + s0 = alpha + X[ ix ]; + s1 = alpha + X[ ix+strideX ]; + s2 = alpha + X[ ix+(2*strideX) ]; + s3 = alpha + X[ ix+(3*strideX) ]; + s4 = alpha + X[ ix+(4*strideX) ]; + s5 = alpha + X[ ix+(5*strideX) ]; + s6 = alpha + X[ ix+(6*strideX) ]; + s7 = alpha + X[ ix+(7*strideX) ]; + ix += 8 * strideX; + + M = N % 8; + for ( i = 8; i < N-M; i += 8 ) { + s0 += alpha + X[ ix ]; + s1 += alpha + X[ ix+strideX ]; + s2 += alpha + X[ ix+(2*strideX) ]; + s3 += alpha + X[ ix+(3*strideX) ]; + s4 += alpha + X[ ix+(4*strideX) ]; + s5 += alpha + X[ ix+(5*strideX) ]; + s6 += alpha + X[ ix+(6*strideX) ]; + s7 += alpha + X[ ix+(7*strideX) ]; + ix += 8 * strideX; + } + // Pairwise sum the accumulators: + sum = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); + + // Clean-up loop... + for (; i < N; i++ ) { + sum += alpha + X[ ix ]; + ix += strideX; + } + return sum; + } + // Recurse by dividing by two, but avoiding non-multiples of unroll factor... + n = N / 2; + n -= n % 8; + return API_SUFFIX(stdlib_strided_sapxsumpw_ndarray)( n, alpha, X, strideX, ix ) + API_SUFFIX(stdlib_strided_sapxsumpw_ndarray)( N-n, alpha, X, strideX, ix+(n*strideX) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/sapxsumpw.c b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/sapxsumpw.c deleted file mode 100644 index 8871478a4eb6..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/src/sapxsumpw.c +++ /dev/null @@ -1,122 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/sapxsumpw.h" -#include - -/** -* Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation. -* -* ## Method -* -* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. -* -* ## References -* -* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). -* -* @param N number of indexed elements -* @param alpha constant -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sapxsumpw( const int64_t N, const float alpha, const float *X, const int64_t stride ) { - float *xp1; - float *xp2; - int64_t ix; - int64_t M; - int64_t n; - int64_t i; - float sum; - float s0; - float s1; - float s2; - float s3; - float s4; - float s5; - float s6; - float s7; - - if ( N <= 0 ) { - return 0.0f; - } - if ( N == 1 || stride == 0 ) { - return alpha + X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - sum = 0.0f; - for ( i = 0; i < N; i++ ) { - sum += alpha + X[ ix ]; - ix += stride; - } - return sum; - } - // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) - if ( N <= 128 ) { - // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... - s0 = alpha + X[ ix ]; - s1 = alpha + X[ ix+stride ]; - s2 = alpha + X[ ix+(2*stride) ]; - s3 = alpha + X[ ix+(3*stride) ]; - s4 = alpha + X[ ix+(4*stride) ]; - s5 = alpha + X[ ix+(5*stride) ]; - s6 = alpha + X[ ix+(6*stride) ]; - s7 = alpha + X[ ix+(7*stride) ]; - ix += 8 * stride; - - M = N % 8; - for ( i = 8; i < N-M; i += 8 ) { - s0 += alpha + X[ ix ]; - s1 += alpha + X[ ix+stride ]; - s2 += alpha + X[ ix+(2*stride) ]; - s3 += alpha + X[ ix+(3*stride) ]; - s4 += alpha + X[ ix+(4*stride) ]; - s5 += alpha + X[ ix+(5*stride) ]; - s6 += alpha + X[ ix+(6*stride) ]; - s7 += alpha + X[ ix+(7*stride) ]; - ix += 8 * stride; - } - // Pairwise sum the accumulators: - sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); - - // Clean-up loop... - for (; i < N; i++ ) { - sum += alpha + X[ ix ]; - ix += stride; - } - return sum; - } - // Recurse by dividing by two, but avoiding non-multiples of unroll factor... - n = N / 2; - n -= n % 8; - if ( stride < 0 ) { - xp1 = (float *)X + ( (n-N)*stride ); - xp2 = (float *)X; - } else { - xp1 = (float *)X; - xp2 = (float *)X + ( n*stride ); - } - return stdlib_strided_sapxsumpw( n, alpha, xp1, stride ) + stdlib_strided_sapxsumpw( N-n, alpha, xp2, stride ); -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js index c16278d1610d..305f05c82690 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.js @@ -152,14 +152,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumpw( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js index 22fa27a4bbd8..194ecf674277 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.ndarray.native.js @@ -161,14 +161,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumpw( x.length, 5.0, x, 0, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js index 4b9c1dedbbec..e4aa827c9c1b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.js @@ -152,14 +152,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumpw( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js index ea0af9baf524..3cdbccd275ab 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sapxsumpw/test/test.sapxsumpw.native.js @@ -270,14 +270,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element plus a constant repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sapxsumpw( x.length, 5.0, x, 0 ); - t.strictEqual( v, 6.0, 'returns expected value' ); + t.strictEqual( v, x.length * (x[0]+5.0), 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/README.md index 71d4acba54ec..fee160d72f1e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/README.md @@ -51,7 +51,7 @@ The [_L1_ norm][l1norm] is defined as var sasumpw = require( '@stdlib/blas/ext/base/sasumpw' ); ``` -#### sasumpw( N, x, stride ) +#### sasumpw( N, x, strideX ) Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation. @@ -59,9 +59,8 @@ Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision fl var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sasumpw( N, x, 1 ); +var v = sasumpw( x.length, x, 1 ); // returns 5.0 ``` @@ -69,9 +68,9 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **stride**: stride length. -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of absolute values of every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -96,7 +95,7 @@ var v = sasumpw( 4, x1, 2 ); // returns 9.0 ``` -#### sasumpw.ndarray( N, x, stride, offset ) +#### sasumpw.ndarray( N, x, strideX, offsetX ) Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. @@ -104,17 +103,16 @@ Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision fl var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sasumpw.ndarray( N, x, 1, 0 ); +var v = sasumpw.ndarray( x.length, x, 1, 0 ); // returns 5.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values of every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the sum of absolute values of every other element starting from the second element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -147,11 +145,12 @@ var v = sasumpw.ndarray( 4, x, 2, 1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sasumpw = require( '@stdlib/blas/ext/base/sasumpw' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sasumpw( x.length, x, 1 ); @@ -162,8 +161,123 @@ console.log( v ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sasumpw.h" +``` + +#### stdlib_strided_sasumpw( N, \*X, strideX ) + +Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } + +float v = stdlib_strided_sasumpw( 4, x, 1 ); +// returns 10.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_sasumpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sasumpw_ndarray( N, \*X, strideX, offsetX ) + +Computes the sum of absolute values ([_L1_ norm][l1norm]) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } + +float v = stdlib_strided_sasumpw_ndarray( 4, x, 1, 0 ); +// returns 10.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_sasumpw_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sasumpw.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the sum: + float v = stdlib_strided_sasumpw( N, x, strideX ); + + // Print the result: + printf( "sumabs: %f\n", v ); +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js index 6a6fd9c6a57c..663a70aa54fd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sasumpw = require( './../lib/sasumpw.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js index 3c378c2ac2f5..42361ad19d62 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); - var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,7 +35,9 @@ var sasumpw = tryRequire( resolve( __dirname, './../lib/sasumpw.native.js' ) ); var opts = { 'skip': ( sasumpw instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -50,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js index a8a5f2a62579..2629611a6740 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var sasumpw = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,7 +45,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js index 37276b0febad..b24835f9fae1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,8 +35,9 @@ var sasumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sasumpw instanceof Error ) }; - -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -50,7 +50,7 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/c/benchmark.length.c index 91039fef9d09..cbda2fdbb842 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sasumpw( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sasumpw_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/repl.txt index 1774f5a709d6..6d862901ce62 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the sum of absolute values (L1 norm) of single-precision floating- point strided array elements using pairwise summation. - The `N` and `stride` parameters determine which elements in the strided - array are accessed at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,7 +34,7 @@ > {{alias}}( x.length, x, 1 ) 5.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > {{alias}}( 3, x, 2 ) 5.0 @@ -46,13 +46,13 @@ 5.0 -{{alias}}.ndarray( N, x, stride, offset ) +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the sum of absolute values (L1 norm) of single-precision floating- point strided array elements using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -63,10 +63,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/types/index.d.ts index 3c08de014e05..2455965d0a3c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns sum * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = sasumpw( x.length, x, 1 ); * // returns 5.0 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the sum of absolute values (L1 norm) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns sum * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = sasumpw.ndarray( x.length, x, 1, 0 ); * // returns 5.0 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns sum * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/c/example.c index f9aeaa51ea83..0bccb6b926cc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/blas/ext/base/sasumpw.h" -#include #include int main( void ) { // Create a strided array: - const float x[] = { -1.0, 2.0, -3.0, 4.0, -5.0, 6.0, -7.0, 8.0 }; + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; - // Specify the number of elements: - const int64_t N = 4; + // Specify the number of indexed elements: + const int N = 8; - // Specify the stride length: - const int64_t stride = 2; + // Specify a stride: + const int strideX = 1; // Compute the sum: - float v = stdlib_strided_sasumpw( N, x, stride ); + float v = stdlib_strided_sasumpw( N, x, strideX ); // Print the result: printf( "sumabs: %f\n", v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/index.js index 776816d6ddd0..d8b4219a2cb9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/examples/index.js @@ -18,11 +18,12 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sasumpw = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( -100.0, 100.0 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); var v = sasumpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/include/stdlib/blas/ext/base/sasumpw.h b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/include/stdlib/blas/ext/base/sasumpw.h index 3d424d0af630..dd2ff694bf08 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/include/stdlib/blas/ext/base/sasumpw.h +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/include/stdlib/blas/ext/base/sasumpw.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SASUMPW_H #define STDLIB_BLAS_EXT_BASE_SASUMPW_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the sum of absolute values (L1 norm) of single-precision floating-point strided array elements using pairwise summation. */ -float stdlib_strided_sasumpw( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sasumpw)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the sum of absolute values (L1 norm) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semnatics. +*/ +float API_SUFFIX(stdlib_strided_sasumpw_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/index.js index dacab0823113..b95bed4fcba7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/index.js @@ -28,9 +28,8 @@ * var sasumpw = require( '@stdlib/blas/ext/base/sasumpw' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sasumpw( N, x, 1 ); +* var v = sasumpw( x.length, x, 1 ); * // returns 5.0 * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.js index 5242573edb4f..664462ceca0a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.js @@ -22,7 +22,7 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var floor = require( '@stdlib/math/base/special/floor' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var absf = require( '@stdlib/math/base/special/absf' ); // VARIABLES // @@ -46,8 +46,8 @@ var BLOCKSIZE = 128; * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -58,7 +58,7 @@ var BLOCKSIZE = 128; * var v = sasumpw( 4, x, 2, 1 ); * // returns 9.0 */ -function sasumpw( N, x, stride, offset ) { +function sasumpw( N, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -76,57 +76,57 @@ function sasumpw( N, x, stride, offset ) { if ( N <= 0 ) { return 0.0; } - if ( N === 1 || stride === 0 ) { - return abs( x[ offset ] ); + ix = offsetX; + if ( strideX === 0 ) { + return float64ToFloat32( N * absf( x[ ix ] ) ); } - ix = offset; if ( N < 8 ) { // Use simple summation... s = 0.0; for ( i = 0; i < N; i++ ) { - s = float64ToFloat32( s + abs( x[ ix ] ) ); - ix += stride; + s = float64ToFloat32( s + absf( x[ ix ] ) ); + ix += strideX; } return s; } if ( N <= BLOCKSIZE ) { // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... - s0 = abs( x[ ix ] ); - s1 = abs( x[ ix+stride ] ); - s2 = abs( x[ ix+(2*stride) ] ); - s3 = abs( x[ ix+(3*stride) ] ); - s4 = abs( x[ ix+(4*stride) ] ); - s5 = abs( x[ ix+(5*stride) ] ); - s6 = abs( x[ ix+(6*stride) ] ); - s7 = abs( x[ ix+(7*stride) ] ); - ix += 8 * stride; + s0 = absf( x[ ix ] ); + s1 = absf( x[ ix+strideX ] ); + s2 = absf( x[ ix+(2*strideX) ] ); + s3 = absf( x[ ix+(3*strideX) ] ); + s4 = absf( x[ ix+(4*strideX) ] ); + s5 = absf( x[ ix+(5*strideX) ] ); + s6 = absf( x[ ix+(6*strideX) ] ); + s7 = absf( x[ ix+(7*strideX) ] ); + ix += 8 * strideX; M = N % 8; for ( i = 8; i < N-M; i += 8 ) { - s0 = float64ToFloat32( s0 + abs( x[ ix ] ) ); - s1 = float64ToFloat32( s1 + abs( x[ ix+stride ] ) ); - s2 = float64ToFloat32( s2 + abs( x[ ix+(2*stride) ] ) ); - s3 = float64ToFloat32( s3 + abs( x[ ix+(3*stride) ] ) ); - s4 = float64ToFloat32( s4 + abs( x[ ix+(4*stride) ] ) ); - s5 = float64ToFloat32( s5 + abs( x[ ix+(5*stride) ] ) ); - s6 = float64ToFloat32( s6 + abs( x[ ix+(6*stride) ] ) ); - s7 = float64ToFloat32( s7 + abs( x[ ix+(7*stride) ] ) ); - ix += 8 * stride; + s0 = float64ToFloat32( s0 + absf( x[ ix ] ) ); + s1 = float64ToFloat32( s1 + absf( x[ ix+strideX ] ) ); + s2 = float64ToFloat32( s2 + absf( x[ ix+(2*strideX) ] ) ); + s3 = float64ToFloat32( s3 + absf( x[ ix+(3*strideX) ] ) ); + s4 = float64ToFloat32( s4 + absf( x[ ix+(4*strideX) ] ) ); + s5 = float64ToFloat32( s5 + absf( x[ ix+(5*strideX) ] ) ); + s6 = float64ToFloat32( s6 + absf( x[ ix+(6*strideX) ] ) ); + s7 = float64ToFloat32( s7 + absf( x[ ix+(7*strideX) ] ) ); + ix += 8 * strideX; } // Pairwise sum the accumulators: s = float64ToFloat32( float64ToFloat32( float64ToFloat32(s0+s1) + float64ToFloat32(s2+s3) ) + float64ToFloat32( float64ToFloat32(s4+s5) + float64ToFloat32(s6+s7) ) ); // eslint-disable-line max-len // Clean-up loop... for ( i; i < N; i++ ) { - s = float64ToFloat32( s + abs( x[ ix ] ) ); - ix += stride; + s = float64ToFloat32( s + absf( x[ ix ] ) ); + ix += strideX; } return s; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return float64ToFloat32( sasumpw( n, x, stride, ix ) + sasumpw( N-n, x, stride, ix+(n*stride) ) ); // eslint-disable-line max-len + return float64ToFloat32( sasumpw( n, x, strideX, ix ) + sasumpw( N-n, x, strideX, ix+(n*strideX) ) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.native.js index 5cbf52454d03..f8ebb0c0eb79 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './sasumpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,8 +30,8 @@ var addon = require( './sasumpw.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} sum * * @example @@ -44,11 +42,8 @@ var addon = require( './sasumpw.native.js' ); * var v = sasumpw( 4, x, 2, 1 ); * // returns 9.0 */ -function sasumpw( N, x, stride, offset ) { - var view; - offset = minViewBufferIndex( N, stride, offset ); - view = offsetView( x, offset ); - return addon( N, view, stride ); +function sasumpw( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.js index ee1afc1ac462..9df52825fc94 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.js @@ -20,9 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var sum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -40,44 +39,19 @@ var sum = require( './ndarray.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sasumpw( N, x, 1 ); +* var v = sasumpw( x.length, x, 1 ); * // returns 5.0 */ -function sasumpw( N, x, stride ) { - var ix; - var s; - var i; - - if ( N <= 0 ) { - return 0.0; - } - if ( N === 1 || stride === 0 ) { - return abs( x[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - for ( i = 0; i < N; i++ ) { - s = float64ToFloat32( s + abs( x[ ix ] ) ); - ix += stride; - } - return s; - } - return sum( N, x, stride, ix ); +function sasumpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.native.js index 202356129f4e..ae857b1789a9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/lib/sasumpw.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} sum * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sasumpw( N, x, 1 ); +* var v = sasumpw( x.length, x, 1 ); * // returns 5.0 */ -function sasumpw( N, x, stride ) { - return addon( N, x, stride ); +function sasumpw( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/manifest.json index 9414cf70c710..9644a24c3e15 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/manifest.json @@ -28,49 +28,55 @@ { "task": "build", "src": [ - "./src/sasumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" ] }, { "task": "benchmark", "src": [ - "./src/sasumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" + ] }, { "task": "examples", "src": [ - "./src/sasumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/addon.c index d3519c2874db..a229f4715f37 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/addon.c @@ -1,4 +1,3 @@ - /** * @license Apache-2.0 * @@ -18,12 +17,13 @@ */ #include "stdlib/blas/ext/base/sasumpw.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -35,14 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); - - napi_value v; - napi_status status = napi_create_double( env, stdlib_strided_sasumpw( N, X, stride ), &v ); - assert( status == napi_ok ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sasumpw)( N, X, strideX ), v ); + return v; +} +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sasumpw_ndarray)( N, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/main.c new file mode 100644 index 000000000000..622997c2e656 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/main.c @@ -0,0 +1,132 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sasumpw.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/absf.h" + +/** +* Computes the sum of absolute values (L1 norm) of single-precision floating-point strided array elements using pairwise summation. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sasumpw)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sasumpw_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the sum of absolute values (L1 norm) of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sasumpw_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT M; + CBLAS_INT n; + CBLAS_INT i; + float sum; + float s0; + float s1; + float s2; + float s3; + float s4; + float s5; + float s6; + float s7; + + if ( N <= 0 ) { + return 0.0f; + } + ix = offsetX; + if ( strideX == 0 ) { + return N * stdlib_base_absf( X[ ix ] ); + } + if ( N < 8 ) { + // Use simple summation... + sum = 0.0f; + for ( i = 0; i < N; i++ ) { + sum += stdlib_base_absf( X[ ix ] ); + ix += strideX; + } + return sum; + } + // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) + if ( N <= 128 ) { + // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... + s0 = stdlib_base_absf( X[ ix ] ); + s1 = stdlib_base_absf( X[ ix+strideX ] ); + s2 = stdlib_base_absf( X[ ix+(2*strideX) ] ); + s3 = stdlib_base_absf( X[ ix+(3*strideX) ] ); + s4 = stdlib_base_absf( X[ ix+(4*strideX) ] ); + s5 = stdlib_base_absf( X[ ix+(5*strideX) ] ); + s6 = stdlib_base_absf( X[ ix+(6*strideX) ] ); + s7 = stdlib_base_absf( X[ ix+(7*strideX) ] ); + ix += 8 * strideX; + + M = N % 8; + for ( i = 8; i < N-M; i += 8 ) { + s0 += stdlib_base_absf( X[ ix ] ); + s1 += stdlib_base_absf( X[ ix+strideX ] ); + s2 += stdlib_base_absf( X[ ix+(2*strideX) ] ); + s3 += stdlib_base_absf( X[ ix+(3*strideX) ] ); + s4 += stdlib_base_absf( X[ ix+(4*strideX) ] ); + s5 += stdlib_base_absf( X[ ix+(5*strideX) ] ); + s6 += stdlib_base_absf( X[ ix+(6*strideX) ] ); + s7 += stdlib_base_absf( X[ ix+(7*strideX) ] ); + ix += 8 * strideX; + } + // Pairwise sum the accumulators: + sum = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); + + // Clean-up loop... + for (; i < N; i++ ) { + sum += stdlib_base_absf( X[ ix ] ); + ix += strideX; + } + return sum; + } + // Recurse by dividing by two, but avoiding non-multiples of unroll factor... + n = N / 2; + n -= n % 8; + return API_SUFFIX(stdlib_strided_sasumpw_ndarray)( n, X, strideX, ix ) + API_SUFFIX(stdlib_strided_sasumpw_ndarray)( N-n, X, strideX, ix+(n*strideX) ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/sasumpw.c b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/sasumpw.c deleted file mode 100644 index a40c77ec7513..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/src/sasumpw.c +++ /dev/null @@ -1,122 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/sasumpw.h" -#include -#include - -/** -* Computes the sum of absolute values (L1 norm) of single-precision floating-point strided array elements using pairwise summation. -* -* ## Method -* -* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. -* -* ## References -* -* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sasumpw( const int64_t N, const float *X, const int64_t stride ) { - float *xp1; - float *xp2; - int64_t ix; - int64_t M; - int64_t n; - int64_t i; - float sum; - float s0; - float s1; - float s2; - float s3; - float s4; - float s5; - float s6; - float s7; - - if ( N <= 0 ) { - return 0.0f; - } - if ( N == 1 || stride == 0 ) { - return fabsf( X[ 0 ] ); - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - sum = 0.0f; - for ( i = 0; i < N; i++ ) { - sum += fabsf( X[ ix ] ); - ix += stride; - } - return sum; - } - // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) - if ( N <= 128 ) { - // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... - s0 = fabsf( X[ ix ] ); - s1 = fabsf( X[ ix+stride ] ); - s2 = fabsf( X[ ix+(2*stride) ] ); - s3 = fabsf( X[ ix+(3*stride) ] ); - s4 = fabsf( X[ ix+(4*stride) ] ); - s5 = fabsf( X[ ix+(5*stride) ] ); - s6 = fabsf( X[ ix+(6*stride) ] ); - s7 = fabsf( X[ ix+(7*stride) ] ); - ix += 8 * stride; - - M = N % 8; - for ( i = 8; i < N-M; i += 8 ) { - s0 += fabsf( X[ ix ] ); - s1 += fabsf( X[ ix+stride ] ); - s2 += fabsf( X[ ix+(2*stride) ] ); - s3 += fabsf( X[ ix+(3*stride) ] ); - s4 += fabsf( X[ ix+(4*stride) ] ); - s5 += fabsf( X[ ix+(5*stride) ] ); - s6 += fabsf( X[ ix+(6*stride) ] ); - s7 += fabsf( X[ ix+(7*stride) ] ); - ix += 8 * stride; - } - // Pairwise sum the accumulators: - sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); - - // Clean-up loop... - for (; i < N; i++ ) { - sum += fabsf( X[ ix ] ); - ix += stride; - } - return sum; - } - // Recurse by dividing by two, but avoiding non-multiples of unroll factor... - n = N / 2; - n -= n % 8; - if ( stride < 0 ) { - xp1 = (float *)X + ( (n-N)*stride ); - xp2 = (float *)X; - } else { - xp1 = (float *)X; - xp2 = (float *)X + ( n*stride ); - } - return stdlib_strided_sasumpw( n, xp1, stride ) + stdlib_strided_sasumpw( N-n, xp2, stride ); -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.js index 4ba34cb8d024..f85303fab5f1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.js @@ -153,14 +153,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sasumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.native.js index 4b7824262ed8..cd5885550431 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.ndarray.native.js @@ -162,14 +162,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first indexed element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sasumpw( x.length, x, 0, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.js index b4edbf624a86..96a4e839df0c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.js @@ -153,14 +153,14 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sasumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.native.js index 241143d176ce..a653885b8c27 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sasumpw/test/test.sasumpw.native.js @@ -244,14 +244,14 @@ tape( 'the function supports a negative `stride` parameter', opts, function test t.end(); }); -tape( 'if provided a `stride` parameter equal to `0`, the function returns the first element', opts, function test( t ) { +tape( 'if provided a `stride` parameter equal to `0`, the function returns the sum of the first element repeated N times', opts, function test( t ) { var x; var v; x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); v = sasumpw( x.length, x, 0 ); - t.strictEqual( v, 1.0, 'returns expected value' ); + t.strictEqual( v, 5.0, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md index fc090f8e6bf8..deda4f366042 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/README.md @@ -61,11 +61,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in the strided input array, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -115,7 +115,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offsetX and offsetY parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in the strided input array starting from the second value and to store in the last `N` elements of the strided output array starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element in the strided input array starting from the second element and to store in the last `N` elements of the strided output array starting from the last element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -148,14 +148,17 @@ scusum.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusum = require( '@stdlib/blas/ext/base/scusum' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusum( x.length, 0.0, x, 1, y, -1 ); @@ -166,6 +169,138 @@ console.log( y ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/scusum.h" +``` + +#### stdlib_strided_scusum( N, sum, \*X, strideX, \*Y, strideY ) + +Computes the cumulative sum of single-precision floating-point strided array elements. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scusum( 4, 0.0f, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scusum( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_scusum_ndarray( N, sum, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Computes the cumulative sum of single-precision floating-point strided array elements using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scusum_ndarray( 4, 0.0f, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scusum_ndarray( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/scusum.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative sum: + stdlib_strided_scusum( N, 0.0f, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js index 69c251af827c..01e5462f87e4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.js @@ -21,9 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -32,7 +30,9 @@ var scusum = require( './../lib/scusum.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -45,8 +45,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js index 942a4ddda88a..94876e968929 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,7 +35,9 @@ var scusum = tryRequire( resolve( __dirname, './../lib/scusum.native.js' ) ); var opts = { 'skip': ( scusum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -50,8 +50,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js index 00e014a1fe5e..7887fb8bf9f6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.js @@ -21,18 +21,18 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusum = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -45,8 +45,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js index 0a920dce4110..98438aa8b2bf 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,7 +35,9 @@ var scusum = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( scusum instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -50,8 +50,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/c/benchmark.length.c index daae2fff79be..62ffb33c4416 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scusum_ndarray( len, 0.0f, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt index d6e5e3124514..d30a2e0acfc2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative sum of single-precision floating-point strided array elements. - The `N` and `stride` parameters determine which elements in the strided - arrays are accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -44,7 +44,7 @@ > {{alias}}( x.length, 0.0, x, 1, y, 1 ) [ 1.0, -1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); > {{alias}}( 3, 0.0, x, 2, y, 2 ) @@ -66,8 +66,8 @@ elements using alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameter supports indexing semantics based on starting + indices. Parameters ---------- @@ -81,7 +81,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -90,7 +90,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/types/index.d.ts index 22a74c53c2a8..72ac43f45abb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/docs/types/index.d.ts @@ -28,9 +28,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -50,10 +50,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/c/example.c index 58a1d9c51297..f86a82bac261 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/blas/ext/base/scusum.h" -#include #include -#include int main( void ) { // Create strided arrays: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify stride lengths: - const int64_t strideX = 2; - const int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative sum: stdlib_strided_scusum( N, 0.0f, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js index 6a92d6ab1267..be336f4c7b9a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/examples/index.js @@ -18,15 +18,17 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusum = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusum( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/include/stdlib/blas/ext/base/scusum.h b/lib/node_modules/@stdlib/blas/ext/base/scusum/include/stdlib/blas/ext/base/scusum.h index d2ef9741f552..84b670480a7f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/include/stdlib/blas/ext/base/scusum.h +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/include/stdlib/blas/ext/base/scusum.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SCUSUM_H #define STDLIB_BLAS_EXT_BASE_SCUSUM_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative sum of single-precision floating-point strided array elements. */ -void stdlib_strided_scusum( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scusum)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scusum_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js index fc8c631d22b0..40ae6ac83462 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.js @@ -31,10 +31,10 @@ var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ).ndarray; * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js index 3f05e52ab35a..a24b7c6e0d2a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './scusum.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -33,10 +31,10 @@ var addon = require( './scusum.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * @@ -50,14 +48,7 @@ var addon = require( './scusum.native.js' ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusum( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - - offsetX = minViewBufferIndex( N, strideX, offsetX ); - viewX = offsetView( x, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - viewY = offsetView( y, offsetY ); - addon( N, sum, viewX, strideX, viewY, strideY ); + addon.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js index 6c0613927f8e..cf08e66e4147 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.js @@ -31,9 +31,9 @@ var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js index 96b9f767476f..70004245bd99 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/lib/scusum.native.js @@ -31,9 +31,9 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json index 972622c09784..18744d15a7ad 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/manifest.json @@ -28,14 +28,12 @@ { "task": "build", "src": [ - "./src/scusum.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/blas/ext/base/scusumkbn", @@ -43,39 +41,41 @@ "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-float", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/scusum.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/scusumkbn" + "@stdlib/blas/ext/base/scusumkbn", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "examples", "src": [ - "./src/scusum.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/scusumkbn" + "@stdlib/blas/ext/base/scusumkbn", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] } ] diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c index aa739dabff08..8eb8818a8325 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/addon.c @@ -17,13 +17,13 @@ */ #include "stdlib/blas/ext/base/scusum.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_float.h" #include "stdlib/napi/argv_strided_float32array.h" #include -#include /** * Receives JavaScript callback invocation data. @@ -40,8 +40,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_scusum( N, sum, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_scusum)( N, sum, X, strideX, Y, strideY ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 5 ); + API_SUFFIX(stdlib_strided_scusum_ndarray)( N, sum, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/main.c new file mode 100644 index 000000000000..7c3a208ebdc7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/main.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusum.h" +#include "stdlib/blas/ext/base/scusumkbn.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void API_SUFFIX(stdlib_strided_scusum)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scusum_ndarray)( N, sum, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y output array +* @param strideY stride length for Y +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scusum_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + API_SUFFIX(stdlib_strided_scusumkbn_ndarray)( N, sum, X, strideX, offsetX, Y, strideY, offsetY ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/scusum.c b/lib/node_modules/@stdlib/blas/ext/base/scusum/src/scusum.c deleted file mode 100644 index f4822613f1ad..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusum/src/scusum.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusum.h" -#include "stdlib/blas/ext/base/scusumkbn.h" -#include - -/** -* Computes the cumulative sum of single-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param sum initial sum -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scusum( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - stdlib_strided_scusumkbn( N, sum, X, strideX, Y, strideY ); -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md index 9959aa54cf6a..a886b5b06ff3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/README.md @@ -61,11 +61,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -114,7 +114,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element starting from the second element and to store in the last `N` elements of `y` starting from the last element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -147,14 +147,17 @@ scusumkbn.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumkbn( x.length, 0.0, x, 1, y, -1 ); @@ -165,8 +168,138 @@ console.log( y ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/scusumkbn.h" +``` + +#### stdlib_strided_scusumkbn( N, sum, \*X, strideX, \*Y, strideY ) + +Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scusumkbn( 4, 0.0f, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scusumkbn( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_scusumkbn_ndarray( N, sum, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scusumkbn_ndarray( 4, 0.0f, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scusumkbn_ndarray( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/scusumkbn.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative sum: + stdlib_strided_scusumkbn( N, 0.0f, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js index d3306232854f..c6bc32f4b5be 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var scusumkbn = require( './../lib/scusumkbn.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,8 +45,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js index 5ec896713745..0e7b58b7ca4c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var scusumkbn = tryRequire( resolve( __dirname, './../lib/scusumkbn.native.js' ) var opts = { 'skip': ( scusumkbn instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,8 +50,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js index b515bb63eec5..04ee413248f4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var scusumkbn = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,8 +45,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js index a9ac4955e25a..2ac5c4647a5d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var scusumkbn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( scusumkbn instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,8 +50,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/c/benchmark.length.c index db6994749941..7a00351ca445 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scusumkbn_ndarray( len, 0.0f, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt index a64a884cd6b1..ac7d807b96cb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/repl.txt @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -55,8 +55,7 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] @@ -68,8 +67,8 @@ semantics. While typed array views mandate a view offset based on the underlying - buffer, the offset parameters support indexing semantics based on - starting indices. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -83,7 +82,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -92,7 +91,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/types/index.d.ts index eba0f2fcf550..9124a74cf282 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/docs/types/index.d.ts @@ -28,9 +28,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -50,10 +50,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/c/example.c index f57296b2794f..b05a93fa29a7 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/blas/ext/base/scusumkbn.h" -#include #include -#include int main( void ) { // Create strided arrays: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify stride lengths: - const int64_t strideX = 2; - const int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative sum: stdlib_strided_scusumkbn( N, 0.0f, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js index c3c81e53b3b9..87a31dfa72d2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/examples/index.js @@ -18,14 +18,17 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumkbn = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumkbn( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include/stdlib/blas/ext/base/scusumkbn.h b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include/stdlib/blas/ext/base/scusumkbn.h index efd09cd3770f..8d285545d4aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include/stdlib/blas/ext/base/scusumkbn.h +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/include/stdlib/blas/ext/base/scusumkbn.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SCUSUMKBN_H #define STDLIB_BLAS_EXT_BASE_SCUSUMKBN_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. */ -void stdlib_strided_scusumkbn( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scusumkbn)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scusumkbn_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/index.js index 77e8a723b0c8..c162885e8cb5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scusumkbn( N, 0.0, x, 1, y, 1 ); +* scusumkbn( x.length, 0.0, x, 1, y, 1 ); * // y => [ 1.0, -1.0, 1.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var scusumkbn = require( '@stdlib/blas/ext/base/scusumkbn' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* scusumkbn.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* scusumkbn.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.js index 128fe7c6f470..ff59c13b518c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.js @@ -40,22 +40,20 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scusumkbn( N, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumkbn( 4, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumkbn( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { @@ -78,9 +76,9 @@ function scusumkbn( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { v = x[ ix ]; t = float64ToFloat32( s + v ); if ( abs( s ) >= abs( v ) ) { - c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( s-t ) + v ) ); // eslint-disable-line max-len + c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( s - t ) + v ) ); // eslint-disable-line max-len } else { - c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( v-t ) + s ) ); // eslint-disable-line max-len + c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( v - t ) + s ) ); // eslint-disable-line max-len } s = t; y[ iy ] = float64ToFloat32( s + c ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.native.js index a90fbd186970..f8d25cf3ba79 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './scusumkbn.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -33,33 +31,24 @@ var addon = require( './scusumkbn.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scusumkbn( N, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumkbn( 4, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumkbn( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - offsetX = minViewBufferIndex( N, strideX, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - - viewX = offsetView( x, offsetX ); - viewY = offsetView( y, offsetY ); - addon( N, sum, viewX, strideX, viewY, strideY ); + addon.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.js index ebddb73d9957..3bfaad0300ae 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.js @@ -20,8 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -40,9 +40,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -50,48 +50,12 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumkbn( N, 0.0, x, 1, y, 1 ); +* var v = scusumkbn( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumkbn( N, sum, x, strideX, y, strideY ) { - var ix; - var iy; - var s; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - s = sum; - c = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = float64ToFloat32( s + v ); - if ( abs( s ) >= abs( v ) ) { - c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( s-t ) + v ) ); // eslint-disable-line max-len - } else { - c = float64ToFloat32( c + float64ToFloat32( float64ToFloat32( v-t ) + s ) ); // eslint-disable-line max-len - } - s = t; - y[ iy ] = float64ToFloat32( s + c ); - ix += strideX; - iy += strideY; - } + ndarray( N, sum, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.native.js index 9743aa6b2401..8b578e9ac7b2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/lib/scusumkbn.native.js @@ -31,9 +31,9 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -41,9 +41,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumkbn( N, 0.0, x, 1, y, 1 ); +* var v = scusumkbn( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumkbn( N, sum, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/manifest.json index a25295fc9fe6..af6a8bb276be 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/manifest.json @@ -28,7 +28,7 @@ { "task": "build", "src": [ - "./src/scusumkbn.c" + "./src/main.c" ], "include": [ "./include" @@ -41,13 +41,15 @@ "@stdlib/napi/argv-float", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-strided-float32array", - "@stdlib/math/base/special/absf" + "@stdlib/math/base/special/absf", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/scusumkbn.c" + "./src/main.c" ], "include": [ "./include" @@ -55,13 +57,15 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/special/absf" + "@stdlib/math/base/special/absf", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "examples", "src": [ - "./src/scusumkbn.c" + "./src/main.c" ], "include": [ "./include" @@ -69,7 +73,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/special/absf" + "@stdlib/math/base/special/absf", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] } ] diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.c index 6e9988f0c84e..2da790c46ed8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/blas/ext/base/scusumkbn.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_float.h" @@ -39,8 +40,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_scusumkbn( N, sum, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_scusumkbn)( N, sum, X, strideX, Y, strideY ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 5 ); + API_SUFFIX(stdlib_strided_scusumkbn_ndarray)( N, sum, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/main.c new file mode 100644 index 000000000000..36708668335f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/main.c @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumkbn.h" +#include "stdlib/math/base/special/absf.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. +* +* ## Method +* +* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). +* +* ## References +* +* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param Y output array +* @param strideY stride length for Y +*/ +void API_SUFFIX(stdlib_strided_scusumkbn)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scusumkbn_ndarray)( N, sum, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). +* +* ## References +* +* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y output array +* @param strideY stride length for Y +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scusumkbn_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + float s; + float v; + float t; + float c; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + s = sum; + c = 0.0f; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + t = s + v; + if ( stdlib_base_absf( s ) >= stdlib_base_absf( v ) ) { + c += (s-t) + v; + } else { + c += (v-t) + s; + } + s = t; + Y[ iy ] = s + c; + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/scusumkbn.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/scusumkbn.c deleted file mode 100644 index 131f3e09eeee..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn/src/scusumkbn.c +++ /dev/null @@ -1,79 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusumkbn.h" -#include "stdlib/math/base/special/absf.h" -#include - -/** -* Computes the cumulative sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm. -* -* ## Method -* -* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). -* -* ## References -* -* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). -* -* @param N number of indexed elements -* @param sum initial sum -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scusumkbn( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - int64_t ix; - int64_t iy; - int64_t i; - float s; - float v; - float t; - float c; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - s = sum; - c = 0.0f; - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - t = s + v; - if ( stdlib_base_absf( s ) >= stdlib_base_absf( v ) ) { - c += (s-t) + v; - } else { - c += (v-t) + s; - } - s = t; - Y[ iy ] = s + c; - ix += strideX; - iy += strideY; - } - return; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md index 76711bfe20aa..de14e0dc61a5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/README.md @@ -61,11 +61,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -115,7 +115,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element starting from the second element and to store in the last `N` elements of `y` starting from the last element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -148,16 +148,17 @@ scusumkbn2.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumkbn2 = require( '@stdlib/blas/ext/base/scusumkbn2' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); - +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumkbn2( x.length, 0.0, x, 1, y, -1 ); @@ -168,8 +169,138 @@ console.log( y ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/scusumkbn2.h" +``` + +#### stdlib_strided_scusumkbn2( N, sum, \*X, strideX, \*Y, strideY ) + +Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f } + +stdlib_strided_scusumkbn2( 4, 0.0f, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scusumkbn2( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_scusumkbn2_ndarray( N, sum, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f } + +stdlib_strided_scusumkbn2_ndarray( 4, 0.0f, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scusumkbn2_ndarray( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/scusumkbn2.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative sum: + stdlib_strided_scusumkbn2( N, 0.0f, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js index 4a8201013ca1..b9c749ec6270 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var scusumkbn2 = require( './../lib/scusumkbn2.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,8 +45,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js index b19255d0b9af..083641751d1f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var scusumkbn2 = tryRequire( resolve( __dirname, './../lib/scusumkbn2.native.js' var opts = { 'skip': ( scusumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,8 +50,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js index 99eaa0a272b4..3685e9cf9d6e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -31,7 +30,9 @@ var scusumkbn2 = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -44,8 +45,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js index 138307c744d3..0d2a5008f024 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/benchmark.ndarray.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -36,7 +35,9 @@ var scusumkbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( scusumkbn2 instanceof Error ) }; -var rand = uniform( -100.0, 100.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,8 +50,8 @@ var rand = uniform( -100.0, 100.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/c/benchmark.length.c index 4a6dea1048d6..604f38573a6a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scusumkbn2_ndarray( len, 0.0f, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt index 1994b0296f7d..fce0869a64cd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/repl.txt @@ -1,13 +1,13 @@ {{alias}}( N, sum, x, strideX, y, strideY ) - Computes the cumulative sum of single-precision floating-point strided - array elements using a second-order iterative Kahan–Babuška algorithm. + Computes the cumulative sum of single-precision floating-point strided array + elements using a second-order iterative Kahan–Babuška algorithm. - The `N` and stride parameters determine which elements in the strided - arrays are accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. - Indexing is relative to the first index. To introduce an offset, use - a typed array view. + Indexing is relative to the first index. To introduce an offset, use a typed + array view. If `N <= 0`, the function returns `y` unchanged. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -55,21 +55,20 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 0.0, x1, 2, y1, 1 ) + > {{alias}}( 3, 0.0, x1, 2, y1, 1 ) [ -2.0, 0.0, -1.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ] {{alias}}.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) - Computes the cumulative sum of single-precision floating-point strided - array elements using a second-order iterative Kahan–Babuška algorithm and + Computes the cumulative sum of single-precision floating-point strided array + elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offsetX` and `offsetY` parameter supports indexing semantics - based on starting indices. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters @@ -84,7 +83,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -93,7 +92,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/types/index.d.ts index da4a5dd398d2..7a57cccc4ba5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/docs/types/index.d.ts @@ -28,9 +28,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -50,10 +50,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/c/example.c index 833e717efc6c..0ba3f7f82365 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/blas/ext/base/scusumkbn2.h" -#include #include -#include int main( void ) { // Create strided arrays: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify stride lengths: - const int64_t strideX = 2; - const int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative sum: stdlib_strided_scusumkbn2( N, 0.0f, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js index 4f33d6985df7..80b3a76a3941 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/examples/index.js @@ -18,14 +18,17 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumkbn2 = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); -var y = filledarrayBy( x.length, 'float32', discreteUniform( 0, 10 ) ); +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumkbn2( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include/stdlib/blas/ext/base/scusumkbn2.h b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include/stdlib/blas/ext/base/scusumkbn2.h index 5a4cb6140a2f..f10fbc643ee2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include/stdlib/blas/ext/base/scusumkbn2.h +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/include/stdlib/blas/ext/base/scusumkbn2.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SCUSUMKBN2_H #define STDLIB_BLAS_EXT_BASE_SCUSUMKBN2_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. */ -void stdlib_strided_scusumkbn2( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scusumkbn2)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scusumkbn2_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/index.js index 14d862b67d39..a36a3efce94e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scusumkbn2( N, 0.0, x, 1, y, 1 ); +* scusumkbn2( x.length, 0.0, x, 1, y, 1 ); * // y => [ 1.0, -1.0, 1.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var scusumkbn2 = require( '@stdlib/blas/ext/base/scusumkbn2' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* scusumkbn2.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* scusumkbn2.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.js index 7de0bc2efaeb..5111a6b28bd1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.js @@ -40,22 +40,20 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scusumkbn2( N, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumkbn2( 4, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumkbn2( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.native.js index 16fc87aba102..4f90ad58084c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './scusumkbn2.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -33,33 +31,24 @@ var addon = require( './scusumkbn2.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scusumkbn2( N, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumkbn2( 4, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumkbn2( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - offsetX = minViewBufferIndex( N, strideX, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - - viewX = offsetView( x, offsetX ); - viewY = offsetView( y, offsetY ); - addon( N, sum, viewX, strideX, viewY, strideY ); + addon.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.js index f04bdcd846eb..7fe8684e7ab9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.js @@ -20,8 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -40,9 +40,9 @@ var abs = require( '@stdlib/math/base/special/abs' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -50,59 +50,12 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumkbn2( N, 0.0, x, 1, y, 1 ); +* var v = scusumkbn2( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumkbn2( N, sum, x, strideX, y, strideY ) { - var ccs; - var ix; - var iy; - var cs; - var cc; - var v; - var t; - var c; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - ccs = 0.0; // second order correction term for lost low order bits - cs = 0.0; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - t = float64ToFloat32( sum+v ); - if ( abs( sum ) >= abs( v ) ) { - c = float64ToFloat32( float64ToFloat32( sum-t ) + v ); - } else { - c = float64ToFloat32( float64ToFloat32( v-t ) + sum ); - } - sum = t; - t = float64ToFloat32( cs+c ); - if ( abs( cs ) >= abs( c ) ) { - cc = float64ToFloat32( float64ToFloat32( cs-t ) + c ); - } else { - cc = float64ToFloat32( float64ToFloat32( c-t ) + cs ); - } - cs = t; - ccs = float64ToFloat32( ccs+cc ); - - y[ iy ] = float64ToFloat32( sum + float64ToFloat32( cs+ccs ) ); - ix += strideX; - iy += strideY; - } + ndarray( N, sum, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.native.js index 83d28858eedb..05f97943cdaa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/lib/scusumkbn2.native.js @@ -31,9 +31,9 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -41,9 +41,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumkbn2( N, 0.0, x, 1, y, 1 ); +* var v = scusumkbn2( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumkbn2( N, sum, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/manifest.json index 749982d13002..dd9a160103f0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/manifest.json @@ -28,7 +28,7 @@ { "task": "build", "src": [ - "./src/scusumkbn2.c" + "./src/main.c" ], "include": [ "./include" @@ -41,13 +41,15 @@ "@stdlib/napi/argv", "@stdlib/napi/argv-float", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/scusumkbn2.c" + "./src/main.c" ], "include": [ "./include" @@ -55,13 +57,15 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/special/absf" + "@stdlib/math/base/special/absf", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "examples", "src": [ - "./src/scusumkbn2.c" + "./src/main.c" ], "include": [ "./include" @@ -69,7 +73,9 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/special/absf" + "@stdlib/math/base/special/absf", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] } ] diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.c index 9cc3505ac456..afb2b38179b9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/blas/ext/base/scusumkbn2.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_float.h" @@ -39,8 +40,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_scusumkbn2( N, sum, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_scusumkbn2)( N, sum, X, strideX, Y, strideY ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 5 ); + API_SUFFIX(stdlib_strided_scusumkbn2_ndarray)( N, sum, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/main.c new file mode 100644 index 000000000000..94dad7db9d3f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/main.c @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumkbn2.h" +#include "stdlib/math/base/special/absf.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. +* +* ## Method +* +* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). +* +* ## References +* +* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param Y output array +* @param strideY stride length for Y +*/ +void API_SUFFIX(stdlib_strided_scusumkbn2)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scusumkbn2_ndarray)( N, sum, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). +* +* ## References +* +* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride lengh for X +* @param offsetX starting index for X +* @param Y output array +* @param strideY stride lengt for Y +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scusumkbn2_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + float ccs; + float cs; + float cc; + float v; + float t; + float c; + float s; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + s = sum; + ccs = 0.0f; // second order correction term for lost lower order bits + cs = 0.0f; // first order correction term for lost low order bits + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + t = s + v; + if ( stdlib_base_absf( s ) >= stdlib_base_absf( v ) ) { + c = (s-t) + v; + } else { + c = (v-t) + s; + } + s = t; + t = cs + c; + if ( stdlib_base_absf( cs ) >= stdlib_base_absf( c ) ) { + cc = (cs-t) + c; + } else { + cc = (c-t) + cs; + } + cs = t; + ccs += cc; + + Y[ iy ] = s + cs + ccs; + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/scusumkbn2.c b/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/scusumkbn2.c deleted file mode 100644 index 940efdc4ded8..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumkbn2/src/scusumkbn2.c +++ /dev/null @@ -1,92 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusumkbn2.h" -#include "stdlib/math/base/special/absf.h" -#include - -/** -* Computes the cumulative sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm. -* -* ## Method -* -* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). -* -* ## References -* -* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). -* -* @param N number of indexed elements -* @param sum initial sum -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scusumkbn2( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - int64_t ix; - int64_t iy; - int64_t i; - float ccs; - float cs; - float cc; - float v; - float t; - float c; - float s; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - s = sum; - ccs = 0.0f; // second order correction term for lost lower order bits - cs = 0.0f; // first order correction term for lost low order bits - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - t = s + v; - if ( stdlib_base_absf( s ) >= stdlib_base_absf( v ) ) { - c = (s-t) + v; - } else { - c = (v-t) + s; - } - s = t; - t = cs + c; - if ( stdlib_base_absf( cs ) >= stdlib_base_absf( c ) ) { - cc = (cs-t) + c; - } else { - cc = (c-t) + cs; - } - cs = t; - ccs += cc; - - Y[ iy ] = s + cs + ccs; - ix += strideX; - iy += strideY; - } - return; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md index bc247cf7aae6..6f1e31e5b9c1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/README.md @@ -61,11 +61,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -115,7 +115,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element starting from the second element and to store in the last `N` elements of `y` starting from the last element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -149,15 +149,17 @@ scusumors.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumors = require( '@stdlib/blas/ext/base/scusumors' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumors( x.length, 0.0, x, 1, y, -1 ); @@ -168,6 +170,138 @@ console.log( y ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/scusumors.h" +``` + +#### stdlib_strided_scusumors( N, sum, \*X, strideX, \*Y, strideY ) + +Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f } + +stdlib_strided_scusumors( 4, 0.0f, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scusumors( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_scusumors_ndarray( N, sum, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f } + +stdlib_strided_scusumors_ndarray( 4, 0.0f, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scusumors_ndarray( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/scusumors.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative sum: + stdlib_strided_scusumors( N, 0.0f, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js index 2f42a28b2db3..e041274ef8f5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.js @@ -21,15 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumors = require( './../lib/scusumors.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -40,11 +45,8 @@ var scusumors = require( './../lib/scusumors.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js index 4256c5fc0c77..fe4f0b2a358d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +35,9 @@ var scusumors = tryRequire( resolve( __dirname, './../lib/scusumors.native.js' ) var opts = { 'skip': ( scusumors instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,11 +50,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js index 2c987c262a8a..3138c25ebade 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.js @@ -21,15 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -40,11 +45,8 @@ var scusumors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js index 37cc520539ab..7dd82e9de393 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +35,9 @@ var scusumors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( scusumors instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -49,11 +50,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - - x = filledarrayBy( len, 'float32', uniform( -10.0, 10.0 ) ); - y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/c/benchmark.length.c index 5e3dbe434046..fcb6ef19ea91 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scusumors_ndarray( len, 0.0f, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt index c16d450b275c..81cc057e0a3b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/repl.txt @@ -4,7 +4,7 @@ elements using ordinary recursive summation. The `N` and stride parameters determine which elements in the strided arrays - are accessed at runtime. + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -67,8 +67,8 @@ semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameters support indexing semantics based on starting + indices. Parameters ---------- @@ -82,7 +82,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -91,7 +91,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/types/index.d.ts index 8a0cf6dd1ec4..ccc29eed81a4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/docs/types/index.d.ts @@ -28,9 +28,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -50,10 +50,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/c/example.c index 6414a73d6183..b5e8371f22da 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/blas/ext/base/scusumors.h" -#include #include -#include int main( void ) { // Create strided arrays: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify stride lengths: - const int64_t strideX = 2; - const int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative sum: stdlib_strided_scusumors( N, 0.0f, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js index 7bb9a381a349..2d80bb5d1af9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/examples/index.js @@ -18,15 +18,17 @@ 'use strict'; -var Float32Array = require( '@stdlib/array/float32' ); -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumors = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumors( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/include/stdlib/blas/ext/base/scusumors.h b/lib/node_modules/@stdlib/blas/ext/base/scusumors/include/stdlib/blas/ext/base/scusumors.h index 48771eef6d1d..5e78c9d78ce2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/include/stdlib/blas/ext/base/scusumors.h +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/include/stdlib/blas/ext/base/scusumors.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SCUSUMORS_H #define STDLIB_BLAS_EXT_BASE_SCUSUMORS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation. */ -void stdlib_strided_scusumors( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scusumors)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scusumors_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/index.js index baed5c2f0ff4..fd7469158844 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/index.js @@ -29,9 +29,8 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scusumors( N, 0.0, x, 1, y, 1 ); +* scusumors( x.length, 0.0, x, 1, y, 1 ); * // y => [ 1.0, -1.0, 1.0 ] * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js index 210f8a30aa55..a7a8240c86aa 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.js @@ -31,10 +31,10 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js index 1e5087b5aa64..674ecc746cd0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './scusumors.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -33,10 +31,10 @@ var addon = require( './scusumors.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * @@ -50,16 +48,7 @@ var addon = require( './scusumors.native.js' ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumors( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - - offsetX = minViewBufferIndex( N, strideX, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - - viewX = offsetView( x, offsetX ); - viewY = offsetView( y, offsetY ); - - addon( N, sum, viewX, strideX, viewY, strideY ); + addon.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.js index 45ebaecf7bf3..8510cc98bb01 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.js @@ -20,7 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,9 +32,9 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -41,35 +42,12 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumors( N, 0.0, x, 1, y, 1 ); +* var v = scusumors( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumors( N, sum, x, strideX, y, strideY ) { - var ix; - var iy; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - for ( i = 0; i < N; i++ ) { - sum = float64ToFloat32( sum + x[ ix ] ); - y[ iy ] = sum; - ix += strideX; - iy += strideY; - } + ndarray( N, sum, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.native.js index 7daf20a31f99..4050ada398f4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/lib/scusumors.native.js @@ -31,9 +31,9 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -41,9 +41,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumors( N, 0.0, x, 1, y, 1 ); +* var v = scusumors( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumors( N, sum, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json index 17c6d6c978f5..c8928576cc34 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/manifest.json @@ -28,50 +28,52 @@ { "task": "build", "src": [ - "./src/scusumors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-float", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" ] }, { "task": "benchmark", "src": [ - "./src/scusumors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] }, { "task": "examples", "src": [ - "./src/scusumors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c index 61230aba23f2..40f323dd2997 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/blas/ext/base/scusumors.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_float.h" @@ -39,12 +40,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - - stdlib_strided_scusumors( N, sum, X, strideX, Y, strideY ); - + API_SUFFIX(stdlib_strided_scusumors)( N, sum, X, strideX, Y, strideY ); return NULL; } +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 5 ); + API_SUFFIX(stdlib_strided_scusumors_ndarray)( N, sum, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) - +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/main.c new file mode 100644 index 000000000000..be4515a4925d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/main.c @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumors.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation. +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param Y output array +* @param strideY stride length for Y +*/ +void API_SUFFIX(stdlib_strided_scusumors)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scusumors_ndarray)( N, sum, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y output array +* @param strideY stride length for Y +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scusumors_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + float s; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + s = sum; + for ( i = 0; i < N; i++ ) { + s += X[ ix ]; + Y[ iy ] = s; + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/scusumors.c b/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/scusumors.c deleted file mode 100644 index b755aab74a1b..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumors/src/scusumors.c +++ /dev/null @@ -1,59 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusumors.h" -#include - -/** -* Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation. -* -* @param N number of indexed elements -* @param sum initial sum -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scusumors( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - int64_t ix; - int64_t iy; - int64_t i; - float s; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - s = sum; - for ( i = 0; i < N; i++ ) { - s += X[ ix ]; - Y[ iy ] = s; - ix += strideX; - iy += strideY; - } - return; -} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md index 99de471245d3..58e25d7518a5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/README.md @@ -61,11 +61,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -115,7 +115,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative sum of every other element starting from the second element and to store in the last `N` elements of `y` starting from the last element: ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -149,15 +149,17 @@ scusumpw.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 ); ```javascript -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumpw = require( '@stdlib/blas/ext/base/scusumpw' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumpw( x.length, 0.0, x, 1, y, -1 ); @@ -168,8 +170,138 @@ console.log( y ); + + * * * +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/scusumpw.h" +``` + +#### stdlib_strided_scusumpw( N, sum, \*X, strideX, \*Y, strideY ) + +Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f } + +stdlib_strided_scusumpw( 4, 0.0f, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scusumpw( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_scusumpw_ndarray( N, sum, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f } +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f } + +stdlib_strided_scusumpw_ndarray( 4, 0.0f, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **sum**: `[in] float` initial sum. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scusumpw_ndarray( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/scusumpw.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative sum: + stdlib_strided_scusumpw( N, 0.0f, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
## References diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js index 9140d18b1123..5ab230748e21 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.js @@ -21,18 +21,18 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumpw = require( './../lib/scusumpw.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -45,8 +45,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y = new Float32Array( len ); - var x = filledarrayBy( len, 'float32', rand ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js index e63e3363000e..60d651aced41 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,7 +35,9 @@ var scusumpw = tryRequire( resolve( __dirname, './../lib/scusumpw.native.js' ) ) var opts = { 'skip': ( scusumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -50,8 +50,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js index 0a6f1bc6c736..cf51c329ec9b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.js @@ -21,18 +21,18 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var scusumpw = require( './../lib/ndarray.js' ); // VARIABLES // -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -45,8 +45,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js index 0a386bb1269e..635f00179c15 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var uniform = require( '@stdlib/random/base/uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,7 +35,9 @@ var scusumpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( scusumpw instanceof Error ) }; -var rand = uniform( -10.0, 10.0 ); +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -50,8 +50,8 @@ var rand = uniform( -10.0, 10.0 ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x = filledarrayBy( len, 'float32', rand ); - var y = new Float32Array( len ); + var x = uniform( len, -100, 100, options ); + var y = uniform( len, -100, 100, options ); return benchmark; diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/c/benchmark.length.c index 1ae836b58c1c..bd11818f8375 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scusumpw_ndarray( len, 0.0f, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt index 70e9f3b55348..1088423ebe42 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/repl.txt @@ -23,13 +23,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -66,8 +66,8 @@ elements using pairwise summation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. + buffer, the offset parameter supports indexing semantics based on a starting + index. Parameters ---------- @@ -81,7 +81,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -90,7 +90,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/types/index.d.ts index ca8d5f1d11e6..d14a9db7b98b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/docs/types/index.d.ts @@ -28,9 +28,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @returns output array * * @example @@ -50,10 +50,10 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array - * @param strideX - `x` stride length + * @param strideX - stride length for `x` * @param offsetX - starting index for `x` * @param y - output array - * @param strideY - `y` stride length + * @param strideY - stride length for `y` * @param offsetY - starting index for `y` * @returns output array * @@ -75,9 +75,9 @@ interface Routine { * @param N - number of indexed elements * @param sum - initial sum * @param x - input array -* @param strideX - `x` stride length +* @param strideX - stride length for `x` * @param y - output array -* @param strideY - `y` stride length +* @param strideY - stride length for `y` * @returns output array * * @example diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/c/example.c index de0dde11533f..69cf517ecd18 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/blas/ext/base/scusumpw.h" -#include #include -#include int main( void ) { // Create strided arrays: - const float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - const int64_t N = 4; + const int N = 4; // Specify stride lengths: - const int64_t strideX = 2; - const int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative sum: stdlib_strided_scusumpw( N, 0.0f, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js index 64d24e25349a..7725d88e1b85 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/examples/index.js @@ -18,15 +18,17 @@ 'use strict'; -var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var filledarrayBy = require( '@stdlib/array/filled-by' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var scusumpw = require( './../lib' ); -var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) ); -var y = new Float32Array( x.length ); - +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( x ); + +var y = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); console.log( y ); scusumpw( x.length, 0.0, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include/stdlib/blas/ext/base/scusumpw.h b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include/stdlib/blas/ext/base/scusumpw.h index acbf3964a90b..293e2f54115b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include/stdlib/blas/ext/base/scusumpw.h +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/include/stdlib/blas/ext/base/scusumpw.h @@ -19,7 +19,7 @@ #ifndef STDLIB_BLAS_EXT_BASE_SCUSUMPW_H #define STDLIB_BLAS_EXT_BASE_SCUSUMPW_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. */ -void stdlib_strided_scusumpw( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scusumpw)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation and alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scusumpw_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/index.js index 3658a03afb6e..fddfdca7af09 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scusumpw( N, 0.0, x, 1, y, 1 ); +* scusumpw( x.length, 0.0, x, 1, y, 1 ); * // y => [ 1.0, -1.0, 1.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var scusumpw = require( '@stdlib/blas/ext/base/scusumpw' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* scusumpw.ndarray( N, 0.0, x, 2, 1, y, 1, 0 ); +* scusumpw.ndarray( 4, 0.0, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.js index e162d7d78f4b..d0eb097dd91d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.js @@ -46,22 +46,20 @@ var BLOCKSIZE = 128; * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scusumpw( N, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumpw( 4, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumpw( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.native.js index a5c83d5f57fe..11a4475dcbe0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var minViewBufferIndex = require( '@stdlib/strided/base/min-view-buffer-index' ); -var offsetView = require( '@stdlib/strided/base/offset-view' ); -var addon = require( './scusumpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -33,35 +31,24 @@ var addon = require( './scusumpw.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {NonNegativeInteger} offsetX - starting index for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @param {NonNegativeInteger} offsetY - starting index for `y` * @returns {Float32Array} output array * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scusumpw( N, 0.0, x, 2, 1, y, 1, 0 ); +* var v = scusumpw( 4, 0.0, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -1.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ] */ function scusumpw( N, sum, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - - offsetX = minViewBufferIndex( N, strideX, offsetX ); - offsetY = minViewBufferIndex( N, strideY, offsetY ); - - viewX = offsetView( x, offsetX ); - viewY = offsetView( y, offsetY ); - - addon( N, sum, viewX, strideX, viewY, strideY ); + addon.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.js index 5d08496a20f2..07fc0ce8bd9c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.js @@ -20,7 +20,8 @@ // MODULES // -var cusum = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,9 +40,9 @@ var cusum = require( './ndarray.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -49,29 +50,12 @@ var cusum = require( './ndarray.js' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumpw( N, 0.0, x, 1, y, 1 ); +* var v = scusumpw( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumpw( N, sum, x, strideX, y, strideY ) { - var ix; - var iy; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - return cusum( N, sum, x, strideX, ix, y, strideY, iy ); + return ndarray( N, sum, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.native.js b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.native.js index e5d423a852a5..ce47e2ba9b93 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/lib/scusumpw.native.js @@ -31,9 +31,9 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} sum - initial sum * @param {Float32Array} x - input array -* @param {integer} strideX - `x` stride length +* @param {integer} strideX - stride length for `x` * @param {Float32Array} y - output array -* @param {integer} strideY - `y` stride length +* @param {integer} strideY - stride length for `y` * @returns {Float32Array} output array * * @example @@ -41,9 +41,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scusumpw( N, 0.0, x, 1, y, 1 ); +* var v = scusumpw( x.length, 0.0, x, 1, y, 1 ); * // returns [ 1.0, -1.0, 1.0 ] */ function scusumpw( N, sum, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/manifest.json index 5b3db9e7966a..4188b4abb85e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/manifest.json +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/manifest.json @@ -28,50 +28,52 @@ { "task": "build", "src": [ - "./src/scusumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-float", "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float32array" + "@stdlib/napi/argv-strided-float32array", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] }, { "task": "benchmark", "src": [ - "./src/scusumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", "src": [ - "./src/scusumpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.c index d9f6b05df005..7454b4c9b160 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.c +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/blas/ext/base/scusumpw.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_float.h" @@ -40,10 +41,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_scusumpw)( N, sum, X, strideX, Y, strideY ); + return NULL; +} - stdlib_strided_scusumpw( N, sum, X, strideX, Y, strideY ); - +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, sum, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 5 ); + API_SUFFIX(stdlib_strided_scusumpw_ndarray)( N, sum, X, strideX, offsetX, Y, strideY, offsetY ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/main.c new file mode 100644 index 000000000000..5c1024dded94 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/main.c @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/scusumpw.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param Y output array +* @param strideY stride length for Y +*/ +void API_SUFFIX(stdlib_strided_scusumpw)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scusumpw_ndarray)( N, sum, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. +* +* ## Method +* +* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. +* +* ## References +* +* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). +* +* @param N number of indexed elements +* @param sum initial sum +* @param X input array +* @param strideX stride length for X +* @param Y output array +* @param strideY stride length for Y +*/ +void API_SUFFIX(stdlib_strided_scusumpw_ndarray)( const CBLAS_INT N, const float sum, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + CBLAS_INT n; + float s; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + + // Blocksize for pairwise summation... + if ( N <= 128 ) { + s = 0.0f; + for ( i = 0; i < N; i++ ) { + s += X[ ix ]; + Y[ iy ] = sum + s; + ix += strideX; + iy += strideY; + } + return; + } + n = N / 2; + API_SUFFIX(stdlib_strided_scusumpw_ndarray)( n, sum, X, strideX, ix, Y, strideY, iy ); + iy += (n-1) * strideY; + API_SUFFIX(stdlib_strided_scusumpw_ndarray)( N-n, Y[ iy ], X, strideX, ix+(n*strideX), Y, strideY, iy+strideY ); + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/scusumpw.c b/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/scusumpw.c deleted file mode 100644 index 2ccb45d1a101..000000000000 --- a/lib/node_modules/@stdlib/blas/ext/base/scusumpw/src/scusumpw.c +++ /dev/null @@ -1,94 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/blas/ext/base/scusumpw.h" -#include - -/** -* Computes the cumulative sum of single-precision floating-point strided array elements using pairwise summation. -* -* ## Method -* -* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. -* -* ## References -* -* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). -* -* @param N number of indexed elements -* @param sum initial sum -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scusumpw( const int64_t N, const float sum, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - float *xp1; - float *xp2; - float *yp1; - float *yp2; - int64_t ix; - int64_t iy; - int64_t i; - int64_t n; - float s; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - // Blocksize for pairwise summation... - if ( N <= 128 ) { - s = 0.0f; - for ( i = 0; i < N; i++ ) { - s += X[ ix ]; - Y[ iy ] = sum + s; - ix += strideX; - iy += strideY; - } - return; - } - n = N / 2; - if ( strideX < 0 ) { - xp1 = (float *)X + ( (n-N)*strideX ); - xp2 = (float *)X; - } else { - xp1 = (float *)X; - xp2 = (float *)X + ( n*strideX ); - } - if ( strideY < 0 ) { - yp1 = Y + ( (n-N)*strideY ); - yp2 = Y; - } else { - yp1 = Y; - yp2 = Y + ( n*strideY ); - } - stdlib_strided_scusumpw( n, sum, xp1, strideX, yp1, strideY ); - iy += (n-1) * strideY; - stdlib_strided_scusumpw( N-n, Y[ iy ], xp2, strideX, yp2, strideY ); - return; -} diff --git a/lib/node_modules/@stdlib/complex/float64/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/complex/float64/base/docs/types/index.d.ts index f2865d3cdf6b..b6e35e32732f 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/complex/float64/base/docs/types/index.d.ts @@ -85,6 +85,25 @@ interface Namespace { * * var im = imag( out ); * // returns -1.0 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var out = new Float64Array( 2 ); + * var v = ns.mul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ); + * // returns [ -13.0, -1.0 ] + * + * var bool = ( out === v ); + * // returns true + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var z1 = new Float64Array( [ 5.0, 3.0 ] ); + * var z2 = new Float64Array( [ -2.0, 1.0 ] ); + * + * var out = ns.mul.strided( z1, 1, 0, z2, 1, 0, new Float64Array( 2 ), 1, 0 ); + * // returns [ -13.0, -1.0 ] */ mul: typeof mul; } diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/README.md b/lib/node_modules/@stdlib/complex/float64/base/mul/README.md index 71d756d1f03f..ee4bb7078828 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/mul/README.md +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/README.md @@ -58,6 +58,66 @@ var im = imag( v ); // returns -1.0 ``` +The function supports the following parameters: + +- **z1**: first [complex number][@stdlib/complex/float64/ctor]. +- **z2**: second [complex number][@stdlib/complex/float64/ctor]. + +#### mul.assign( re1, im1, re2, im2, out, strideOut, offsetOut ) + +Multiplies two double-precision complex floating-point numbers and assigns results to a provided output array. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var out = new Float64Array( 2 ); +var v = mul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ); +// returns [ -13.0, -1.0 ] + +var bool = ( out === v ); +// returns true +``` + +The function supports the following parameters: + +- **re1**: real component of the first complex number. +- **im1**: imaginary component of the first complex number. +- **re2**: real component of the second complex number. +- **im2**: imaginary component of the second complex number. +- **out**: output array. +- **strideOut**: stride length for `out`. +- **offsetOut**: starting index for `out`. + +#### mul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo ) + +Multiplies two double-precision complex floating-point numbers stored in real-valued strided array views and assigns results to a provided strided output array. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var z1 = new Float64Array( [ 5.0, 3.0 ] ); +var z2 = new Float64Array( [ -2.0, 1.0 ] ); +var out = new Float64Array( 2 ); + +var v = mul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 ); +// returns [ -13.0, -1.0 ] + +var bool = ( out === v ); +// returns true +``` + +The function supports the following parameters: + +- **z1**: first complex number strided array view. +- **sz1**: stride length for `z1`. +- **oz1**: starting index for `z1`. +- **z2**: second complex number strided array view. +- **sz2**: stride length for `z2`. +- **oz2**: starting index for `z2`. +- **out**: output array. +- **so**: stride length for `out`. +- **oo**: starting index for `out`. +
@@ -224,6 +284,8 @@ int main( void ) {
+[@stdlib/complex/float64/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/complex/float64/ctor + [@stdlib/complex/float64/base/add]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/complex/float64/base/add diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/complex/float64/base/mul/benchmark/benchmark.assign.js new file mode 100644 index 000000000000..d7b8ffa41df2 --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/benchmark/benchmark.assign.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var pkg = require( './../package.json' ).name; +var mul = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// MAIN // + +bench( pkg+':assign', function benchmark( b ) { + var out; + var re; + var im; + var N; + var i; + var j; + var k; + + N = 100; + re = uniform( N, -500.0, 500.0, options ); + im = uniform( N, -500.0, 500.0, options ); + + out = new Float64Array( 2 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + j = i % N; + k = ( i+1 ) % N; + out = mul.assign( re[ j ], im[ j ], re[ k ], im[ k ], out, 1, 0 ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/benchmark/benchmark.strided.js b/lib/node_modules/@stdlib/complex/float64/base/mul/benchmark/benchmark.strided.js new file mode 100644 index 000000000000..ab42981df7ae --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/benchmark/benchmark.strided.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var pkg = require( './../package.json' ).name; +var mul = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// MAIN // + +bench( pkg+':strided', function benchmark( b ) { + var out; + var z1; + var z2; + var N; + var i; + var j; + + N = 50; + z1 = uniform( N*2, -500.0, 500.0, options ); + z2 = uniform( N*2, -500.0, 500.0, options ); + + out = new Float64Array( 2 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + j = ( i % N ) * 2; + out = mul.strided( z1, 1, j, z2, 1, j, out, 1, 0 ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/docs/repl.txt b/lib/node_modules/@stdlib/complex/float64/base/mul/docs/repl.txt index 971b25501178..a08f0cc24c33 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/mul/docs/repl.txt +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/docs/repl.txt @@ -28,6 +28,93 @@ > var im = {{alias:@stdlib/complex/float64/imag}}( out ) -1.0 + +{{alias}}.assign( re1, im1, re2, im2, out, strideOut, offsetOut ) + Multiplies two double-precision complex floating-point numbers and assigns + results to a provided output array. + + Parameters + ---------- + re1: number + Real component of the first complex number. + + im1: number + Imaginary component of the first complex number. + + re2: number + Real component of the second complex number. + + im2: number + Imaginary component of the second complex number. + + out: ArrayLikeObject + Output array. + + strideOut: integer + Stride length. + + offsetOut: integer + Starting index. + + Returns + ------- + out: ArrayLikeObject + Output array. + + Examples + -------- + > var out = new {{alias:@stdlib/array/float64}}( 2 ); + > {{alias}}.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ) + [ -13.0, -1.0 ] + + +{{alias}}.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo ) + Multiplies two double-precision complex floating-point numbers stored in + real-valued strided array views and assigns results to a provided strided + output array. + + Parameters + ---------- + z1: ArrayLikeObject + First complex number view. + + sz1: integer + Stride length for `z1`. + + oz1: integer + Starting index for `z1`. + + z2: ArrayLikeObject + Second complex number view. + + sz2: integer + Stride length for `z2`. + + oz2: integer + Starting index for `z2`. + + out: ArrayLikeObject + Output array. + + so: integer + Stride length for `out`. + + oo: integer + Starting index for `out`. + + Returns + ------- + out: ArrayLikeObject + Output array. + + Examples + -------- + > var z1 = new {{alias:@stdlib/array/float64}}( [ 5.0, 3.0 ] ); + > var z2 = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0 ] ); + > var out = new {{alias:@stdlib/array/float64}}( 2 ); + > {{alias}}.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 ) + [ -13.0, -1.0 ] + See Also -------- diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/index.d.ts b/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/index.d.ts index 896caea64f88..21ae20ad27d6 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/index.d.ts @@ -21,6 +21,90 @@ /// import { Complex128 } from '@stdlib/types/complex'; +import { Collection, NumericArray } from '@stdlib/types/array'; + +/** +* Interface for multiplying two double-precision complex floating-point numbers. +*/ +interface Mul { + /** + * Multiplies two double-precision complex floating-point numbers. + * + * @param z1 - complex number + * @param z2 - complex number + * @returns result + * + * @example + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var z1 = new Complex128( 5.0, 3.0 ); + * // returns + * + * var z2 = new Complex128( -2.0, 1.0 ); + * // returns + * + * var out = mul( z1, z2 ); + * // returns + * + * var re = real( out ); + * // returns -13.0 + * + * var im = imag( out ); + * // returns -1.0 + */ + ( z1: Complex128, z2: Complex128 ): Complex128; + + /** + * Multiplies two double-precision complex floating-point numbers and assigns results to a provided output array. + * + * @param re1 - real component of the first complex number + * @param im1 - imaginary component of the first complex number + * @param re2 - real component of the second complex number + * @param im2 - imaginary component of the second complex number + * @param out - output array + * @param strideOut - stride length + * @param offsetOut - starting index + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var out = new Float64Array( 2 ); + * var v = mul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ); + * // returns [ -13.0, -1.0 ] + * + * var bool = ( out === v ); + * // returns true + */ + assign>( re1: number, im1: number, re2: number, im2: number, out: T, strideOut: number, offsetOut: number ): T; + + /** + * Multiplies two double-precision complex floating-point numbers stored in real-valued strided array views and assigns results to a provided strided output array. + * + * @param z1 - first complex number view + * @param strideZ1 - stride length for `z1` + * @param offsetZ1 - starting index for `z1` + * @param z2 - second complex number view + * @param strideZ2 - stride length for `z2` + * @param offsetZ2 - starting index for `z2` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var z1 = new Float64Array( [ 5.0, 3.0 ] ); + * var z2 = new Float64Array( [ -2.0, 1.0 ] ); + * + * var out = mul.strided( z1, 1, 0, z2, 1, 0, new Float64Array( 2 ), 1, 0 ); + * // returns [ -13.0, -1.0 ] + */ + strided, U extends NumericArray | Collection, V extends NumericArray | Collection>( z1: T, strideZ1: number, offsetZ1: number, z2: U, strideZ2: number, offsetZ2: number, out: V, strideOut: number, offsetOut: number ): V; +} /** * Multiplies two double-precision complex floating-point numbers. @@ -48,8 +132,27 @@ import { Complex128 } from '@stdlib/types/complex'; * * var im = imag( out ); * // returns -1.0 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var out = new Float64Array( 2 ); +* var v = mul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ); +* // returns [ -13.0, -1.0 ] +* +* var bool = ( out === v ); +* // returns true +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var z1 = new Float64Array( [ 5.0, 3.0 ] ); +* var z2 = new Float64Array( [ -2.0, 1.0 ] ); +* +* var out = mul.strided( z1, 1, 0, z2, 1, 0, new Float64Array( 2 ), 1, 0 ); +* // returns [ -13.0, -1.0 ] */ -declare function mul( z1: Complex128, z2: Complex128 ): Complex128; +declare var mul: Mul; // EXPORTS // diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/test.ts b/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/test.ts index 0e931ab559d4..738bd4835200 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/test.ts +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/docs/types/test.ts @@ -65,3 +65,294 @@ import mul = require( './index' ); mul( z ); // $ExpectError mul( z, z, z ); // $ExpectError } + +// Attached to the main export is an `assign` method which returns a collection... +{ + mul.assign( 1.0, 1.0, 1.0, 1.0, new Float64Array( 2 ), 1, 0 ); // $ExpectType Float64Array + mul.assign( 1.0, 1.0, 1.0, 1.0, new Float32Array( 2 ), 1, 0 ); // $ExpectType Float32Array + mul.assign( 1.0, 1.0, 1.0, 1.0, [ 0.0, 0.0 ], 1, 0 ); // $ExpectType number[] +} + +// The compiler throws an error if the `assign` method is provided a first argument which is not a number... +{ + const out = new Float64Array( 2 ); + + mul.assign( true, 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( false, 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( null, 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( undefined, 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( '5', 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( [], 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( {}, 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( ( x: number ): number => x, 2.0, 3.0, 4.0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a second argument which is not a number... +{ + const out = new Float64Array( 2 ); + + mul.assign( 1.0, true, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, false, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, null, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, undefined, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, '5', 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, [], 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, {}, 3.0, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, ( x: number ): number => x, 3.0, 4.0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a third argument which is not a number... +{ + const out = new Float64Array( 2 ); + + mul.assign( 1.0, 2.0, true, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, false, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, null, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, undefined, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, '5', 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, [], 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, {}, 4.0, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, ( x: number ): number => x, 4.0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a fourth argument which is not a number... +{ + const out = new Float64Array( 2 ); + + mul.assign( 1.0, 2.0, 3.0, true, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, false, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, null, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, undefined, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, '5', out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, [], out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, {}, out, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a fifth argument which is not a collection... +{ + mul.assign( 1.0, 2.0, 3.0, 4.0, 1, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, true, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, false, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, null, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, undefined, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, '5', 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, [ '5' ], 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, {}, 1, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a sixth argument which is not a number... +{ + const out = new Float64Array( 2 ); + + mul.assign( 1.0, 2.0, 3.0, 4.0, out, true, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, false, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, null, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, undefined, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, '5', 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, [], 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, {}, 0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a seventh argument which is not a number... +{ + const out = new Float64Array( 2 ); + + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, true ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, false ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, null ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, undefined ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, '5' ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, [] ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, {} ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an unsupported number of arguments... +{ + const out = new Float64Array( 2 ); + + mul.assign(); // $ExpectError + mul.assign( 1.0 ); // $ExpectError + mul.assign( 1.0, 2.0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1 ); // $ExpectError + mul.assign( 1.0, 2.0, 3.0, 4.0, out, 1, 0, {} ); // $ExpectError +} + +// Attached to the main export is a `strided` method which returns a collection... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + + mul.strided( z1, 1, 0, z2, 1, 0, new Float64Array( 2 ), 1, 0 ); // $ExpectType Float64Array + mul.strided( z1, 1, 0, z2, 1, 0, new Float32Array( 2 ), 1, 0 ); // $ExpectType Float32Array + mul.strided( z1, 1, 0, z2, 1, 0, [ 0.0, 0.0 ], 1, 0 ); // $ExpectType number[] +} + +// The compiler throws an error if the `strided` method is provided a first argument which is not a collection... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( true, 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( false, 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( null, 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( undefined, 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( '5', 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( [ '5' ], 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( {}, 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( ( x: number ): number => x, 1, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a second argument which is not a number... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( z1, true, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, false, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, null, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, undefined, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, '5', 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, [], 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, {}, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, ( x: number ): number => x, 0, z2, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a third argument which is not a number... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( 2 ); + + mul.strided( z1, 1, true, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, false, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, null, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, undefined, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, '5', z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, [], z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, {}, z2, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, ( x: number ): number => x, z2, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a fourth argument which is not a collection... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( z1, 1, 0, true, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, false, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, null, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, undefined, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, '5', 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, [ '5' ], 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, {}, 1, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a fifth argument which is not a number... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( z1, 1, 0, z2, true, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, false, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, null, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, undefined, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, '5', 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, [], 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, {}, 0, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a sixth argument which is not a number... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( z1, 1, 0, z2, 1, true, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, false, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, null, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, undefined, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, '5', out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, [], out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, {}, out, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a seventh argument which is not a collection... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + + mul.strided( z1, 1, 0, z2, 1, 0, 1, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, true, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, false, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, null, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, undefined, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, '5', 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, [ '5' ], 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, {}, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided an eighth argument which is not a number... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( z1, 1, 0, z2, 1, 0, out, true, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, false, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, null, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, undefined, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, '5', 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, [], 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, {}, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided a ninth argument which is not a number... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, true ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, false ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, null ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, undefined ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, '5' ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, [] ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, {} ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `strided` method is provided an unsupported number of arguments... +{ + const z1 = new Float64Array( 2 ); + const z2 = new Float64Array( z1.length ); + const out = new Float64Array( z2.length ); + + mul.strided(); // $ExpectError + mul.strided( z1 ); // $ExpectError + mul.strided( z1, 1 ); // $ExpectError + mul.strided( z1, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1 ); // $ExpectError + mul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0, {} ); // $ExpectError +} + diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/lib/assign.js b/lib/node_modules/@stdlib/complex/float64/base/mul/lib/assign.js new file mode 100644 index 000000000000..a9d41af6e087 --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/lib/assign.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Multiplies two double-precision complex floating-point numbers and assigns results to a provided output array. +* +* @param {number} re1 - real component of the first complex number +* @param {number} im1 - imaginary component of the first complex number +* @param {number} re2 - real component of the second complex number +* @param {number} im2 - imaginary component of the second complex number +* @param {Collection} out - output array +* @param {integer} strideOut - stride length +* @param {NonNegativeInteger} offsetOut - starting index +* @returns {Collection} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var out = assign( 5.0, 3.0, -2.0, 1.0, new Float64Array( 2 ), 1, 0 ); +* // returns [ -13.0, -1.0 ] +*/ +function assign( re1, im1, re2, im2, out, strideOut, offsetOut ) { + out[ offsetOut ] = (re1*re2) - (im1*im2); + out[ offsetOut+strideOut ] = (re1*im2) + (im1*re2); + return out; +} + + +// EXPORTS // + +module.exports = assign; diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/lib/index.js b/lib/node_modules/@stdlib/complex/float64/base/mul/lib/index.js index 2c2848d3aedf..d40b0770cd4e 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/mul/lib/index.js +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/lib/index.js @@ -47,9 +47,20 @@ // MODULES // +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); var main = require( './main.js' ); +var assign = require( './assign.js' ); +var strided = require( './strided.js' ); + + +// MAIN // + +setReadOnly( main, 'assign', assign ); +setReadOnly( main, 'strided', strided ); // EXPORTS // module.exports = main; + +// exports: { "assign": "main.assign", "strided": "main.strided" } diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/lib/strided.js b/lib/node_modules/@stdlib/complex/float64/base/mul/lib/strided.js new file mode 100644 index 000000000000..f4665f138c1b --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/lib/strided.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Multiplies two double-precision complex floating-point numbers stored in real-valued strided array views and assigns results to a provided strided output array. +* +* @param {Float64Array} z1 - first complex number view +* @param {integer} strideZ1 - stride length for `z1` +* @param {NonNegativeInteger} offsetZ1 - starting index for `z1` +* @param {Float64Array} z2 - second complex number view +* @param {integer} strideZ2 - stride length for `z2` +* @param {NonNegativeInteger} offsetZ2 - starting index for `z2` +* @param {Collection} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Collection} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var z1 = new Float64Array( [ 5.0, 3.0 ] ); +* var z2 = new Float64Array( [ -2.0, 1.0 ] ); +* +* var out = strided( z1, 1, 0, z2, 1, 0, new Float64Array( 2 ), 1, 0 ); +* // returns [ -13.0, -1.0 ] +*/ +function strided( z1, strideZ1, offsetZ1, z2, strideZ2, offsetZ2, out, strideOut, offsetOut ) { // eslint-disable-line max-len + var re1 = z1[ offsetZ1 ]; + var im1 = z1[ offsetZ1+strideZ1 ]; + var re2 = z2[ offsetZ2 ]; + var im2 = z2[ offsetZ2+strideZ2 ]; + out[ offsetOut ] = (re1*re2) - (im1*im2); + out[ offsetOut+strideOut ] = (re1*im2) + (im1*re2); + return out; +} + + +// EXPORTS // + +module.exports = strided; diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.assign.js b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.assign.js new file mode 100644 index 000000000000..b3418bc06ea8 --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.assign.js @@ -0,0 +1,132 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var mul = require( './../lib/assign.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mul, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function multiplies two complex numbers', function test( t ) { + var expected; + var out; + var v; + + out = new Float64Array( 2 ); + v = mul( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ); + + expected = new Float64Array( [ -13.0, -1.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 4 ); + v = mul( 5.0, 3.0, -2.0, 1.0, out, 2, 0 ); + + expected = new Float64Array( [ -13.0, 0.0, -1.0, 0.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 4 ); + v = mul( 5.0, 3.0, -2.0, 1.0, out, 2, 1 ); + + expected = new Float64Array( [ 0.0, -13.0, 0.0, -1.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 4 ); + v = mul( 5.0, 3.0, -2.0, 1.0, out, -2, 3 ); + + expected = new Float64Array( [ 0.0, -1.0, 0.0, -13.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if a real or imaginary component is `NaN`, all components are `NaN`', function test( t ) { + var expected; + var out; + var v; + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( NaN, 3.0, -2.0, 1.0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( 5.0, 3.0, NaN, 1.0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( NaN, 3.0, NaN, 1.0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( 5.0, NaN, -2.0, 1.0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( 5.0, 3.0, -2.0, NaN, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( 5.0, NaN, -2.0, NaN, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( NaN, NaN, NaN, NaN, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.js b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.js index 71c368aa8ac9..818fdb9bf048 100644 --- a/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.js +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,10 +21,7 @@ // MODULES // var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var Complex128 = require( '@stdlib/complex/float64/ctor' ); -var real = require( '@stdlib/complex/float64/real' ); -var imag = require( '@stdlib/complex/float64/imag' ); +var isMethod = require( '@stdlib/assert/is-method' ); var mul = require( './../lib' ); @@ -36,75 +33,8 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function multiplies two complex numbers', function test( t ) { - var z1; - var z2; - var v; - - z1 = new Complex128( 5.0, 3.0 ); - z2 = new Complex128( -2.0, 1.0 ); - - v = mul( z1, z2 ); - - t.strictEqual( real( v ), -13.0, 'returns expected value' ); - t.strictEqual( imag( v ), -1.0, 'returns expected value' ); - - t.end(); -}); - -tape( 'if a real or imaginary component is `NaN`, all components are `NaN`', function test( t ) { - var z1; - var z2; - var v; - - z1 = new Complex128( NaN, 3.0 ); - z2 = new Complex128( -2.0, 1.0 ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - - z1 = new Complex128( 5.0, 3.0 ); - z2 = new Complex128( NaN, 1.0 ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - - z1 = new Complex128( NaN, 3.0 ); - z2 = new Complex128( NaN, 1.0 ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - - z1 = new Complex128( 5.0, NaN ); - z2 = new Complex128( -2.0, 1.0 ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - - z1 = new Complex128( 5.0, 3.0 ); - z2 = new Complex128( -2.0, NaN ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - - z1 = new Complex128( 5.0, NaN ); - z2 = new Complex128( -2.0, NaN ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - - z1 = new Complex128( NaN, NaN ); - z2 = new Complex128( NaN, NaN ); - - v = mul( z1, z2 ); - t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); - t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); - +tape( 'attached to the main export is an `assign` method', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( isMethod( mul, 'assign' ), true, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.main.js b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.main.js new file mode 100644 index 000000000000..71c368aa8ac9 --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.main.js @@ -0,0 +1,110 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); +var mul = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mul, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function multiplies two complex numbers', function test( t ) { + var z1; + var z2; + var v; + + z1 = new Complex128( 5.0, 3.0 ); + z2 = new Complex128( -2.0, 1.0 ); + + v = mul( z1, z2 ); + + t.strictEqual( real( v ), -13.0, 'returns expected value' ); + t.strictEqual( imag( v ), -1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if a real or imaginary component is `NaN`, all components are `NaN`', function test( t ) { + var z1; + var z2; + var v; + + z1 = new Complex128( NaN, 3.0 ); + z2 = new Complex128( -2.0, 1.0 ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + z1 = new Complex128( 5.0, 3.0 ); + z2 = new Complex128( NaN, 1.0 ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + z1 = new Complex128( NaN, 3.0 ); + z2 = new Complex128( NaN, 1.0 ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + z1 = new Complex128( 5.0, NaN ); + z2 = new Complex128( -2.0, 1.0 ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + z1 = new Complex128( 5.0, 3.0 ); + z2 = new Complex128( -2.0, NaN ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + z1 = new Complex128( 5.0, NaN ); + z2 = new Complex128( -2.0, NaN ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + z1 = new Complex128( NaN, NaN ); + z2 = new Complex128( NaN, NaN ); + + v = mul( z1, z2 ); + t.strictEqual( isnan( real( v ) ), true, 'returns expected value' ); + t.strictEqual( isnan( imag( v ) ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.strided.js b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.strided.js new file mode 100644 index 000000000000..1502ecde6aa6 --- /dev/null +++ b/lib/node_modules/@stdlib/complex/float64/base/mul/test/test.strided.js @@ -0,0 +1,158 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var mul = require( './../lib/strided.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mul, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function multiplies two complex numbers', function test( t ) { + var expected; + var out; + var z1; + var z2; + var v; + + z1 = new Float64Array( [ 5.0, 3.0 ] ); + z2 = new Float64Array( [ -2.0, 1.0 ] ); + out = new Float64Array( 2 ); + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + + expected = new Float64Array( [ -13.0, -1.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 5.0, 0.0, 3.0, 0.0 ] ); + z2 = new Float64Array( [ -2.0, 1.0 ] ); + out = new Float64Array( 4 ); + v = mul( z1, 2, 0, z2, 1, 0, out, 2, 0 ); + + expected = new Float64Array( [ -13.0, 0.0, -1.0, 0.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 5.0, 3.0 ] ); + z2 = new Float64Array( [ 0.0, -2.0, 0.0, 1.0 ] ); + out = new Float64Array( 4 ); + v = mul( z1, 1, 0, z2, 2, 1, out, 2, 1 ); + + expected = new Float64Array( [ 0.0, -13.0, 0.0, -1.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 3.0, 5.0 ] ); + z2 = new Float64Array( [ 1.0, -2.0 ] ); + out = new Float64Array( 4 ); + v = mul( z1, -1, 1, z2, -1, 1, out, -2, 3 ); + + expected = new Float64Array( [ 0.0, -1.0, 0.0, -13.0 ] ); + + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if a real or imaginary component is `NaN`, all components are `NaN`', function test( t ) { + var expected; + var out; + var z1; + var z2; + var v; + + z1 = new Float64Array( [ NaN, 3.0 ] ); + z2 = new Float64Array( [ -2.0, 1.0 ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 5.0, 3.0 ] ); + z2 = new Float64Array( [ NaN, 1.0 ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ NaN, 3.0 ] ); + z2 = new Float64Array( [ NaN, 1.0 ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 5.0, NaN ] ); + z2 = new Float64Array( [ -2.0, 1.0 ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 5.0, 3.0 ] ); + z2 = new Float64Array( [ -2.0, NaN ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ 5.0, NaN ] ); + z2 = new Float64Array( [ -2.0, NaN ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + z1 = new Float64Array( [ NaN, NaN ] ); + z2 = new Float64Array( [ NaN, NaN ] ); + out = new Float64Array( 2 ); + expected = new Float64Array( [ NaN, NaN ] ); + + v = mul( z1, 1, 0, z2, 1, 0, out, 1, 0 ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/constants/float32/half-ln-two/README.md b/lib/node_modules/@stdlib/constants/float32/half-ln-two/README.md index da0b2675a26f..6b199dd62222 100644 --- a/lib/node_modules/@stdlib/constants/float32/half-ln-two/README.md +++ b/lib/node_modules/@stdlib/constants/float32/half-ln-two/README.md @@ -120,6 +120,12 @@ Macro for one half times the [natural logarithm][@stdlib/math/base/special/ln] o
+* * * + +## See Also + +- [`@stdlib/constants/float64/half-ln-two`][@stdlib/constants/float64/half-ln-two]: one half times the natural logarithm of 2. +
@@ -132,6 +138,8 @@ Macro for one half times the [natural logarithm][@stdlib/math/base/special/ln] o +[@stdlib/constants/float64/half-ln-two]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/half-ln-two +
diff --git a/lib/node_modules/@stdlib/constants/float32/ln-pi/README.md b/lib/node_modules/@stdlib/constants/float32/ln-pi/README.md index 85094b7be3f5..6759e78d8263 100644 --- a/lib/node_modules/@stdlib/constants/float32/ln-pi/README.md +++ b/lib/node_modules/@stdlib/constants/float32/ln-pi/README.md @@ -125,6 +125,7 @@ Macro for the natural logarithm of the mathematical constant [π][pi] as a singl ## See Also - [`@stdlib/constants/float32/pi`][@stdlib/constants/float32/pi]: π. +- [`@stdlib/constants/float64/ln-pi`][@stdlib/constants/float64/ln-pi]: natural logarithm of π.
@@ -140,6 +141,8 @@ Macro for the natural logarithm of the mathematical constant [π][pi] as a singl [@stdlib/constants/float32/pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/pi +[@stdlib/constants/float64/ln-pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/ln-pi +
diff --git a/lib/node_modules/@stdlib/constants/float32/ln-ten/README.md b/lib/node_modules/@stdlib/constants/float32/ln-ten/README.md index d2252dfe1c6c..92d4b2c56142 100644 --- a/lib/node_modules/@stdlib/constants/float32/ln-ten/README.md +++ b/lib/node_modules/@stdlib/constants/float32/ln-ten/README.md @@ -124,7 +124,8 @@ Macro for the [natural logarithm][@stdlib/math/base/special/ln] of `10` as a sin ## See Also -- [`@stdlib/constants/float32/ln-two`][@stdlib/constants/float32/ln-two]: natural logarithm of single-precision floating-point number 2. +- [`@stdlib/constants/float32/ln-two`][@stdlib/constants/float32/ln-two]: natural logarithm of 2 as a single-precision floating-point number. +- [`@stdlib/constants/float64/ln-ten`][@stdlib/constants/float64/ln-ten]: natural logarithm of 10.
@@ -140,6 +141,8 @@ Macro for the [natural logarithm][@stdlib/math/base/special/ln] of `10` as a sin [@stdlib/constants/float32/ln-two]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/ln-two +[@stdlib/constants/float64/ln-ten]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/ln-ten +
diff --git a/lib/node_modules/@stdlib/constants/float32/ln-two/README.md b/lib/node_modules/@stdlib/constants/float32/ln-two/README.md index 26f54aeb49d5..f9871b04b97b 100644 --- a/lib/node_modules/@stdlib/constants/float32/ln-two/README.md +++ b/lib/node_modules/@stdlib/constants/float32/ln-two/README.md @@ -118,6 +118,13 @@ Macro for the [natural logarithm][@stdlib/math/base/special/lnf] of `2` as a sin
+* * * + +## See Also + +- [`@stdlib/constants/float32/ln-ten`][@stdlib/constants/float32/ln-ten]: natural logarithm of `10` as a single-precision floating-point number. +- [`@stdlib/constants/float64/ln-two`][@stdlib/constants/float64/ln-two]: natural logarithm of 2. +
@@ -130,6 +137,10 @@ Macro for the [natural logarithm][@stdlib/math/base/special/lnf] of `2` as a sin +[@stdlib/constants/float32/ln-ten]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/ln-ten + +[@stdlib/constants/float64/ln-two]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/ln-two +
diff --git a/lib/node_modules/@stdlib/constants/float32/max-base10-exponent-subnormal/README.md b/lib/node_modules/@stdlib/constants/float32/max-base10-exponent-subnormal/README.md index e5e594250ad9..0dd9a487a26b 100644 --- a/lib/node_modules/@stdlib/constants/float32/max-base10-exponent-subnormal/README.md +++ b/lib/node_modules/@stdlib/constants/float32/max-base10-exponent-subnormal/README.md @@ -126,6 +126,13 @@ Macro for the maximum base 10 exponent for a subnormal [single-precision floatin
+* * * + +## See Also + +- [`@stdlib/constants/float32/max-base10-exponent`][@stdlib/constants/float32/max-base10-exponent]: the maximum base 10 exponent for a single-precision floating-point number. +- [`@stdlib/constants/float64/max-base10-exponent-subnormal`][@stdlib/constants/float64/max-base10-exponent-subnormal]: the maximum base 10 exponent for a subnormal double-precision floating-point number. +
@@ -138,6 +145,10 @@ Macro for the maximum base 10 exponent for a subnormal [single-precision floatin +[@stdlib/constants/float32/max-base10-exponent]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/max-base10-exponent + +[@stdlib/constants/float64/max-base10-exponent-subnormal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-base10-exponent-subnormal +
diff --git a/lib/node_modules/@stdlib/constants/float32/max-base10-exponent/README.md b/lib/node_modules/@stdlib/constants/float32/max-base10-exponent/README.md index e505a1e7114b..c350ba635113 100644 --- a/lib/node_modules/@stdlib/constants/float32/max-base10-exponent/README.md +++ b/lib/node_modules/@stdlib/constants/float32/max-base10-exponent/README.md @@ -130,7 +130,8 @@ Macro for the maximum base 10 exponent for a [single-precision floating-point nu ## See Also -- [`@stdlib/constants/float32/max-base2-exponent`][@stdlib/constants/float32/max-base2-exponent]: the maximum biased base 2 exponent for a single-precision floating-point number. +- [`@stdlib/constants/float32/max-base10-exponent-subnormal`][@stdlib/constants/float32/max-base10-exponent-subnormal]: the maximum base 10 exponent for a subnormal single-precision floating-point number. +- [`@stdlib/constants/float64/max-base10-exponent`][@stdlib/constants/float64/max-base10-exponent]: the maximum base 10 exponent for a double-precision floating-point number.
@@ -144,7 +145,9 @@ Macro for the maximum base 10 exponent for a [single-precision floating-point nu -[@stdlib/constants/float32/max-base2-exponent]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/max-base2-exponent +[@stdlib/constants/float32/max-base10-exponent-subnormal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/max-base10-exponent-subnormal + +[@stdlib/constants/float64/max-base10-exponent]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-base10-exponent diff --git a/lib/node_modules/@stdlib/constants/float32/max-base2-exponent-subnormal/README.md b/lib/node_modules/@stdlib/constants/float32/max-base2-exponent-subnormal/README.md index de187f0fee8a..718b4724caef 100644 --- a/lib/node_modules/@stdlib/constants/float32/max-base2-exponent-subnormal/README.md +++ b/lib/node_modules/@stdlib/constants/float32/max-base2-exponent-subnormal/README.md @@ -124,6 +124,13 @@ Macro for the maximum biased base 2 exponent for a subnormal [single-precision f
+* * * + +## See Also + +- [`@stdlib/constants/float32/max-base2-exponent`][@stdlib/constants/float32/max-base2-exponent]: the maximum biased base 2 exponent for a single-precision floating-point number. +- [`@stdlib/constants/float64/max-base2-exponent-subnormal`][@stdlib/constants/float64/max-base2-exponent-subnormal]: the maximum biased base 2 exponent for a subnormal double-precision floating-point number. +
@@ -136,6 +143,10 @@ Macro for the maximum biased base 2 exponent for a subnormal [single-precision f +[@stdlib/constants/float32/max-base2-exponent]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/max-base2-exponent + +[@stdlib/constants/float64/max-base2-exponent-subnormal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-base2-exponent-subnormal +
diff --git a/lib/node_modules/@stdlib/constants/float32/max-base2-exponent/README.md b/lib/node_modules/@stdlib/constants/float32/max-base2-exponent/README.md index 04b8659f3c8b..524eb7692bce 100644 --- a/lib/node_modules/@stdlib/constants/float32/max-base2-exponent/README.md +++ b/lib/node_modules/@stdlib/constants/float32/max-base2-exponent/README.md @@ -124,6 +124,13 @@ Macro for the maximum biased base 2 exponent for a [single-precision floating-po
+* * * + +## See Also + +- [`@stdlib/constants/float32/max-base2-exponent-subnormal`][@stdlib/constants/float32/max-base2-exponent-subnormal]: the maximum biased base 2 exponent for a subnormal single-precision floating-point number. +- [`@stdlib/constants/float64/max-base2-exponent`][@stdlib/constants/float64/max-base2-exponent]: the maximum biased base 2 exponent for a double-precision floating-point number. +
@@ -136,6 +143,10 @@ Macro for the maximum biased base 2 exponent for a [single-precision floating-po +[@stdlib/constants/float32/max-base2-exponent-subnormal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/max-base2-exponent-subnormal + +[@stdlib/constants/float64/max-base2-exponent]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-base2-exponent +
diff --git a/lib/node_modules/@stdlib/constants/float32/max-safe-fibonacci/README.md b/lib/node_modules/@stdlib/constants/float32/max-safe-fibonacci/README.md index 3b2d566a39f9..0f2583463d5d 100644 --- a/lib/node_modules/@stdlib/constants/float32/max-safe-fibonacci/README.md +++ b/lib/node_modules/@stdlib/constants/float32/max-safe-fibonacci/README.md @@ -149,6 +149,12 @@ Macro for the maximum [safe][safe-integers] [Fibonacci number][fibonacci-number]
+* * * + +## See Also + +- [`@stdlib/constants/float64/max-safe-fibonacci`][@stdlib/constants/float64/max-safe-fibonacci]: maximum safe Fibonacci number when stored in double-precision floating-point format. +
@@ -165,6 +171,8 @@ Macro for the maximum [safe][safe-integers] [Fibonacci number][fibonacci-number] +[@stdlib/constants/float64/max-safe-fibonacci]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-safe-fibonacci +
diff --git a/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md b/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md index bdafa9622fb3..0a6edf628998 100644 --- a/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md +++ b/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md @@ -148,6 +148,12 @@ Macro for the maximum [safe][safe-integers] nth [Fibonacci number][fibonacci-num
+* * * + +## See Also + +- [`@stdlib/constants/float64/max-safe-nth-fibonacci`][@stdlib/constants/float64/max-safe-nth-fibonacci]: maximum safe nth Fibonacci number when stored in double-precision floating-point format. +
@@ -164,6 +170,8 @@ Macro for the maximum [safe][safe-integers] nth [Fibonacci number][fibonacci-num +[@stdlib/constants/float64/max-safe-nth-fibonacci]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-safe-nth-fibonacci +
diff --git a/lib/node_modules/@stdlib/constants/float32/min-base10-exponent-subnormal/README.md b/lib/node_modules/@stdlib/constants/float32/min-base10-exponent-subnormal/README.md index 277a53575e78..a0d340455e88 100644 --- a/lib/node_modules/@stdlib/constants/float32/min-base10-exponent-subnormal/README.md +++ b/lib/node_modules/@stdlib/constants/float32/min-base10-exponent-subnormal/README.md @@ -126,6 +126,13 @@ Macro for the minimum base 10 exponent for a subnormal [single-precision floatin
+* * * + +## See Also + +- [`@stdlib/constants/float32/min-base10-exponent`][@stdlib/constants/float32/min-base10-exponent]: the minimum base 10 exponent for a normal single-precision floating-point number. +- [`@stdlib/constants/float64/min-base10-exponent-subnormal`][@stdlib/constants/float64/min-base10-exponent-subnormal]: the minimum base 10 exponent for a subnormal double-precision floating-point number. +
@@ -138,6 +145,10 @@ Macro for the minimum base 10 exponent for a subnormal [single-precision floatin +[@stdlib/constants/float32/min-base10-exponent]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/min-base10-exponent + +[@stdlib/constants/float64/min-base10-exponent-subnormal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/min-base10-exponent-subnormal +
diff --git a/lib/node_modules/@stdlib/constants/float32/phi/README.md b/lib/node_modules/@stdlib/constants/float32/phi/README.md index 3ecb2169f619..db56af9f2362 100644 --- a/lib/node_modules/@stdlib/constants/float32/phi/README.md +++ b/lib/node_modules/@stdlib/constants/float32/phi/README.md @@ -141,6 +141,12 @@ Macro for the [golden ratio][phi-value].
+* * * + +## See Also + +- [`@stdlib/constants/float64/phi`][@stdlib/constants/float64/phi]: golden ratio. +
@@ -153,6 +159,12 @@ Macro for the [golden ratio][phi-value]. [phi-value]: http://oeis.org/A001622 + + +[@stdlib/constants/float64/phi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/phi + + +
diff --git a/lib/node_modules/@stdlib/constants/float32/pi/README.md b/lib/node_modules/@stdlib/constants/float32/pi/README.md index d09323920e77..ac7408481fde 100644 --- a/lib/node_modules/@stdlib/constants/float32/pi/README.md +++ b/lib/node_modules/@stdlib/constants/float32/pi/README.md @@ -108,6 +108,14 @@ Macro for the mathematical constant [π][pi].
+* * * + +## See Also + +- [`@stdlib/constants/float32/fourth-pi`][@stdlib/constants/float32/fourth-pi]: 1/4 times π. +- [`@stdlib/constants/float32/half-pi`][@stdlib/constants/float32/half-pi]: 1/2 times π. +- [`@stdlib/constants/float32/two-pi`][@stdlib/constants/float32/two-pi]: 2π. +
@@ -118,6 +126,16 @@ Macro for the mathematical constant [π][pi]. [pi]: https://en.wikipedia.org/wiki/Pi + + +[@stdlib/constants/float32/fourth-pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/fourth-pi + +[@stdlib/constants/float32/half-pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/half-pi + +[@stdlib/constants/float32/two-pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/two-pi + + +
diff --git a/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md b/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md index 194bd769c40e..3944e0477b58 100644 --- a/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md +++ b/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md @@ -124,7 +124,7 @@ Macro for the square root of the mathematical constant [π][@stdlib/constants/fl ## See Also -- [`@stdlib/constants/float32/pi`][@stdlib/constants/float32/pi]: π. +- [`@stdlib/constants/float64/sqrt-half-pi`][@stdlib/constants/float64/sqrt-half-pi]: square root of 0.5π.
@@ -134,9 +134,11 @@ Macro for the square root of the mathematical constant [π][@stdlib/constants/fl
+[@stdlib/constants/float32/pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/pi + -[@stdlib/constants/float32/pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/pi +[@stdlib/constants/float64/sqrt-half-pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/sqrt-half-pi diff --git a/lib/node_modules/@stdlib/constants/float32/sqrt-two/README.md b/lib/node_modules/@stdlib/constants/float32/sqrt-two/README.md index 1850d2f11598..720c319fe40c 100644 --- a/lib/node_modules/@stdlib/constants/float32/sqrt-two/README.md +++ b/lib/node_modules/@stdlib/constants/float32/sqrt-two/README.md @@ -120,6 +120,13 @@ Macro for the [square root][@stdlib/math/base/special/sqrtf] of `2` as a single-
+* * * + +## See Also + +- [`@stdlib/constants/float32/sqrt-three`][@stdlib/constants/float32/sqrt-three]: square root of 3 as a single-precision floating-point number. +- [`@stdlib/constants/float64/sqrt-two`][@stdlib/constants/float64/sqrt-two]: square root of 2. +
@@ -132,6 +139,10 @@ Macro for the [square root][@stdlib/math/base/special/sqrtf] of `2` as a single- +[@stdlib/constants/float32/sqrt-three]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/sqrt-three + +[@stdlib/constants/float64/sqrt-two]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/sqrt-two +
diff --git a/lib/node_modules/@stdlib/datasets/cmudict/README.md b/lib/node_modules/@stdlib/datasets/cmudict/README.md index 41ec9cef0417..b38873b220a2 100644 --- a/lib/node_modules/@stdlib/datasets/cmudict/README.md +++ b/lib/node_modules/@stdlib/datasets/cmudict/README.md @@ -58,10 +58,10 @@ The function accepts the following `options`: - **data**: dataset name. The following names are recognized: - - **dict**: the main pronouncing dictionary - - **phones**: manners of articulation for each sound - - **symbols**: complete list of ARPABET symbols used by the dictionary - - **vp**: verbal pronunciations of punctuation marks + - **dict**: the main pronouncing dictionary. + - **phones**: manners of articulation for each sound. + - **symbols**: complete list of ARPABET symbols used by the dictionary. + - **vp**: verbal pronunciations of punctuation marks. To only return the main pronouncing dictionary, set the `data` option to `dict`. diff --git a/lib/node_modules/@stdlib/error/tools/database/data/data.csv b/lib/node_modules/@stdlib/error/tools/database/data/data.csv index 77adcd57dc74..b4703f28aa72 100644 --- a/lib/node_modules/@stdlib/error/tools/database/data/data.csv +++ b/lib/node_modules/@stdlib/error/tools/database/data/data.csv @@ -1068,3 +1068,19 @@ "HD","invalid option. Each key object's `name` property must be a string. Value: `%s`.","TypeError" "HE","invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","TypeError" "HF","invalid option. Each action must be an array of objects. Value: `%s`.","TypeError" +"HG","invalid argument. First argument must be a valid index ndarray.","TypeError" +"HH","invalid operation. This ndarray index instance has already been freed and can no longer be used.","Error" +"HI","invalid operation. Unrecognized ndarray index type. Value: `%s`.","Error" +"HJ","invalid operation. Index exceeds ndarray bounds.","RangeError" +"HK","invalid operation. Number of indices does not match the number of array dimensions. Array shape: (%s). Index dimensions: %u.","RangeError" +"HL","invalid operation. Unable to resolve ndarray index. Value: `%s`.","Error" +"HM","invalid argument. First argument is not compatible with the specified index ""kind"". Type: %s. Kind: %s.","TypeError" +"HN","invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.","RangeError" +"HO","invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.","RangeError" +"HP","invalid argument. Must provide unique dimension indices. Value: `[%s]`.","Error" +"HQ","invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.","RangeError" +"HR","invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.","Error" +"HS","invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","RangeError" +"HT","invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`","TypeError" +"HU","invalid argument. First argument must be a valid action name. Value: `%s`.","TypeError" +"HV","invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`","TypeError" diff --git a/lib/node_modules/@stdlib/error/tools/database/data/data.json b/lib/node_modules/@stdlib/error/tools/database/data/data.json index b37325d25a45..0fb9960c4aeb 100644 --- a/lib/node_modules/@stdlib/error/tools/database/data/data.json +++ b/lib/node_modules/@stdlib/error/tools/database/data/data.json @@ -1 +1 @@ -{"10":"invalid operation. Cannot reset a REPL which has already closed.","11":"invalid operation. Cannot clear a REPL which has already closed.","12":"invalid operation. Cannot clear the line of a REPL which has already closed.","13":"invalid operation. Cannot clear the command buffer of a REPL which has already closed.","14":"invalid argument. Provided command either does not contain an `await` expression or contains a top-level `return` which is not allowed.","15":"invalid argument. Must provide a program AST node.","16":"invalid invocation. Insufficient arguments. Must provide a REPL instance.","17":"invalid operation. No presentation to reload. Use the `load()` method to load a presentation.","18":"invalid operation. No presentation file to watch. Use the `load()` method to load a presentation.","19":"unexpected error. Encountered a \"rename\" event for the source presentation file. No longer watching source presentation file for changes.","20":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user is watching, an access token.","21":"unexpected error. Unable to resolve package directory as unable to find a `package.json` in a parent directory.","22":"invalid argument. Source code does not contain JSDoc comment with function options.","23":"unexpected error. Unable to resolve root project directory.","24":"invalid argument. An iterator must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","25":"invalid argument. Callback must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","26":"invalid argument. Array-like object arguments must have a length which is a multiple of two. Length: `%u`.","27":"invalid argument. Array-like object and typed array arguments must have a length which is a multiple of two. Length: `%u`.","28":"invalid argument. ArrayBuffer byte length must be a multiple of `%u`. Byte length: `%u`.","29":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","30":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.","31":"invalid argument. Fifth argument must be a function. Value: `%s`.","32":"invalid argument. Fourth argument must be a function. Value: `%s`.","33":"invalid argument. Second argument must be either an integer (starting index) or a callback function. Value: `%s`.","34":"invalid argument. Third argument must be either an integer (ending index) or a callback function. Value: `%s`.","35":"invalid argument. Second argument must be either an integer (starting view index) or a callback function. Value: `%s`.","36":"invalid argument. Third argument must be either an integer (ending view index) or a callback function. Value: `%s`.","37":"invalid argument. Second argument must be a recognized data type. Value: `%s`.","38":"invalid argument. First argument must be array-like. Value: `%s`.","39":"invalid argument. Second argument must be a string. Value: `%s`.","40":"invalid argument. Must provide either a Date object, a JavaScript timestamp (i.e., a nonnegative integer), or a date string. Value: `%s`.","41":"invalid option. Unrecognized rounding mode. Option: `%s`.","42":"invalid argument. Third argument must be either a nonnegative integer or an options object. Value: `%s`.","43":"invalid argument. Fourth argument must be an object. Value: `%s`.","44":"invalid argument. First argument must an iterator protocol-compliant object. Value: `%s`.","45":"invalid argument. Second argument must be a positive integer. Value: `%s`.","46":"invalid argument. First argument must be an iterator protocol-compliant object. Value: `%s`.","47":"invalid argument. Must provide an object. Value: `%s`.","48":"invalid argument. Object property values must be functions. Key: `%s`. Value: `%s`.","49":"invalid argument. First argument must be a number. Value: `%s`.","50":"invalid option. Second `%s` parameter option must be a positive integer. Option: `%s`.","51":"invalid argument. First argument must be an array. Value: `%s`.","52":"invalid argument. First argument must be an array of length `%u`. Value: `%s`.","53":"invalid argument. First argument must be an array of length %u. Value: `%s`.","54":"unexpected error. Scaling weight vector by nonpositive value, likely due to too large value of eta * lambda. Value: `%f`.","55":"invalid argument. Second argument must be a boolean. Value: `%s`.","56":"invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.","57":"invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.","58":"invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.","59":"invalid option. `%s` option must be a recognized casting mode. Option: `%s`.","60":"invalid argument. Input string must have a length equal to %u. Value: `%s`.","61":"invalid assignment. `%s` must be a boolean. Value: `%s`.","62":"invalid assignment. `%s` must be a string. Value: `%s`.","63":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","64":"invalid assignment. `%s` must be a positive number. Value: `%s`.","65":"invalid assignment. `%s` must be either an array of strings or an empty array. Value: `%s`.","66":"invalid assignment. `%s` must be a number or number array. Value: `%s`.","67":"invalid assignment. A `%s` must be a number on the interval: [0, 1]. Value: `%f`.","68":"invalid assignment. `%s` must be a string or a string array. Value: `%s`","69":"invalid assignment. Unsupported/unrecognized line style. Must be one of the following: \"%s\". Value: `%s`.","70":"invalid argument. Must provide a Uint32Array. Value: `%s`.","71":"invalid argument. First argument must be a positive number. Value: `%s`.","72":"invalid argument. Second argument must be a positive number. Value: `%s`.","73":"invalid argument. Second argument must be a probability. Value: `%s`.","74":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%s`.","75":"invalid option. `%s` option must have a `MIN` property specifying the minimum possible pseudorandom integer value.","76":"invalid option. `%s` option must have a `MAX` property specifying the maximum possible pseudorandom integer value.","77":"invalid argument. First argument must be an integer and not NaN. Value: `%s`.","78":"invalid argument. Second argument must be an integer and not NaN. Value: `%s`.","79":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d,%d]`.","80":"invalid argument. First argument must be either a string containing presentation text or an options object specifying a presentation file to load. Value: `%s`.","81":"invalid argument. Second argument must be an options object. Value: `%s`.","82":"invalid argument. Invalid presentation identifier. Must be either a string or nonnegative integer. Value: `%s`.","83":"invalid argument. Workspace name already exists. Value: `%s`.","84":"invalid argument. Must provide a string, regular expression, nonnegative integer, or an array of nonnegative integers. Value: `%s`.","85":"invalid argument. Unrecognized tutorial name. Value: `%s`.","86":"invalid argument. Documentation argument must be a string. Value: `%s`.","87":"invalid option. `%s` option must be a regular expression. Option: `%s`.","88":"internal error. Unrecognized pattern type: `%s`.","89":"invalid option. `%s` option must be a readable stream. Option: `%s`.","90":"invalid argument. Denominator degrees of freedom must be a positive number. Value: `%s`.","91":"invalid argument. Scale parameter must be a number. Value: `%s`.","92":"invalid argument. Mean parameter `%s` must be a probability. Value: `%s`.","93":"invalid argument. Population size must be a nonnegative integer. Value: `%s`.","94":"invalid argument. Subpopulation size must be a nonnegative integer. Value: `%s`.","95":"invalid argument. Number of draws must be a nonnegative integer. Value: `%s`.","96":"invalid assignment. Must be a nonnegative integer. Value: `%s`.","97":"invalid assignment. Must be larger than or equal to %u. Value: `%u`.","98":"invalid assignment. Must be less than or equal to %u. Value: `%u`.","99":"invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.","00":"not implemented","01":"invalid invocation. `this` context must be a constructor.","02":"invalid invocation. `this` is not a complex number array.","03":"invalid arguments. Target array lacks sufficient storage to accommodate source values.","04":"invalid arguments. Creating a generic array from an ArrayBuffer is not supported.","05":"invalid arguments. Must provide a length, typed array, array-like object, or an iterable.","06":"invalid arguments. Generated array exceeds maximum array length.","07":"invalid arguments. If either of the first two arguments are complex numbers, the output array must be a complex number array or a \"generic\" array-like object.","08":"invalid arguments. If either of the first two arguments are complex numbers, the output array data type must be a complex number data type or \"generic\".","09":"not supported. The current environment does not support SharedArrayBuffers, and, unfortunately, SharedArrayBuffers cannot be polyfilled. For shared memory applications, upgrade your runtime environment to one which supports SharedArrayBuffers.","0A":"insufficient arguments. Must provide a search value.","0B":"invalid argument. Attempted to add duplicate listener.","0C":"exception","0D":"unexpected error. Benchmark failed.","0E":"unexpected error. Invalid benchmark.","0F":"unexpected error.","0G":"invalid invocation. Constructor must be called with the `new` keyword.","0H":"unexpected error. Max retries exceeded. Too many open files.","0I":"insufficient arguments. Must provide two or more iterators.","0J":"insufficient arguments. Must provide both an iterator and a static value.","0K":"invalid invocation. `this` is not a fluent interface iterator.","0L":"insufficient arguments. Must provide a hash function.","0M":"invalid argument. Iterator arguments must be iterator protocol-compliant objects.","0N":"insufficient arguments. Must provide at least one iterator function.","0O":"invalid argument. Providing a number is not supported.","0P":"invalid argument. Providing a complex number is not supported.","0Q":"invalid argument. Providing an ndarray is not supported.","0R":"invalid argument. Providing an array-like object is not supported.","0S":"invalid argument. If the first argument is an ndarray, the second argument must be an ndarray.","0T":"invalid argument. Output array must have the same number of elements (i.e., length) as the input array.","0U":"invalid argument. If the first argument is an array-like object, the second argument must be an array-like object.","0V":"invalid argument. Providing a number is not supported. Consider providing a zero-dimensional ndarray containing the numeric value.","0W":"invalid argument. Providing a complex number is not supported. Consider providing a zero-dimensional ndarray containing the complex number value.","0X":"invalid arguments. Must provide either a data source, array shape, or both.","0Y":"invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.","0Z":"invalid argument. Cannot broadcast an array to a shape having fewer dimensions. Arrays can only be broadcasted to shapes having the same or more dimensions.","0a":"invalid argument. First argument must contain at least one element.","0b":"invalid arguments. The length of the first argument is incompatible with the second and third arguments.","0c":"invalid argument. Must provide an ndarray having two or more dimensions.","0d":"invalid arguments. Arrays must have the same shape.","0e":"invalid invocation. Cannot write to a read-only array.","0f":"invalid argument. Fourth argument length must be equal to 1 when creating a zero-dimensional ndarray.","0g":"invalid arguments. The input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","0h":"invalid arguments. Interface must accept at least one input and/or output ndarray. Based on the provided arguments, `nin+nout` equals `0`.","0i":"invalid arguments. Fourth argument does not equal the number of input and output ndarrays.","0j":"invalid argument. Unexpected number of types. A type must be specified for each input and output ndarray for each provided ndarray function.","0k":"invalid argument. The third argument must have the same number of elements as the first argument.","0l":"invalid invocation. Insufficient arguments.","0m":"invalid invocation. Too many arguments.","0n":"invalid arguments. Unable to resolve an ndarray function supporting the provided array argument data types.","0o":"invalid operation. Unable to load Electron. Ensure Electron is installed and try again.","0p":"invalid operation. A browser environment has no support for changing the current working directory.","0q":"invalid operation. The environment does not support reading from `stdin`.","0r":"unexpected error. PRNG returned NaN.","0s":"invalid argument. Third argument must be less than or equal to the first argument.","0t":"invalid argument. Second argument must be less than or equal to the first argument.","0u":"invalid operation. Cannot delete the `base` workspace.","0v":"invalid invocation. Must provide either a string containing presentation text or an options object specifying a presentation file to load.","0w":"invalid argument. When not provided presentation text, an options argument must specify a presentation file to load.","0x":"invalid invocation. Not currently in a presentation workspace. Must provide either a string or nonnegative integer which corresponds to the identifier of the presentation to be stopped.","0y":"unexpected error. Command execution terminated.","0z":"invalid operation. Cannot load a file into a REPL which has already closed.","1A":"invalid arguments. First and second arguments must be arrays having the same length.","1B":"invalid arguments. Subpopulation size must be less than or equal to population size.","1C":"invalid arguments. Number of draws must be less than or equal to population size.","1D":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number number of observations must be greater than zero).","1E":"invalid arguments. First and second arguments must have the same length.","1F":"invalid arguments. First and second arguments must be arrays having the same length.","1G":"invalid arguments. First and second argument must have the same length.","1H":"invalid arguments. Not enough observations. First and second arguments must contain at least four observations.","1I":"invalid arguments. The first and second arguments must have the same length.","1J":"`x` or `x - y` cannot be zero for all elements.","1K":"invalid arguments. Strided array parameters are incompatible with the provided array-like object. Linear index exceeds array bounds.","1L":"invalid arguments. Unable to resolve a strided array function supporting the provided array argument data types.","1M":"invalid arguments. Interface must accept at least one strided input and/or output array. Based on the provided arguments, `nin+nout` equals `0`.","1N":"invalid argument. Unexpected number of types. A type must be specified for each strided input and output array for each provided strided array function.","1O":"invalid argument. Fourth argument is incompatible with the number of strided input and output arrays.","1P":"invalid argument. Input array offset must be a nonnegative integer.","1Q":"invalid argument. Output array offset must be a nonnegative integer.","1R":"invalid argument. Input array must be an array-like object.","1S":"invalid argument. Output array must be an array-like object.","1T":"invalid argument. Input array has insufficient elements based on the associated stride and the number of indexed elements.","1U":"invalid argument. Output array has insufficient elements based on the associated stride and the number of indexed elements.","1V":"insufficient arguments. Must provide either an array of code points or one or more code points as separate arguments.","1W":"invalid argument. Third argument must not be an empty string.","1X":"invalid argument. Pad string must not be an empty string.","1Y":"insufficient arguments. Must provide multiple functions to compose.","1Z":"insufficient arguments. Must provide multiple functions to execute sequentially.","1a":"invalid arguments. First and last arguments must be the same length.","1b":"insufficient arguments. Must provide at least two objects.","1c":"invalid invocation. `this` is not a compact adjacency matrix.","1d":"invalid argument. Cannot specify one or more accessors and a value or writable attribute in the property descriptor.","1e":"invalid argument. The list does not contain the provided list node.","1f":"unexpected error. Unable to resolve global object.","1g":"invalid argument. The output ndarray must be writable. Cannot write to a read-only ndarray.","1h":"invalid arguments. Input and output arrays must have the same length.","1i":"invalid arguments. Input and output arrays must have the same number of elements (i.e., length).","1j":"invalid arguments. Input ndarrays must be broadcast compatible.","1k":"invalid arguments. Input arrays must have the same number of elements (i.e., length).","1l":"insufficient arguments. Must provide both a target object and one or more source objects.","1m":"invalid invocation. `this` is not host tuple.","1n":"invalid invocation. `this` is not the host tuple factory.","1o":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented.","1p":"invalid argument. Second argument must have a length equal to the size of the outermost input array dimension.","1q":"evaluation error. Did not receive timing results.","1r":"evaluation error. Unable to retrieve evaluation results. Ensure that the provided snippet does not return prematurely.","1s":"invalid argument. Must provide a zipped array.","1t":"invalid argument. Array must only contain arrays.","1u":"invalid argument. Indices must be specified as an array.","1v":"invalid argument. All indices must be integers.","1w":"invalid argument. Must provide valid indices (i.e., an index must be on the interval [0, len], where len is the tuple length).","1x":"insufficient arguments. Must provide at least one array.","1y":"invalid argument. Must provide a username or, to get who an authenticated user is following, an access token.","1z":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user has starred, an access token.","2A":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","2B":"invalid argument. First argument must be an ArrayBuffer. Value: `%s`.","2C":"invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.","2D":"invalid argument. Byte offset must be a multiple of `%u`. Value: `%u`.","2E":"invalid arguments. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","2F":"invalid argument. Length must be a nonnegative integer. Value: `%s`.","2G":"invalid arguments. ArrayBuffer has insufficient capacity. Either decrease the array length or provide a bigger buffer. Minimum capacity: `%u`.","2H":"invalid argument. Second argument must be a function. Value: `%s`.","2I":"invalid argument. First argument must have a length which is a multiple of two. Length: `%u`.","2J":"invalid argument. First argument must be an array-like object or an iterable. Value: `%s`.","2K":"invalid argument. Must provide a nonnegative integer. Value: `%s`.","2L":"invalid argument. Index argument must be a nonnegative integer. Value: `%s`.","2M":"invalid argument. Index argument is out-of-bounds. Value: `%u`.","2N":"invalid argument. First argument must be either a complex number, an array-like object, or a complex number array. Value: `%s`.","2O":"invalid argument. First argument must be an array-like object. Value: `%s`.","2P":"invalid argument. Second argument must be a recognized array data type. Value: `%s`.","2Q":"invalid argument. Second argument must have a recognized/supported data type. Type: `%s`. Value: `%s`.","2R":"invalid argument. Unable to parse %s date.","2S":"invalid argument. Numeric %s date must be either a Unix or JavaScript timestamp.","2T":"invalid argument. %s date must either be a date string, Date object, Unix timestamp, or JavaScript timestamp.","2U":"invalid argument. Length must be a positive integer. Value: `%s`.","2V":"invalid argument. Options argument must be an object. Value: `%s`.","2W":"invalid option. `%s` option must be a string. Option: `%s`.","2X":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","2Y":"invalid argument. Must provide a recognized data type. Value: `%s`.","2Z":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, typed array, or array-like object. Value: `%s`.","2a":"invalid argument. Must provide a length, typed array, array-like object, or an iterable. Value: `%s`.","2b":"invalid argument. Callback argument must be a function. Value: `%s`.","2c":"invalid argument. Iterator argument must be an iterator protocol-compliant object. Value: `%s`.","2d":"invalid argument. First argument must be a nonnegative integer. Value: `%s`.","2e":"invalid argument. Third argument must be a recognized data type. Value: `%s`.","2f":"invalid argument. First argument must be either an array, typed array, or complex typed array. Value: `%s`.","2g":"invalid argument. Start must be numeric. Value: `%s`.","2h":"invalid argument. Stop must be numeric. Value: `%s`.","2i":"invalid argument. Increment must be numeric. Value: `%s`.","2j":"invalid argument. First argument must be either a real or complex number. Value: `%s`.","2k":"invalid argument. Second argument must be either a real or complex number. Value: `%s`.","2l":"invalid argument. Third argument must be an array-like object. Value: `%s`.","2m":"invalid argument. Third argument must be a nonnegative integer. Value: `%s`.","2n":"invalid option. `%s` option must be a real or complex floating-point data type or \"generic\". Option: `%s`.","2o":"invalid option. `%s` option must be a boolean. Option: `%s`.","2p":"invalid argument. Exponent of start value must be numeric. Value: `%s`.","2q":"invalid argument. Exponent of stop value must be numeric. Value: `%s`.","2r":"invalid argument. First argument must be either an array length or an array-like object. Value: `%s`.","2s":"invalid argument. Must provide a typed array or ArrayBuffer. Value: `%s`.","2t":"invalid option. `%s` option must be a nonnegative integer. Option: `%s`.","2u":"invalid argument. Must provide an array-like object. Value: `%s`.","2v":"invalid option. `%s` option must be either `1` or `-1`. Option: `%s`.","2w":"invalid argument. Second argument must be either a function or an options object. Value: `%s`.","2x":"invalid argument. Must provide a typed array. Value: `%s`.","2y":"invalid argument. Second argument must be an array-like object. Value: `%s`.","2z":"invalid argument. Third argument must be an integer. Value: `%s`.","3A":"invalid argument. Key path must be a string or a key array. Value: `%s`.","3B":"invalid argument. Must provide a string. Value: `%s`.","3C":"invalid argument. Must provide a valid position (i.e., a nonnegative integer). Value: `%s`.","3D":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%u`.","3E":"invalid argument. Second argument must be callable. Value: `%s`.","3F":"invalid argument. First argument must be a string. Value: `%s`.","3G":"invalid argument. Fourth argument must be one of the following: \"%s\". Value: `%s`.","3H":"invalid argument. Fifth argument must be one of the following: \"%s\". Value: `%s`.","3I":"invalid argument. Second argument must be either an object (except null) or a function. Value: `%s`.","3J":"invalid argument. Must provide a function. Value: `%s`.","3K":"invalid argument. Must provide either an options object or a callback function. Value: `%s`.","3L":"invalid argument. First argument must be an object. Value: `%s`.","3M":"invalid option. `%s` option must be a writable stream. Option: `%s`.","3N":"invalid argument. Third argument must be a function. Value: `%s`.","3O":"invalid option. `%s` option must be either a positive integer or `null`. Option: `%s`.","3P":"invalid option. `%s` option must be a positive integer. Option: `%s`.","3Q":"invalid argument. First argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3R":"invalid argument. Second argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3S":"invalid argument. Arrays must be the same length. First argument length: `%u`. Second argument length: `%u`.","3T":"invalid argument. First argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3U":"invalid argument. Second argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3V":"invalid argument. First argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3W":"invalid argument. Second argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3X":"invalid argument. Second argument must be a nonnegative integer. Value: `%s`.","3Y":"invalid argument. Second argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3Z":"invalid argument. Last argument must be a nonnegative integer. Value: `%s`.","3a":"invalid argument. Last argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3b":"invalid argument. Must provide a Buffer. Value: `%s`.","3c":"invalid argument. First argument must be a function. Value: `%s`.","3d":"invalid argument. Third argument must be a constructor function. Value: `%s`.","3e":"invalid argument. Real component must be a number. Value: `%s`.","3f":"invalid argument. Imaginary component must be a number. Value: `%s`.","3g":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","3h":"invalid argument. Unsupported/unrecognized dataset name. Value: `%s`.","3i":"invalid option. Unrecognized `%s`. Option: `[%s]`.","3j":"invalid option. `%s` option must be a string or an array of strings. Option: `%s`.","3k":"invalid option. `%s` option must be a positive integer or an array of positive integers. Option: `%s`.","3l":"invalid option. `%s` option must be a positive integer array of length two. Option: `%s`.","3m":"invalid option. `%s` option cannot be less than 1790. Option: `%s`.","3n":"invalid option. `%s` option cannot be greater than 5000. Option: `%s`.","3o":"invalid argument. Must provide an error object. Value: `%s`.","3p":"invalid argument. First argument must be a valid file descriptor (i.e., nonnegative integer). Value: `%s`.","3q":"invalid argument. Last argument must be a function. Value: `%s`.","3r":"invalid argument. Must provide a valid file descriptor (i.e., a nonnegative integer). Value: `%s`.","3s":"invalid argument. First argument must be an array of strings. Value: `%s`.","3t":"invalid argument. Options argument must be either a string or an object. Value: `%s`.","3u":"invalid argument. Predicate function must be a function. Value: `%s`.","3v":"invalid argument. First argument must be an iterator. Value: `%s`.","3w":"invalid argument. Must provide an iterator. Value: `%s`.","3x":"invalid argument. Must provide an iterator protocol-compliant object. Argument: `%u`. Value: `%s`.","3y":"invalid argument. Must provide an iterator protocol-compliant object. Value: `%s`.","3z":"invalid argument. Unable to parse date string. Value: `%s`.","4A":"invalid argument. Second argument must be a number. Value: `%s`.","4B":"invalid argument. Third argument must be a number. Value: `%s`.","4C":"invalid argument. Hash function argument must be a function. Value: `%s`.","4D":"invalid option. `%s` option must be a positive number. Option: `%s`.","4E":"invalid argument. Third argument must be either a nonnegative integer or an object. Value: `%s`.","4F":"invalid arguments. All arguments must be functions. Value: `%s`.","4G":"invalid argument. Each iterator function, except the last iterator function, within an iterator pipeline must return an iterator. Value: `%s`.","4H":"invalid argument. Must provide an an iterator. Value: `%s`.","4I":"invalid return value. Callback function must return an integer. Value: `%s`.","4J":"invalid argument. Fourth argument must be a boolean. Value: `%s`.","4K":"invalid return value. Callback function must return a positive integer. Value: `%s`.","4L":"invalid argument. Fifth argument must be a callback function. Value: `%s`.","4M":"invalid argument. Third argument must be either an integer (starting index) or a callback function. Value: `%s`.","4N":"invalid argument. Fourth argument must be either an integer (ending index) or a callback function. Value: `%s`.","4O":"invalid argument. Unrecognized/unsupported scale function. Value: `%s`.","4P":"invalid argument. Must provide an iterator protocol-compliant object or a number. Argument: `%u`. Value: `%s`.","4Q":"invalid argument. First argument must be a finite number. Value: `%s`.","4R":"invalid option. `%s` option must be a positive finite number. Option: `%s`.","4S":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","4T":"invalid option. `%s` option must be less than or equal to 79. Option: `%u`.","4U":"invalid option. `%s` option must be less than or equal to 77. Option: `%u`.","4V":"invalid argument. Must provide an argument having a supported data type. Value: `%s`.","4W":"invalid option. Unsupported policy for determining an output array data type. Option: `%s`.","4X":"invalid option. `%s` option must be a recognized/supported data type. Option: `%s`.","4Y":"invalid option. `%s` option must be a recognized/supported output array data type policy. Option: `%s`.","4Z":"invalid argument. Resolution table must be an object. Value: `%s`.","4a":"invalid argument. Resolution table `%s` field value must be either a function or null. Value: `%s`.","4b":"invalid argument. First argument must be a positive integer. Value: `%s`.","4c":"invalid argument. First argument must be a one-dimensional ndarray. Value: `%s`.","4d":"invalid argument. Second argument must be either +1 or -1. Value: `%s`.","4e":"invalid argument. First argument must be a one-dimensional ndarray of length %u. Actual length: `%u`.","4f":"invalid argument. First argument must be an ndarray. Value: `%s`.","4g":"invalid argument. First argument must be an ndarray whose last dimension is of size `%u`. Actual size: `%u`.","4h":"invalid argument. Second argument is incompatible with model loss function. Probability predictions are only supported when the loss function is one of the following: \"%s\". Model loss function: `%s`.","4i":"invalid argument. Second argument must be a string value equal to either \"label\", \"probability\", or \"linear\". Value: `%s`.","4j":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of `eta*lambda`. Value: `%f`.","4k":"invalid option. `%s` option must be a nonnegative number. Option: `%s`.","4l":"invalid option. `%s` option must be an array-like object. Option: `%s`.","4m":"invalid option. First `%s` option must be one of the following: \"%s\". Option: `%s`.","4n":"invalid option. Second `%s` option must be a positive number. Option: `%s`.","4o":"invalid option. Third `%s` option must be a number. Option: `%s`.","4p":"invalid argument. Argument specifying number of dimensions must be a positive integer. Value: `%s`.","4q":"invalid argument. First argument must either be a positive integer specifying the number of clusters or a matrix containing initial centroids. Value: `%s`.","4r":"invalid option. First `%s` parameter option must be greater than or equal to the number of clusters. Options: `%f`.","4s":"invalid argument. Must provide a 1-dimensional ndarray. Value: `%s`.","4t":"invalid argument. Vector length must match centroid dimensions. Expected: `%u``. Actual: `%u``.","4u":"invalid argument. Output argument must be a 1-dimensional ndarray. Value: `%s`.","4v":"invalid argument. Must provide a 2-dimensional ndarray. Value: `%s`.","4w":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u``. Actual: `%u`.","4x":"invalid argument. Output vector length must match the number of data points. Expected: `%u`. Actual: `%u`.","4y":"invalid option. `%s` option method must be one of the following: \"%s\". Option: `%s`.","4z":"invalid option. First `%s` parameter option must be a positive integer. Option: `%s`.","5A":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","5B":"invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.","5C":"invalid option. `%s` option must be a recognized order. Option: `%s`.","5D":"invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.","5E":"invalid argument. Linear index must not exceed array dimensions. Number of array elements: `%u`. Value: `%d`.","5F":"invalid argument. Input array cannot be broadcast to the specified shape, as the specified shape has a dimension whose size is less than the size of the corresponding dimension in the input array. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5G":"invalid argument. Input array and the specified shape are broadcast incompatible. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5H":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.","5I":"invalid argument. Index must be on the interval: [0, %f]. Value: `%f`.","5J":"invalid argument. Subscripts must not exceed array dimensions. Subscript: `%u`. Value: `%d`.","5K":"invalid argument. First argument must be a recognized data type. Value: `%s`.","5L":"invalid argument. First argument must have a recognized data type. Value: `%s`.","5M":"invalid arguments. Number of indices must match the number of dimensions. ndims: `%u`. nargs: `%u`.","5N":"invalid argument. Indices must be integer valued. Argument: `%u`. Value: `%s`.","5O":"invalid argument. Index must be an integer. Value: `%s`.","5P":"invalid argument. First argument must be a supported ndarray data type. Value: `%s`.","5Q":"invalid argument. Second argument must be an array-like object, typed-array-like, or a Buffer. Value: `%s`.","5R":"invalid argument. Second argument `get` and `set` properties must be functions. Value: `%s`.","5S":"invalid argument. Third argument must be an array-like object containing nonnegative integers. Value: `%s`.","5T":"invalid argument. Number of dimensions must not exceed %u due to stack limits. Value: `%u`.","5U":"invalid argument. Fourth argument must be an array-like object containing integers. Value: `%s`.","5V":"invalid argument. Fourth argument length must match the number of dimensions. Expected number of dimensions: `%u`. Strides length: `%u`.","5W":"invalid argument. Fourth argument must contain a single element equal to `0`. Value: `%d`.","5X":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.","5Y":"invalid argument. Sixth argument must be a supported order. Value: `%s`.","5Z":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%u`.","5a":"invalid option. `%s` option must be a recognized mode. Option: `%s`.","5b":"invalid option. `%s` option must be an array containing recognized modes. Option: `%s`.","5c":"invalid option. Each submode must be a recognized mode. Option: `%s`.","5d":"invalid argument. First argument must be either a function or an array of functions. Value: `%s`.","5e":"invalid argument. Third argument must be an array-like object or null. Value: `%s`.","5f":"invalid argument. Fourth argument must be a positive integer. Value: `%s`.","5g":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%s`.","5h":"invalid argument. Input array must be an ndarray-like object. Value: `%s`.","5i":"invalid argument. Output array must be an ndarray-like object. Value: `%s`.","5j":"invalid argument. Output argument must be either an array, typed array, or object. Value: `%s`.","5k":"invalid argument. Shape argument must be an array-like object containing nonnegative integers. Value: `%s`.","5l":"invalid argument. Linear index must be integer valued. Value: `%s`.","5m":"invalid option. `%s` option must be a supported/recognized mode. Option: `%s`.","5n":"invalid option. `%s` option must be a supported/recognized order. Option: `%s`.","5o":"invalid argument. First argument must be an array-like object containing nonnegative integers. Value: `%s`.","5p":"invalid argument. Number of provided subscripts must match the number of dimensions. ndims: `%u`. Number of subscripts: `%u`.","5q":"invalid argument. Subscripts must be integer valued. Argument: `%u`. Value: `%s`.","5r":"invalid option. `%s` option cannot be an empty array.","5s":"invalid argument. First argument must be either a nonnegative integer or an array of nonnegative integers. Value: `%s`.","5t":"invalid argument. First argument must be an ndarray-like object. Value: `%s`.","5u":"invalid option. `%s` option must either be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","5v":"invalid option. `%s` option must be either a Buffer or a string. Option: `%s`.","5w":"invalid argument. Request listener must be a function. Value: `%s`.","5x":"invalid argument. Third argument must be a positive integer. Value: `%s`.","5y":"invalid argument. Number of topics must be a positive integer. Value: `%s`.","5z":"invalid argument. First argument must be a nonnegative integer which is less than the total number of topics. Value: `%s`.","6A":"invalid assignment. `%s` must be a nonnegative integer or nonnegative integer array. Value: `%s`.","6B":"invalid assignment. `%s` must be a nonnegative integer. Value: `%s`.","6C":"invalid assignment. Unrecognized/unsupported `%s`. Must be one of the following: \"%s\". Value: `%s`.","6D":"invalid assignment. Unrecognized/unsupported `%s`. Value: `%s`.","6E":"invalid assignment. `%s` must be a nonnegative integer or null. Value: `%s`.","6F":"invalid assignment. `%s` must be a string or null. Value: `%s`.","6G":"invalid argument. Must provide a supported viewer. Value: `%s`.","6H":"invalid assignment. `%s` must be a function. Value: `%s`.","6I":"invalid assignment. `%s` must be either null or an array. Value: `%s`.","6J":"invalid assignment. `%s` must be a string, function, or null. Value: `%s`.","6K":"invalid argument. `options` argument must be an object. Value: `%s`.","6L":"invalid assignment. `%s` must be a number. Value: `%s`.","6M":"invalid assignment. `%s` must be a number on the interval `[0,1]`. Value: `%f`.","6N":"invalid assignment. `%s` must be array-like. Value: `%s`.","6O":"invalid arguments. Must provide equal length array-like objects. x length: `%u`, y length: `%u`.","6P":"invalid assignment. `%s` must be a string or a function. Value: `%s`.","6Q":"invalid assignment. `%s` must be a number or a function. Value: `%s`.","6R":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","6S":"invalid assignment. `%s` must be a nonnegative integer or a function. Value: `%s`.","6T":"invalid assignment. `%s` must be a supported symbol. Symbols: \"%s\". Value: `%s`.","6U":"invalid argument. `options` argument must be a plain object. Value: `%s`.","6V":"invalid assignment. `%s` must be either a string or a string array. Value: `%s`.","6W":"invalid assignment. `%s` must be a string or a string array. Value: `%s`.","6X":"invalid assignment. `%s` must be a string or string array. Value: `%s`.","6Y":"invalid assignment. Unrecognized/unsupported symbol. Value: `[%s]`.","6Z":"invalid assignment. `%s` must be an array. Value: `%s`.","6a":"invalid assignment. `%s` must be either a finite number, Date, or null. Value: `%s`.","6b":"invalid assignment. `%s` must be a boolean or boolean array. Value: `%s`.","6c":"invalid assignment. `%s` must be either a string or string array. Value: `%s`.","6d":"invalid assignment. Unrecognized/unsupported orientation. A `%s` value must be one of the following: \"%s\". Value: `%s`.","6e":"invalid assignment. `%s` must be either a finite number or null. Value: `%s`.","6f":"invalid state. x and y are different lengths. x length: `%u`, y length: `%u`.","6g":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[","6h":"invalid assignment. `%s` must be a positive integer or null. Value: `%s`.","6i":"invalid assignment. `%s` size is smaller than the number of data elements. Number of elements: `%u`. Value: `%u`.","6j":"invalid assignment. `%s` must be an array-like object or an ndarray. Value: `%s`.","6k":"invalid assignment. `%s` length exceeds maximum data buffer size. Buffer size: `%u`. Length: `%u`.","6l":"invalid assignment. `%s` must be a finite number or null. Value: `%s`.","6m":"invalid assignment. `%s` must be a finite number or null. Value: `%s.","6n":"invalid assignment. Must be an array or typed array. Value: `%s`.","6o":"invalid option. `%s` option must be an array or typed array. Option: `%s`.","6p":"invalid option. `%s` option must be a function. Option: `%s`.","6q":"invalid argument. Encoding argument must be a string. Value: `%s`.","6r":"invalid argument. Must provide either a string, nonnegative integer, or an options object. Value: `%s`.","6s":"invalid argument. First argument must be either a string or nonnegative integer. Value: `%s`.","6t":"invalid argument. Unable to parse mask expression. Ensure the expression is properly formatted, only uses the class letters \"u\", \"g\", \"o\", and \"a\", only uses the operators \"+\", \"-\", and \"=\", and only uses the permission symbols \"r\", \"w\", and \"x\". Value: `%s`.","6u":"invalid option. `%s` option must be a pseudorandom number generator function. Option: `%s`.","6v":"invalid argument. First argument must be a number and not NaN. Value: `%s`.","6w":"invalid argument. Second argument must be a number and not NaN. Value: `%s`.","6x":"invalid argument. Minimum support must be less than maximum support. Value: `[%f,%f]`.","6y":"invalid argument. First argument must be a probability. Value: `%s`.","6z":"invalid option. `%s` option must be a Uint32Array. Option: `%s`.","7A":"invalid argument. First argument must be a positive number and not NaN. Value: `%s`.","7B":"invalid argument. Second argument must be a positive number and not NaN. Value: `%s`.","7C":"invalid argument. Third argument must be a number and not NaN. Value: `%s`.","7D":"invalid argument. Third argument must be less than or equal to the first argument. Value: `%u`.","7E":"invalid argument. Second argument must be less than or equal to the first argument. Value: `%u`.","7F":"invalid %s. State array has insufficient length.","7G":"invalid %s. State array has an incompatible schema version. Expected: `%s`. Actual: `%s`.","7H":"invalid %s. State array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","7I":"invalid %s. State array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7J":"invalid %s. State array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7K":"invalid option. `%s` option must be an Int32Array. Option: `%s`.","7L":"invalid option. `%s` option must be a positive integer less than the maximum signed 32-bit integer. Option: `%u`.","7M":"invalid option. `%s` option must be either a positive integer less than the maximum signed 32-bit integer or an array-like object containing integer values less than the maximum signed 32-bit integer. Option: `%s`.","7N":"invalid argument. Must provide an Int32Array. Value: `%s`.","7O":"invalid %s. State array has an incompatible table length. Expected: `%s`. Actual: `%s`.","7P":"invalid %s. `state` array has insufficient length.","7Q":"invalid %s. `state` array has an incompatible schema version. Expected: %s. Actual: %s.","7R":"invalid %s. `state` array has an incompatible number of sections. Expected: %s. Actual: %s.","7S":"invalid %s. `state` array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7T":"invalid %s. `state` array has an incompatible section length. Expected: `%u`. Actual: `%u`.","7U":"invalid %s. `state` array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7V":"invalid option. `%s` option must be a positive integer less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7W":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7X":"invalid argument. Second argument must be on the interval: (0, 1). Value: `%f`.","7Y":"invalid option. `%s` option cannot be undefined. Option: `%s`.","7Z":"invalid option. Unrecognized/unsupported PRNG. Option: `%s`.","7a":"invalid argument. First argument must be a positive number or an options object. Value: `%s`.","7b":"invalid arguments. Parameters must satisfy the following condition: %s. Value: `[%f, %f, %f]`.","7c":"invalid argument. Scale parameter must be a positive number. Value: `%s`.","7d":"invalid argument. Shape parameter must be a positive number. Value: `%s`.","7e":"invalid argument. First argument must be an integer. Value: `%s`.","7f":"invalid argument. Second argument must be an integer. Value: `%s`.","7g":"invalid argument. `n` must be less than or equal to `N`. Value: `%u`.","7h":"invalid argument. `K` must be less than or equal to `N`. Value: `%u`.","7i":"invalid argument. `%s` argument must be array-like. Value: `%s`.","7j":"invalid input option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","7k":"invalid input option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","7l":"invalid option. `%s` option must be an array of probabilities that sum to one. Option: `%s`.","7m":"invalid argument. Minimum support must be less than maximum support. Value: `[%s,%s]`.","7n":"invalid option. `%s` option must be a string or null. Option: `%s`.","7o":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%s,%s]`.","7p":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7q":"invalid argument. Mode must be one of the following: \"%s\". Value: `%s`.","7r":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7s":"invalid operation. Alias already exists in the provided context. Alias: `%s`. Value: `%s`.","7t":"invalid argument. Unrecognized workspace name. Value: `%s`.","7u":"invalid operation. Cannot read from write-only variable `%s`.","7v":"Cannot assign to read only property %s of object #","7w":"invalid option. `%s` option must be a regular expression or an array-like object. Option: `%s`.","7x":"invalid option. `%s` option must be one of `%s`. Option: `%s`.","7y":"invalid argument. Must provide either an options object or a workspace name. Value: `%s`.","7z":"invalid argument. Must provide either a string or regular expression. Value: `%s`.","8A":"invalid argument. Must provide an integer. Value: `%s`.","8B":"invalid argument. Must provide a positive integer. Value: `%s`.","8C":"invalid argument. Presentation text must be a string. Value: `%s`.","8D":"invalid argument. REPL argument must be a REPL instance. Value: `%s`.","8E":"unexpected error. Unable to reload presentation. Error: %s","8F":"unexpected error. Unable to watch presentation source file. Error: %s","8G":"invalid option. `%s` option must be either a recognized string or boolean. Option: `%s`.","8H":"invalid option. `%s` option must be either a positive integer or null. Option: `%s`.","8I":"invalid operation. Alias already exists in REPL context. Alias: `%s`. Value: `%s`.","8J":"invalid argument. Third argument must be an object. Value: `%s`.","8K":"invalid option. `%s` option must be less than or equal to the period. Option: `%u`.","8L":"invalid option. `%s` option must be greater than 2. Option: `%s`.","8M":"invalid option. `%s` option must be an integer. Option: `%s`.","8N":"invalid option. `%s` option must be an positive integer. Option: `%s`.","8O":"invalid option. `%s` option must be less than the period. Option: `%s`.","8P":"invalid option. `%s` option must be a number. Option: `%s`.","8Q":"invalid option. `%s` option must be an positive even integer. Option: `%s`.","8R":"invalid argument. First argument must be a numeric array. Value: `%s`.","8S":"invalid argument. First argument must contain at least two elements. Value: `%s`.","8T":"invalid argument. Second argument must be an array. Value: `%s`.","8U":"invalid argument. Second argument must contain at least two unique elements. Value: `%s`.","8V":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%f`.","8W":"invalid option. `%s` option must be an array containing at least two unique elements. Option: `%s`.","8X":"invalid argument. Must provide array-like arguments. Value: `%s`.","8Y":"invalid argument. Supplied arrays cannot be empty. Value: `%s`.","8Z":"invalid option. `%s` option must be an array. Option: `%s`.","8a":"invalid argument. Minimum support must be a number. Value: `%s`.","8b":"invalid argument. Maximum support must be a number. Value: `%s`.","8c":"invalid arguments. Minimum support must be less than maximum support. Value: `%f, %f`.","8d":"invalid assignment. Must be a number. Value: `%s`.","8e":"invalid assignment. Must be less than %f. Value: `%f`.","8f":"invalid assignment. Must be greater than %f. Value: `%f`.","8g":"invalid argument. Mean parameter `p` must be a probability. Value: `%s`.","8h":"invalid assignment. Must be a probability. Value: `%s`.","8i":"invalid argument. First shape parameter must be a positive number. Value: `%s`.","8j":"invalid argument. Second shape parameter must be a positive number. Value: `%s`.","8k":"invalid assignment. Must be a positive number. Value: `%s`.","8l":"invalid argument. Number of trials must be a positive integer. Value: `%s`.","8m":"invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.","8n":"invalid assignment. Must be a positive integer. Value: `%s`.","8o":"invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.","8p":"invalid argument. Location parameter must be a number. Value: `%s`.","8q":"invalid argument. Rate parameter must be a positive number. Value: `%s`.","8r":"invalid argument. Mean parameter `%s` must be a number. Value: `%s`.","8s":"invalid argument. Minimum support must be an integer. Value: `%s`.","8t":"invalid argument. Maximum support must be an integer. Value: `%s`.","8u":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `%d, %d`.","8v":"invalid assignment. Must be an integer. Value: `%s`.","8w":"invalid assignment. Must be less than or equal to %u. Value: `%d`.","8x":"invalid assignment. Must be greater than or equal to %u. Value: `%s`.","8y":"invalid argument. Shape parameter must be a positive integer. Value: `%s`.","8z":"invalid argument. Numerator degrees of freedom must be a positive number. Value: `%s`.","9A":"invalid argument. Mean parameter `lambda` must be a positive number. Value: `%s`.","9B":"invalid argument. Mode must be a number. Value: `%s`.","9C":"invalid arguments. Parameters must satisfy the following condition: %s. a: `%f`. b: `%f`. c: `%f`.","9D":"invalid assignment. Must be less than or equal to both the maximum support and the mode. Value: `%f`.","9E":"invalid assignment. Must be greater than or equal to both the minimum support and the mode. Value: `%f`.","9F":"invalid assignment. Must be greater than or equal to the minimum support and less than or equal to the maximum support. Value: `%f`.","9G":"invalid argument. An array argument must contain two elements. Value: `%s`.","9H":"invalid argument. Must provide a nonnegative integer or a two-element array. Value: `%s`.","9I":"invalid arguments. Number of successes cannot be larger than the total number of observations. x: `%u`. n: `%u`.","9J":"invalid option. `%s` option must be a probability. Option: `%f`.","9K":"invalid argument. Unsupported/unrecognized distribution name. Value: `%s`.","9L":"invalid argument. First argument must contain nonnegative integers. Index: `%u`. Value: `%s`.","9M":"invalid argument. Probability mass function (PMF) arguments must be numbers. Argument: `%u`. Value: `%s`.","9N":"invalid argument. Second argument must be either an array-like object (or one-dimensional ndarray) of probabilities summing to one, an array-like object (or one-dimensional ndarray) of expected frequencies, or a discrete probability distribution name. Value: `%s`.","9O":"invalid argument. Second argument must only contain numbers. Index: `%u`. Value: `%s`.","9P":"invalid argument. Second argument must only contain nonnegative numbers. Index: `%u`. Value: `%d`.","9Q":"invalid option. `%s` option must be a number on the interval: [0, 1]. Value: `%s`.","9R":"invalid argument. First argument must be an array of arrays or ndarray-like object with dimension two. Value: `%s`.","9S":"invalid argument. First argument must contain nonnegative integers. Value: `%s`.","9T":"invalid argument. First argument must either specify the order of the covariance matrix or be a square 2-dimensional ndarray for storing the covariance matrix. Value: `%s`.","9U":"invalid argument. Second argument must be a 1-dimensional ndarray. Value: `%s`.","9V":"invalid argument. The number of elements (means) in the second argument must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9W":"invalid argument. Vector length must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9X":"invalid argument. Must provide a number. Value: `%s`.","9Y":"invalid argument. Must provide a nonnegative number. Value: `%s`.","9Z":"invalid argument. Must provide a nonnegative number on the interval [0,1]. Value: `%f`.","9a":"invalid argument. Output argument must be an array-like object. Value: `%s`.","9b":"invalid argument. Window size must be a positive integer. Value: `%s`.","9c":"invalid argument. Window size must be greater than or equal to 3. Value: `%s`.","9d":"invalid option. `%s` option must be on the interval [0,1]. Option: `%f`.","9e":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square 2-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","9f":"invalid argument. The number of elements (means) in the second argument must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9g":"invalid argument. Vector length must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","9h":"invalid argument. Vector length must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9i":"invalid argument. First argument must either specify the order of the correlation matrix or be a square 2-dimensional ndarray for storing the correlation matrix. Value: `%s`.","9j":"invalid argument. Unsupported/unrecognized kernel. Value: `%s`.","9k":"invalid argument. Second argument must be a numeric array. Value: `%s`.","9l":"invalid option. Lower bound `%s` must be strictly less than the upper bound `%s`.","9m":"invalid option. `%s` option must be an array of positive numbers. Option: `%s`.","9n":"invalid option. `%s` option must be an array of length two. Option: `%s`.","9o":"invalid option. `%s` option must be a string denoting a known kernel function or a custom function. Option: `%s`.","9p":"invalid arguments. First argument and `%s` must be arrays having the same length.","9q":"invalid invocation. Incorrect number of arguments. Must provide at least two array-like arguments. Value: `%s`.","9r":"invalid option. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","9s":"invalid argument. First argument must be a typed array or number array. Value: `%s`.","9t":"invalid argument. Second argument must be either a CDF function or a string. Value: `%s`.","9u":"invalid argument. Distribution parameter must be a number. Value: `%s`.","9v":"invalid option. `%s` option must contain at least two unique elements. Value: `%s`.","9w":"invalid argument. Provided arrays cannot be empty. Value: `%s`.","9x":"invalid argument. First argument must be an array of probabilities. Value: `%s`.","9y":"invalid argument. When specified, `%s` arguments must contain at least a length of %u. Value: `%u`.","9z":"invalid argument. Second argument must be one of the following: %s. Value: `%s`.","A0":"invalid option. `%s` option must be a number in `[0,1]`. Option: `%s`.","A1":"invalid option. `%s` option must be a number on the interval: [-1, 1]. Option: `%s`.","A2":"invalid argument. First argument must contain at least two elements. Value: `%s`.","A3":"invalid argument. Second argument must be either a numeric array or an options object. Value: `%s`.","A4":"invalid option. `%s` option must be either `equal` or `unequal`. Option: `%s`.","A5":"invalid argument. `%s` argument must be a numeric array. Value: `%s`.","A6":"invalid option. `%s` option must be one of the following: %s. Option: `%s`.","A7":"invalid argument. Third argument must be a positive number. Value: `%s`.","A8":"invalid argument. Fourth argument must be a positive number. Value: `%s`.","A9":"invalid operation. Serialization function must return a string or Buffer. Value: `%s`.","AA":"invalid argument. In binary mode, a provided value must be a string, Buffer, or Uint8Array. Value: `%s`.","AB":"invalid option. `%s` option must be either a string or a regular expression. Option: `%s`.","AC":"invalid argument. First input array offset must be a nonnegative integer. Value: `%s`.","AD":"invalid argument. Second input array offset must be a nonnegative integer. Value: `%s`.","AE":"invalid argument. Output array offset must be a nonnegative integer. Value: `%s`.","AF":"invalid argument. Must provided recognized data types. Unable to resolve a data type string. Value: `%s`.","AG":"invalid argument. Input array offset must be a nonnegative integer. Value: `%s`.","AH":"invalid argument. Input array stride must be an integer. Value: `%s`.","AI":"invalid argument. Output array stride must be an integer. Value: `%s`.","AJ":"invalid option. `%s` option must be an array of strings. Option: `%s`.","AK":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%s`.","AL":"invalid argument. Third argument must be a boolean. Value: `%s`.","AM":"invalid argument. Must provide valid code points (i.e., nonnegative integers). Value: `%s`.","AN":"invalid argument. Must provide a valid code point (cannot exceed max). Value: `%s`.","AO":"invalid argument. Third argument must be a string. Value: `%s`.","AP":"invalid argument. Output string length exceeds maximum allowed string length. Value: `%u`.","AQ":"invalid argument. Third argument must be a string or an array of strings. Value: `%s`.","AR":"invalid argument. At least one padding option must have a length greater than 0. Left padding: `%s`. Right padding: `%s`.","AS":"invalid argument. Second argument must be an array of strings. Value: `%s`.","AT":"invalid argument. Second argument must be a string or regular expression. Value: `%s`.","AU":"invalid argument. Third argument must be a string or replacement function. Value: `%s`.","AV":"invalid argument. Must provide a string or an array of strings. Value: `%s`.","AW":"invalid argument. If only providing a single argument, must provide a Date object. Value: `%s`.","AX":"invalid argument. First argument must be either a string or integer. Value: `%s`.","AY":"invalid argument. Day number must be on the interval: `[1, %u]`. Value: `%d`.","AZ":"invalid argument. First argument must be either a string, integer, or Date object. Value: `%s`.","Aa":"invalid argument. An integer month value must be on the interval: [1, 12]. Value: `%s`.","Ab":"invalid argument. Must provide a recognized month. Value: `%s`.","Ac":"invalid argument. Must provide either an integer or a `Date` object. Value: `%s`.","Ad":"invalid argument. Must provide either a string, integer, or Date object. Value: `%s`.","Ae":"invalid argument. Must provide an array of nonnegative integers. Value: `%s`.","Af":"invalid argument. Input array must contain two elements. Value: `%s`.","Ag":"invalid argument. Must provide a collection. Value: `%s`.","Ah":"invalid argument. First argument must be a collection. Value: `%s`.","Ai":"invalid argument. First argument must be either an array, typed array, or an array-like object. Value: `%s`.","Aj":"invalid argument. All arguments must be functions. Value: `%s`.","Ak":"invalid argument. Number of function invocations must be a nonnegative integer. Value: `%s`.","Al":"invalid argument. First argument must be an array of functions. Value: `%s`.","Am":"invalid argument. Last argument must be a collection. Value: `%s`.","An":"invalid argument. Must provide either a valid buffer size (i.e., a positive integer) or an array-like object which can serve as the underlying buffer. Value: `%s`.","Ao":"invalid argument. An iterator must return an array-like object containing vertices. Value: `%s`.","Ap":"invalid argument. Callback must return an array-like object containing vertices. Value: `%s`.","Aq":"invalid argument. Callback must return an array-like object. Value: `%s`.","Ar":"invalid argument. Each element of the adjacency list must be an array-like object. Value: `%s`.","As":"invalid argument. Each element of the edge list must be an array-like object. Value: `%s`.","At":"invalid argument. Second argument must be an array-like object or an iterable. Value: `%s`.","Au":"invalid argument. First argument exceeds matrix dimensions. Value: `%u`.","Av":"invalid argument. Second argument exceeds matrix dimensions. Value: `%u`.","Aw":"invalid argument. Vertex cannot exceed matrix dimensions. Value: `%u`.","Ax":"invalid argument. Second argument must be a recognized output path convention. Value: `%s`.","Ay":"invalid argument. Cannot convert Windows extended-length paths to POSIX paths. Value: `%s`.","Az":"invalid argument. Arity argument must be a positive integer. Value: `%s`.","B0":"invalid argument. Property descriptor must be an object. Value: `%s`.","B1":"invalid argument. The `value` property of the property descriptor must be a function. Value: `%s`.","B2":"invalid argument. Second argument must be an object of property descriptors. Value: `%s`.","B3":"invalid argument. Path must be a string. Value: `%s`.","B4":"invalid argument. Third argument must be a recognized location. Value: `%s`.","B5":"invalid argument. Must provide a recognized iteration direction. Value: `%s`.","B6":"invalid argument. Must provide an object-like value. Value: `%s`.","B7":"invalid argument. Must provide a regular expression string. Value: `%s`.","B8":"invalid argument. Filename must be a string. Value: `%s`.","B9":"invalid argument. First argument must be an array of positive integers. Value: `%s`.","BA":"invalid argument. First argument must be object-like. Value: `%s`.","BB":"invalid argument. Must provide an array of arrays. Value: `%s`.","BC":"invalid argument. Must provide a boolean. Value: `%s`.","BD":"invalid argument. Second argument must have a prototype from which another object can inherit. Value: `%s`.","BE":"invalid argument. A provided constructor must be either an object (except null) or a function. Value: `%s`.","BF":"invalid argument. If the input array is an ndarray, the output array must also be an ndarray. Value: `%s`.","BG":"invalid argument. If the input array is an array-like object, the output array must also be an array-like object. Value: `%s`.","BH":"invalid argument. First argument must be an array-like object or an ndarray. Value: `%s`.","BI":"invalid argument. If the first input array is an ndarray, the second input array must also be an ndarray. Value: `%s`.","BJ":"invalid argument. If the input arrays are ndarrays, the output array must also be an ndarray. Value: `%s`.","BK":"invalid argument. If the first input array is an array-like object, the second input array must also be an array-like object. Value: `%s`.","BL":"invalid argument. If the input arrays are array-like objects, the output array must also be an array-like object. Value: `%s`.","BM":"invalid argument. First argument must be an array-like object containing array-like objects. Index: `%u`. Value: `%s`.","BN":"invalid argument. First argument must be a three-dimensional nested array. Index: `%u`. Value: `%s`.","BO":"invalid argument. First argument must be a four-dimensional nested array. Index: `%u`. Value: `%s`.","BP":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BQ":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BR":"invalid argument. First argument must be a five-dimensional nested array. Index: `%u`. Value: `%s`.","BS":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BT":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BU":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u, %u). Value: `%s`.","BV":"invalid argument. A merge source must be an object. Value: `%s`.","BW":"invalid option. `%s` option must be either a boolean or a function. Option: `%s`.","BX":"invalid argument. Source argument must be an object. Value: `%s`.","BY":"invalid argument. Target argument must be an object. Value: `%s`.","BZ":"invalid argument. Must provide an array of strings. Value: `%s`.","Ba":"invalid argument. Field names must be distinct. Value: `%s`.","Bb":"invalid argument. Provided field name is reserved. Name: `%s`.","Bc":"invalid arguments. Arguments are incompatible with the number of tuple fields. Number of fields: `%u`. Number of data elements: `%u`.","Bd":"invalid argument. Source is incompatible with the number of tuple fields. Number of fields: `%u`. Source length: `%u`.","Be":"invalid invocation. Number of arguments is incompatible with the number of tuple fields. Number of fields: `%u`. Number of arguments: `%u`.","Bf":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","Bg":"invalid argument. Second argument must be either a string or an array of strings. Value: `%s`.","Bh":"invalid argument. Must provide a valid URI. Value: `%s`.","Bi":"unexpected error. Child process failed with exit code: `%u`.","Bj":"unexpected error. Child process failed due to termination signal: `%s`.","Bk":"invalid argument. Reviver argument must be a function. Value: `%s`.","Bl":"invalid argument. Second argument must be an array-like object containing nonnegative integers. Value: `%s`.","Bm":"invalid argument. Must provide either an array, typed array, or an array-like object. Value: `%s`.","Bn":"invalid argument. Must provide a recognized type. Value: `%s`.","Bo":"invalid argument. Second argument must be an array containing only nonnegative integers. Value: `%s`.","Bp":"invalid invocation. Unexpected number of input arguments. Expected: `%u`. Actual: `%u`.","Bq":"evaluation error. Encountered an error when evaluating snippet. %s","Br":"invalid option. `%s` option must be a positive integer or null. Option: `%s`.","Bs":"insufficient arguments. Expected %u argument(s) and only received %u argument(s).","Bt":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: %u. Actual: %u.","Bu":"invalid invocation. Number of arguments exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bv":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bw":"invalid argument. Must provide array arguments. Value: `%s`.","Bx":"invalid argument. Last argument must be either an array or an options object. Value: `%s`.","By":"invalid argument. Repository slug must be a string. Value: `%s`.","Bz":"invalid argument. Issue title must be a string. Value: `%s`.","C0":"invalid option. `%s` must be one of the following: \"%s\". Option: `%s`.","C1":"invalid argument. Repository name must be a string. Value: `%s`.","C2":"invalid option. `%s` option must be a valid URI. Option: `%s`.","C3":"invalid option. `%s` option must be a 20-character string. Option: `%s`.","C4":"invalid option. `%s` option must be a 40-character string. Option: `%s`.","C5":"invalid argument. Token id must be a nonnegative integer. Value: `%s`.","C6":"invalid argument. Workflow identifier must be a string. Value: `%s`.","C7":"invalid option. `%s` option must be an object of input key-value pairs. Option: `%s`.","C8":"invalid option. `%s` option must be a positive integer or \"last\". Option: `%s`.","C9":"invalid option. `%s` organization name option must be a string. Option: `%s`.","CA":"invalid option. Unknown method. Option: `%s`.","CB":"invalid option. Unrecognized `%s` option. Must be one of the following: \"%s\". Option: `%s`.","CC":"invalid argument. Repository slug must consist of an owner and a repository (e.g., \"stdlib-js/utils\"). Value: `%s`.","CD":"invalid argument. Topics argument must be an array of strings. Value: `%s`.","CE":"invalid option. `%s` option must be one of the following: \"%s\" or \"%s\". Option: `%s`.","CF":"invalid argument. Must provide a supported license SPDX identifier. Value: `%s`.","CG":"invalid argument. Must provide a supported file type. Value: `%s`.","CH":"invalid argument. First argument must be either a string or Buffer. Value: `%s`.","CI":"invalid argument. Second argument must be either a string or Buffer. Value: `%s`.","CJ":"invalid argument. A header object must map each filename extension to a license header string. `%s: %s`. Value: `%s`.","CK":"invalid argument. Second argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CL":"invalid argument. Second argument must be either a string, Buffer, or regular expression. Value: `%s`.","CM":"invalid argument. A header object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CN":"invalid argument. Second argument must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Value: `%s`.","CO":"invalid argument. Third argument must be either a string or Buffer. Value: `%s`.","CP":"invalid argument. Third argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CQ":"invalid argument. Database already contains an entry for the provided URI: `%s`.","CR":"invalid argument. Database already contains an entry for the provided id: `%s`.","CS":"invalid argument. First argument must be a URI. Value: `%s`.","CT":"invalid argument. Second argument must be either a string or regular expression. Value: `%s`.","CU":"invalid option. A `%s` option object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CV":"invalid option. `%s` option must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Option: `%s`.","CW":"invalid option. `%s` option must end with \"package.json\". Option: `%s`.","CX":"invalid argument. Last argument must be a callback function. Value: `%s`.","CY":"invalid option. `%s` option must be an array of package names. Option: `%s`.","CZ":"invalid argument. Version argument must be a string. Value: `%s`.","Ca":"invalid argument. Must provide either a string or a Buffer. Value: `%s`.","Cb":"invalid argument. Must provide either a string or Buffer. Value: `%s`.","Cc":"invalid argument. First argument must be either a string or array of strings. Value: `%s`.","Cd":"invalid option. `%s` option must be an object. Option: `%s`.","Ce":"unexpected error. File does not exist. Unable to resolve file: %s.","Cf":"invalid argument. Must provide either a string or an array of strings. Value: `%s`.","Cg":"invalid argument. Must provide either a string or an array of strings. Value: `%s`. Index: `%u`.","Ch":"unexpected error. Failed to sort packages. Detected the following dependency chain containing a cycle: `%s`.","Ci":"invalid node. Equation comments must have a valid label. Node: `%s`.","Cj":"invalid node. Equation comments must have valid alternate text. Node: `%s`.","Ck":"invalid node. Equation comments must have valid raw equation text. Node: `%s`.","Cl":"invalid node. Invalid equation comment. Ensure that the Markdown file includes both starting and ending equation comments. Node: `%s`.","Cm":"invalid node. Equation element must have a valid label. Node: `%s`.","Cn":"unexpected error. Code block configuration settings should be provided as comma-separated `key:value` pairs (e.g., `foo:true, bar:\"string\", baz:[\"error\",2]`). Value: `%s`.","Co":"unexpected error. Code block configuration values should be parseable as JSON. Value: `%s`.","Cp":"unexpected error. Encountered an error when executing code block. File: `%s`. Message: `%s`.","Cq":"unexpected error. Expected code block to throw an exception. File: `%s`.","Cr":"invalid node. Ensure that the Markdown file includes both a starting `
` and closing `
\\n\\n`. Node: `%s`.","Cs":"invalid node. Equation comments must have valid equation text. Node: `%s`.","Ct":"invalid node. Equation comments must have valid labels. Node: `%s`.","Cu":"invalid option. `%s` option must begin with \"@stdlib/\". Option: `%s`.","Cv":"invalid argument. First argument must be a list of file paths. Value: `%s`.","Cw":"invalid arguments. Subpopulation size must be less than or equal to the population size.","Cx":"invalid arguments. Number of draws must be less than or equal to the population size.","Cy":"invalid arguments. Fourth argument is not compatible with the number of input and output ndarrays.","Cz":"invalid arguments. Input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","D0":"invalid arguments. Length of the first argument is incompatible with the second and third arguments.","D1":"invalid argument. Provided collections must have the same length.","D2":"invalid argument. First argument must be an array-like object containing nonnegative integers.","D3":"invalid arguments. Input arrays must have the same length.","D4":"invalid argument. Must provide valid indices (i.e., must be a nonnegative integer less than or equal to the tuple length).","D5":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented. https://github.com/stdlib-js/stdlib/issues/new/choose","D6":"invalid operation. Parser is unable to parse new chunks, as the parser has been closed. To parse new chunks, create a new parser instance.","D7":"invalid operation. Parser is in an unrecoverable error state. To parse new chunks, create a new parser instance.","D8":"invalid argument. First argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","D9":"invalid argument. Second argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","DA":"invalid argument. First argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DB":"invalid argument. Second argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DC":"invalid assignment. `%s` size is less than the number of data elements. Number of elements: `%u`. Value: `%u`.","DD":"invalid assignment. `%s` must be a string or an array of strings. Value: `%s`.","DE":"invalid assignment. `%s` must be a number or an array of numbers. Value: `%s`.","DF":"invalid assignment. `%s` must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","DG":"invalid assignment. `%s` must be a finite number, Date, or null. Value: `%s`.","DH":"invalid assignment. `%s` must be a boolean or an array of booleans. Value: `%s`.","DI":"invalid assignment. `%s` must be a number or null. Value: `%s`.","DJ":"invalid assignment. `%s` must be an array of strings or an empty array. Value: `%s`.","DK":"invalid state. x and y are different lengths. x length: `%u`. y length: `%u`.","DL":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[%u].length: `%u`.","DM":"invalid assignment. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","DN":"invalid assignment. `%s` must be null or an array. Value: `%s`.","DO":"invalid arguments. Must provide equal length array-like objects. x length: `%u`. y length: `%u`.","DP":"invalid argument. The number of comparisons must be greater or equal to the number of p-values to be adjusted. Value: `%u`.","DQ":"invalid argument. Second argument must be one of the following: \"%s\". Value: `%s`.","DR":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%s`.","DS":"invalid argument. First argument must contain nonnegative integers. Indices: (%s). Value: `%s`.","DT":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Number of input array dimensions: %u.","DU":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Value: `%s`.","DV":"invalid arguments. Minimum support must be less than maximum support. Value: `(%f, %f)`.","DW":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `(%d, %d)`.","DX":"invalid argument. Mean parameter must be a positive number. Value: `%s`.","DY":"invalid argument. Mean parameter must be a probability. Value: `%s`.","DZ":"invalid option. `%s` option must be on the interval: [0, 1]. Option: `%f`.","Da":"invalid argument. Must provide a nonnegative number on the interval: [0, 1]. Value: `%f`.","Db":"invalid argument. First argument must either specify the order of the covariance matrix or be a square two-dimensional ndarray for storing the covariance matrix. Value: `%s`.","Dc":"invalid argument. Second argument must be a one-dimensional ndarray. Value: `%s`.","Dd":"invalid argument. Must provide a one-dimensional ndarray. Value: `%s`.","De":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square two-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","Df":"invalid argument. First argument must either specify the order of the correlation matrix or be a square two-dimensional ndarray for storing the correlation matrix. Value: `%s`.","Dg":"invalid argument. Input array must be an array-like object. Value: `%s`.","Dh":"invalid argument. Output array must be an array-like object. Value: `%s`.","Di":"invalid argument. Mask array offset must be a nonnegative integer. Value: `%s`.","Dj":"invalid argument. Must provide recognized data types. Unable to resolve a data type string. Value: `%s`.","Dk":"invalid option. `%s` option must be one of the following: ['%s']. Option: `%s`.","Dl":"invalid argument. Database already contains an entry for the provided URI. Value: `%s`.","Dm":"invalid argument. Database already contains an entry for the provided id. Value: `%s`.","Dn":"invalid argument. First argument must be an array of objects. Value: `%s`.","Do":"unexpected error. File does not exist. Unable to resolve file: `%s`.","Dp":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`.","Dq":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`. Index: `%u`.","Dr":"invalid argument. Must provide either an options object or a function. Value: `%s`.","Ds":"invalid option. `%s` option must be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","Dt":"invalid argument. Fourth argument must contain a single element equal to 0. Value: `%d`.","Du":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%s`.","Dv":"invalid argument. Must provide an ndarray. Value: `%s`.","Dw":"invalid argument. Second argument must be a supported data type policy. Value: `%s`.","Dx":"invalid argument. Must provide either an integer or a Date object. Value: `%s`.","Dy":"invalid argument. Must provide a valid duration string. Value: `%s`.","Dz":"invalid argument. Day number must be on the interval: [1, %u]. Value: `%d`.","E0":"invalid argument. First argument must be a string or integer. Value: `%s`.","E1":"invalid option. `%s` option must be one of the following: \"%s\". Value: `%s`.","E2":"invalid argument. Third argument must be either an integer (starting index) or a function. Value: `%s`.","E3":"invalid argument. Fourth argument must be either an integer (ending index) or a function. Value: `%s`.","E4":"invalid argument. Second argument must be a valid position (i.e., be within string bounds). Value: `%d`.","E5":"invalid argument. Must provide a valid code point (i.e., cannot exceed %u). Value: `%s`.","E6":"invalid argument. First argument must be astring. Value: `%s`.","E7":"invalid argument. Second argument must be either an integer (starting index) or a function. Value: `%s`.","E8":"invalid argument. Third argument must be either an integer (ending index) or a function. Value: `%s`.","E9":"invalid argument. ArrayBuffer byte length must be a multiple of %u. Byte length: `%u`.","EA":"invalid argument. Byte offset must be a multiple of %u. Value: `%u`.","EB":"invalid argument. First argument must have a length which is a multiple of %u. Length: `%u`.","EC":"invalid argument. Second argument must be a supported data type. Value: `%s`.","ED":"invalid argument. First argument must be one of the following data types: \"%s\". Value: `%s`.","EE":"invalid argument. Second argument must be either an integer (starting view index) or a function. Value: `%s`.","EF":"invalid argument. Third argument must be either an integer (ending view index) or a function. Value: `%s`.","EG":"invalid option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","EH":"invalid option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","EI":"invalid argument. Second argument must be either a scalar or an ndarray-like object. Value: `%s`.","EJ":"invalid argument. Minimum support must be less than maximum support. Value: `[%f, %f]`.","EK":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d, %d]`.","EL":"invalid %s. `state` array has an incompatible schema version. Expected: `%s`. Actual: `%s.`","EM":"invalid %s. `state` array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","EN":"invalid argument. Number of draws must be less than or equal to the population size. Value: `%u`.","EO":"invalid argument. Subpopulation size must be less than or equal to the population size. Value: `%u`.","EP":"invalid argument. Must provide a regular expression. Value: `%s`.","EQ":"invalid argument. Second argument must be an object containing property descriptors. Value: `%s`.","ER":"invalid argument. Must provide an object (except null). Value: `%s`.","ES":"invalid argument. First argument must be an object (except null). Value: `%s`.","ET":"unexpected error. Encountered an invalid record. Field %d on line %d contains a closing quote which is not immediately followed by a delimiter or newline.","EU":"unexpected error. Encountered an invalid record. Field %d on line %d contains an opening quote which does not immediately follow a delimiter or newline.","EV":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence which is not immediately followed by a special character sequence.","EW":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence within a quoted field which is not immediately followed by a quote sequence.","EX":"invalid argument. First argument must be a function having at least one parameter. Value: `%s`.","EY":"invalid argument. All arguments must be objects. Index: `%u`. Value: `%s`.","EZ":"invalid argument. First argument must be a non-null object. Value: `%s`.","Ea":"invalid argument. First argument must be an ndarray whose last dimension is of size %u. Actual size: `%u`.","Eb":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of eta * lambda. Value: `%f`.","Ec":"invalid argument. Output argument must be a one-dimensional ndarray. Value: `%s`.","Ed":"invalid argument. Must provide a two-dimensional ndarray. Value: `%s`.","Ee":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u`. Actual: `%u`.","Ef":"invalid argument. First argument must be an integer, null, or undefined. Value: `%s`.","Eg":"invalid argument. Second argument must be an integer, null, or undefined. Value: `%s`.","Eh":"invalid argument. Third argument must be an integer, null, or undefined. Value: `%s`.","Ei":"invalid argument. Third argument cannot be zero. Value: `%s`.","Ej":"invalid argument. First argument must be a valid subsequence string. Value: `%s`.","Ek":"invalid argument. A subsequence string must have a non-zero increment. Value: `%s`.","El":"invalid argument. The subsequence string resolves to a slice which exceeds index bounds. Value: `%s`.","Em":"invalid argument. Provided arguments must be either a Slice, integer, null, or undefined. Argument: `%d`. Value: `%s`.","En":"invalid operation. Unsupported slice operation. Value: `%s`.","Eo":"invalid operation. Number of array dimensions does not match the number of slice dimensions. Array shape: (%s). Slice dimensions: %u.","Ep":"invalid operation. Slice exceeds array bounds. Array shape: (%s).","Eq":"invalid operation. A subsequence increment must be a non-zero integer. Value: `%s`.","Er":"invalid operation. A subsequence may only include a single ellipsis. Value: `%s`.","Es":"invalid argument. Cannot write to a read-only array.","Et":"invalid argument. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Eu":"invalid argument. Slice arguments must be either a Slice, integer, null, or undefined. Value: `%s`.","Ev":"invalid operation. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Ew":"invalid operation. Assigned value cannot be safely cast to the target array data type. Data types: [%s, %s].","Ex":"invalid operation. Unsupported target array data type. Data type: `%s`.","Ey":"invalid argument. Index must be on the interval: [0, %d]. Value: `%d`.","Ez":"invalid argument. Slice exceeds array bounds. Array shape: (%s).","F0":"invalid argument. Input array values cannot be safely cast to the output array data type. Data types: [%s, %s].","F1":"invalid argument. Second argument must be an ndarray. Value: `%s`.","F2":"invalid argument. First argument must be an ndarray having at least two dimensions.","F3":"invalid argument. Second argument must be an array of nonnegative integers. Value: `%s`.","F4":"invalid option. Cannot write to read-only array.","F5":"invalid argument. First argument must be an array of nonnegative integers. Value: `%s`.","F6":"invalid argument. Must provide an ndarray having a supported data type. Value: `%s`.","F7":"invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.","F8":"invalid argument. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","F9":"invalid argument. Third argument must be either a Slice, integer, null, or undefined. Value: `%s`.","FA":"invalid argument. First argument must be an ndarray having at least three dimensions.","FB":"invalid argument. Index must resolve to a value on the interval: [0, %d]. Value: `%d`.","FC":"invalid argument. First argument must be a recognized index mode. Value: `%s`.","FD":"invalid argument. Third argument exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","FE":"invalid argument. Number of indices does not match the number of array dimensions. Array shape: (%s). Number of indices: %u.","FF":"invalid argument. Each index argument must be either an integer, null, or undefined. Value: `%s`.","FG":"invalid argument. First argument must be a complex number. Value: `%s`.","FH":"invalid arguments. Input arrays must be broadcast compatible.","FI":"invalid argument. The first and second arguments must have the same length.","FJ":"invalid argument. First argument must be either an ndarray or an array of ndarrays. Value: `%s`.","FK":"invalid argument. An ndarray argument must be an ndarray. Value: `%s`.","FL":"invalid argument. Second argument must be a valid property name. Value: `%s`.","FM":"invalid argument. First argument must have a `%s` method.","FN":"invalid argument. Second argument must an array of strings. Value: `%s`.","FO":"invalid argument. Third argument must be a supported data type. Value: `%s`.","FP":"invalid argument. Index argument is out-of-bounds. Value: `%s`.","FQ":"invalid argument. Second argument must be a complex number. Value: `%s`.","FR":"invalid argument. Index arguments must be integers. Value: `%s`.","FS":"invalid argument. Slice exceeds array bounds. Array length: %d.","FT":"invalid argument. Input array and the output array slice are broadcast incompatible. Array length: %u. Desired length: %u.","FU":"invalid operation. Slice exceeds array bounds.","FV":"invalid argument. First argument must be a valid index array.","FW":"invalid operation. This array index instance has already been freed and can no longer be used.","FX":"invalid argument. First argument must be a complex-valued floating-point array. Value: `%s`.","FY":"invalid operation. Index exceeds array bounds.","FZ":"invalid operation. Unrecognized array index type. Value: `%s`.","Fa":"invalid operation. Unable to resolve array index. Value: `%s`.","Fb":"invalid option. `%s` option is missing a `%s` method. Option: `%s`.","Fc":"invalid operation. If not provided an initial value, an array must contain at least one element.","Fd":"invalid arguments. Must provide equal length array-like objects.","Fe":"Index out of bounds","Ff":"invalid option. `%s` option must be less than or equal to 64. Option: `%u`.","Fg":"invalid argument. Unable to parse input string as a complex number. Value: `%s`.","Fh":"invalid operation. Cannot access settings for a REPL which has already closed.","Fi":"invalid argument. First argument must be a recognized setting. Value: `%s`.","Fj":"invalid invocation. `this` is not a boolean array.","Fk":"invalid argument. Unable to parse commits for package: `%s`.","Fl":"invalid argument. Unrecognized release type: `%s`.","Fm":"invalid argument. First argument must be a supported BLAS memory layout. Value: `%s`.","Fn":"invalid argument. First argument must be an existing theme name. Value: `%s`.","Fo":"invalid argument. First argument must not be the default theme name. Value: `%s`.","Fp":"invalid argument. Second argument must be an object. Value: `%s`.","Fq":"invalid arguments. Number of values does not equal the number of falsy values in the mask array.","Fr":"invalid arguments. Insufficient values to satisfy mask array.","Fs":"invalid arguments. Input arguments are not broadcast compatible.","Ft":"invalid arguments. Number of values does not equal the number of truthy values in the mask array.","Fu":"invalid argument. Third argument cannot be safely cast to the input array data type. Data types: [%s, %s].","Fv":"invalid argument. First argument must be a boolean. Value: `%s`.","Fw":"invalid argument. The third argument must be broadcast compatible with the second argument. Array shape: (%d). Desired shape: (%d).","Fx":"invalid argument. First argument must be a valid order. Value: `%s`.","Fy":"invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","Fz":"invalid argument. Third argument must be a nonnegative integer. Value: `%d`.","G0":"invalid argument. Eighth argument must be non-zero. Value: `%d`.","G1":"invalid argument. Twelfth argument must be non-zero. Value: `%d`.","G2":"invalid argument. Seventh argument must be non-zero. Value: `%d`.","G3":"invalid argument. Tenth argument must be non-zero. Value: `%d`.","G4":"invalid argument. Fourth argument must be greater than or equal to max(1,%d). Value: `%d`.","G5":"invalid argument. First argument must be a string or an array of strings. Value: `%s`.","G6":"invalid option. `%s` option must be a valid mode. Option: `%s`.","G7":"invalid argument. First argument must be a nonnegative integer. Value: `%d`.","G8":"invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.","G9":"invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.","GA":"invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GB":"invalid argument. Sixth argument must be non-zero. Value: `%d`.","GC":"invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.","GD":"invalid argument. First argument must specify whether the reference the lower or upper triangular matrix. Value: `%s`.","GE":"invalid argument. Second argument must be a nonnegative integer. Value: `%d`.","GF":"invalid argument. Fifth argument must be non-zero. Value: `%d`.","GG":"invalid argument. Second argument must be a valid transpose operation. Value: `%s`.","GH":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.","GI":"invalid argument. Ninth argument must be non-zero.","GJ":"invalid argument. Twelfth argument must be non-zero.","GK":"invalid argument. Eleventh argument must be non-zero.","GL":"invalid argument. Fifteenth argument must be non-zero.","GM":"invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.","GN":"invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GO":"invalid argument. Third argument must be a valid transpose operation. Value: `%s`.","GP":"invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.","GQ":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%d`.","GR":"invalid argument. Seventh argument must be greater than or equal to max(1,%d). Value: `%d`.","GS":"invalid argument. Ninth argument must be non-zero. Value: `%d`.","GT":"invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","GU":"invalid argument. Third argument must be a valid diagonal type. Value: `%s`.","GV":"invalid argument. First argument must be a valid transpose operation. Value: `%s`.","GW":"invalid argument. Tenth argument must be non-zero.","GX":"invalid argument. Fourteenth argument must be non-zero.","GY":"invalid arguments. Array must have the same shape.","GZ":"invalid argument. Second argument must be an array of integers. Value: `%s`.","Ga":"invalid argument. First argument must be an ndarray having at least %d dimensions.","Gb":"invalid argument. Dimension indices must be sorted in ascending order. Value: `%s`.","Gc":"invalid argument. Dimension indices must be unique. Value: `%s`.","Gd":"invalid argument. First argument must be an array of ndarrays. Value: `%s`.","Ge":"invalid argument. First argument must be an array of ndarrays which are broadcast-compatible. Value: `%s`.","Gf":"invalid argument. First argument must be an array of ndarrays having at least %d dimensions after broadcasting.","Gg":"invalid argument. Index argument is out-of-bounds. Value: `%d`.","Gh":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%d`.","Gi":"invalid argument. Ninth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gj":"invalid argument. Eleventh argument must be greater than or equal to max(1,%d). Value: `%d`.","Gk":"invalid argument. Fourteenth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gl":"invalid argument. First argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gm":"invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gn":"invalid argument. First argument must have at least one dimension.","Go":"invalid argument. Second argument must have at least one dimension.","Gp":"invalid argument. Third argument must be a negative integer. Value: `%s`.","Gq":"invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.","Gr":"invalid argument. The size of the contracted dimension must be the same for both input ndarrays. Dim(%s,%d) = %d. Dim(%s,%d) = %d.","Gs":"invalid arguments. Input ndarrays must be broadcast compatible. Shape(%s) = (%s). Shape(%s) = (%s).","Gt":"invalid argument. Cannot write to read-only array.","Gu":"invalid arguments. The first and second arguments must have the same shape.","Gv":"unexpected error. Environment does not support WebAssembly.","Gw":"invalid invocation. Unable to perform write operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gx":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Resize the underlying memory instance in order to accommodate the list of provided values.","Gy":"invalid invocation. Unable to perform read operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gz":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Not enough values to fill the provided output array.","H0":"invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.","H1":"invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H2":"invalid argument. Second argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H3":"invalid invocation. `this` is not a Float64ArrayFE.","H4":"invalid argument. First argument must be a supported byte order. Value: `%s`.","H5":"invalid argument. Second argument must a data type. Value: `%s`.","H6":"invalid argument. First argument must be an ndarray-like object having a supported data type. Value: `%s`.","H7":"invalid argument. Second argument must be an ndarray-like object having a supported data type. Value: `%s`.","H8":"invalid invocation. `this` is not %s %s.","H9":"invalid argument. First argument must be a supported data type. Value: `%s`.","HA":"invalid argument. Must provide an ArrayBuffer. Value: `%s`.","HB":"invalid argument. Second argument must be a data type. Value: `%s`.","HC":"invalid option. Each key object must have a `name` property. Value: `%s`.","HD":"invalid option. Each key object's `name` property must be a string. Value: `%s`.","HE":"invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","HF":"invalid option. Each action must be an array of objects. Value: `%s`."} +{"10":"invalid operation. Cannot reset a REPL which has already closed.","11":"invalid operation. Cannot clear a REPL which has already closed.","12":"invalid operation. Cannot clear the line of a REPL which has already closed.","13":"invalid operation. Cannot clear the command buffer of a REPL which has already closed.","14":"invalid argument. Provided command either does not contain an `await` expression or contains a top-level `return` which is not allowed.","15":"invalid argument. Must provide a program AST node.","16":"invalid invocation. Insufficient arguments. Must provide a REPL instance.","17":"invalid operation. No presentation to reload. Use the `load()` method to load a presentation.","18":"invalid operation. No presentation file to watch. Use the `load()` method to load a presentation.","19":"unexpected error. Encountered a \"rename\" event for the source presentation file. No longer watching source presentation file for changes.","20":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user is watching, an access token.","21":"unexpected error. Unable to resolve package directory as unable to find a `package.json` in a parent directory.","22":"invalid argument. Source code does not contain JSDoc comment with function options.","23":"unexpected error. Unable to resolve root project directory.","24":"invalid argument. An iterator must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","25":"invalid argument. Callback must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","26":"invalid argument. Array-like object arguments must have a length which is a multiple of two. Length: `%u`.","27":"invalid argument. Array-like object and typed array arguments must have a length which is a multiple of two. Length: `%u`.","28":"invalid argument. ArrayBuffer byte length must be a multiple of `%u`. Byte length: `%u`.","29":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","30":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.","31":"invalid argument. Fifth argument must be a function. Value: `%s`.","32":"invalid argument. Fourth argument must be a function. Value: `%s`.","33":"invalid argument. Second argument must be either an integer (starting index) or a callback function. Value: `%s`.","34":"invalid argument. Third argument must be either an integer (ending index) or a callback function. Value: `%s`.","35":"invalid argument. Second argument must be either an integer (starting view index) or a callback function. Value: `%s`.","36":"invalid argument. Third argument must be either an integer (ending view index) or a callback function. Value: `%s`.","37":"invalid argument. Second argument must be a recognized data type. Value: `%s`.","38":"invalid argument. First argument must be array-like. Value: `%s`.","39":"invalid argument. Second argument must be a string. Value: `%s`.","40":"invalid argument. Must provide either a Date object, a JavaScript timestamp (i.e., a nonnegative integer), or a date string. Value: `%s`.","41":"invalid option. Unrecognized rounding mode. Option: `%s`.","42":"invalid argument. Third argument must be either a nonnegative integer or an options object. Value: `%s`.","43":"invalid argument. Fourth argument must be an object. Value: `%s`.","44":"invalid argument. First argument must an iterator protocol-compliant object. Value: `%s`.","45":"invalid argument. Second argument must be a positive integer. Value: `%s`.","46":"invalid argument. First argument must be an iterator protocol-compliant object. Value: `%s`.","47":"invalid argument. Must provide an object. Value: `%s`.","48":"invalid argument. Object property values must be functions. Key: `%s`. Value: `%s`.","49":"invalid argument. First argument must be a number. Value: `%s`.","50":"invalid option. Second `%s` parameter option must be a positive integer. Option: `%s`.","51":"invalid argument. First argument must be an array. Value: `%s`.","52":"invalid argument. First argument must be an array of length `%u`. Value: `%s`.","53":"invalid argument. First argument must be an array of length %u. Value: `%s`.","54":"unexpected error. Scaling weight vector by nonpositive value, likely due to too large value of eta * lambda. Value: `%f`.","55":"invalid argument. Second argument must be a boolean. Value: `%s`.","56":"invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.","57":"invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.","58":"invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.","59":"invalid option. `%s` option must be a recognized casting mode. Option: `%s`.","60":"invalid argument. Input string must have a length equal to %u. Value: `%s`.","61":"invalid assignment. `%s` must be a boolean. Value: `%s`.","62":"invalid assignment. `%s` must be a string. Value: `%s`.","63":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","64":"invalid assignment. `%s` must be a positive number. Value: `%s`.","65":"invalid assignment. `%s` must be either an array of strings or an empty array. Value: `%s`.","66":"invalid assignment. `%s` must be a number or number array. Value: `%s`.","67":"invalid assignment. A `%s` must be a number on the interval: [0, 1]. Value: `%f`.","68":"invalid assignment. `%s` must be a string or a string array. Value: `%s`","69":"invalid assignment. Unsupported/unrecognized line style. Must be one of the following: \"%s\". Value: `%s`.","70":"invalid argument. Must provide a Uint32Array. Value: `%s`.","71":"invalid argument. First argument must be a positive number. Value: `%s`.","72":"invalid argument. Second argument must be a positive number. Value: `%s`.","73":"invalid argument. Second argument must be a probability. Value: `%s`.","74":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%s`.","75":"invalid option. `%s` option must have a `MIN` property specifying the minimum possible pseudorandom integer value.","76":"invalid option. `%s` option must have a `MAX` property specifying the maximum possible pseudorandom integer value.","77":"invalid argument. First argument must be an integer and not NaN. Value: `%s`.","78":"invalid argument. Second argument must be an integer and not NaN. Value: `%s`.","79":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d,%d]`.","80":"invalid argument. First argument must be either a string containing presentation text or an options object specifying a presentation file to load. Value: `%s`.","81":"invalid argument. Second argument must be an options object. Value: `%s`.","82":"invalid argument. Invalid presentation identifier. Must be either a string or nonnegative integer. Value: `%s`.","83":"invalid argument. Workspace name already exists. Value: `%s`.","84":"invalid argument. Must provide a string, regular expression, nonnegative integer, or an array of nonnegative integers. Value: `%s`.","85":"invalid argument. Unrecognized tutorial name. Value: `%s`.","86":"invalid argument. Documentation argument must be a string. Value: `%s`.","87":"invalid option. `%s` option must be a regular expression. Option: `%s`.","88":"internal error. Unrecognized pattern type: `%s`.","89":"invalid option. `%s` option must be a readable stream. Option: `%s`.","90":"invalid argument. Denominator degrees of freedom must be a positive number. Value: `%s`.","91":"invalid argument. Scale parameter must be a number. Value: `%s`.","92":"invalid argument. Mean parameter `%s` must be a probability. Value: `%s`.","93":"invalid argument. Population size must be a nonnegative integer. Value: `%s`.","94":"invalid argument. Subpopulation size must be a nonnegative integer. Value: `%s`.","95":"invalid argument. Number of draws must be a nonnegative integer. Value: `%s`.","96":"invalid assignment. Must be a nonnegative integer. Value: `%s`.","97":"invalid assignment. Must be larger than or equal to %u. Value: `%u`.","98":"invalid assignment. Must be less than or equal to %u. Value: `%u`.","99":"invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.","00":"not implemented","01":"invalid invocation. `this` context must be a constructor.","02":"invalid invocation. `this` is not a complex number array.","03":"invalid arguments. Target array lacks sufficient storage to accommodate source values.","04":"invalid arguments. Creating a generic array from an ArrayBuffer is not supported.","05":"invalid arguments. Must provide a length, typed array, array-like object, or an iterable.","06":"invalid arguments. Generated array exceeds maximum array length.","07":"invalid arguments. If either of the first two arguments are complex numbers, the output array must be a complex number array or a \"generic\" array-like object.","08":"invalid arguments. If either of the first two arguments are complex numbers, the output array data type must be a complex number data type or \"generic\".","09":"not supported. The current environment does not support SharedArrayBuffers, and, unfortunately, SharedArrayBuffers cannot be polyfilled. For shared memory applications, upgrade your runtime environment to one which supports SharedArrayBuffers.","0A":"insufficient arguments. Must provide a search value.","0B":"invalid argument. Attempted to add duplicate listener.","0C":"exception","0D":"unexpected error. Benchmark failed.","0E":"unexpected error. Invalid benchmark.","0F":"unexpected error.","0G":"invalid invocation. Constructor must be called with the `new` keyword.","0H":"unexpected error. Max retries exceeded. Too many open files.","0I":"insufficient arguments. Must provide two or more iterators.","0J":"insufficient arguments. Must provide both an iterator and a static value.","0K":"invalid invocation. `this` is not a fluent interface iterator.","0L":"insufficient arguments. Must provide a hash function.","0M":"invalid argument. Iterator arguments must be iterator protocol-compliant objects.","0N":"insufficient arguments. Must provide at least one iterator function.","0O":"invalid argument. Providing a number is not supported.","0P":"invalid argument. Providing a complex number is not supported.","0Q":"invalid argument. Providing an ndarray is not supported.","0R":"invalid argument. Providing an array-like object is not supported.","0S":"invalid argument. If the first argument is an ndarray, the second argument must be an ndarray.","0T":"invalid argument. Output array must have the same number of elements (i.e., length) as the input array.","0U":"invalid argument. If the first argument is an array-like object, the second argument must be an array-like object.","0V":"invalid argument. Providing a number is not supported. Consider providing a zero-dimensional ndarray containing the numeric value.","0W":"invalid argument. Providing a complex number is not supported. Consider providing a zero-dimensional ndarray containing the complex number value.","0X":"invalid arguments. Must provide either a data source, array shape, or both.","0Y":"invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.","0Z":"invalid argument. Cannot broadcast an array to a shape having fewer dimensions. Arrays can only be broadcasted to shapes having the same or more dimensions.","0a":"invalid argument. First argument must contain at least one element.","0b":"invalid arguments. The length of the first argument is incompatible with the second and third arguments.","0c":"invalid argument. Must provide an ndarray having two or more dimensions.","0d":"invalid arguments. Arrays must have the same shape.","0e":"invalid invocation. Cannot write to a read-only array.","0f":"invalid argument. Fourth argument length must be equal to 1 when creating a zero-dimensional ndarray.","0g":"invalid arguments. The input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","0h":"invalid arguments. Interface must accept at least one input and/or output ndarray. Based on the provided arguments, `nin+nout` equals `0`.","0i":"invalid arguments. Fourth argument does not equal the number of input and output ndarrays.","0j":"invalid argument. Unexpected number of types. A type must be specified for each input and output ndarray for each provided ndarray function.","0k":"invalid argument. The third argument must have the same number of elements as the first argument.","0l":"invalid invocation. Insufficient arguments.","0m":"invalid invocation. Too many arguments.","0n":"invalid arguments. Unable to resolve an ndarray function supporting the provided array argument data types.","0o":"invalid operation. Unable to load Electron. Ensure Electron is installed and try again.","0p":"invalid operation. A browser environment has no support for changing the current working directory.","0q":"invalid operation. The environment does not support reading from `stdin`.","0r":"unexpected error. PRNG returned NaN.","0s":"invalid argument. Third argument must be less than or equal to the first argument.","0t":"invalid argument. Second argument must be less than or equal to the first argument.","0u":"invalid operation. Cannot delete the `base` workspace.","0v":"invalid invocation. Must provide either a string containing presentation text or an options object specifying a presentation file to load.","0w":"invalid argument. When not provided presentation text, an options argument must specify a presentation file to load.","0x":"invalid invocation. Not currently in a presentation workspace. Must provide either a string or nonnegative integer which corresponds to the identifier of the presentation to be stopped.","0y":"unexpected error. Command execution terminated.","0z":"invalid operation. Cannot load a file into a REPL which has already closed.","1A":"invalid arguments. First and second arguments must be arrays having the same length.","1B":"invalid arguments. Subpopulation size must be less than or equal to population size.","1C":"invalid arguments. Number of draws must be less than or equal to population size.","1D":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number number of observations must be greater than zero).","1E":"invalid arguments. First and second arguments must have the same length.","1F":"invalid arguments. First and second arguments must be arrays having the same length.","1G":"invalid arguments. First and second argument must have the same length.","1H":"invalid arguments. Not enough observations. First and second arguments must contain at least four observations.","1I":"invalid arguments. The first and second arguments must have the same length.","1J":"`x` or `x - y` cannot be zero for all elements.","1K":"invalid arguments. Strided array parameters are incompatible with the provided array-like object. Linear index exceeds array bounds.","1L":"invalid arguments. Unable to resolve a strided array function supporting the provided array argument data types.","1M":"invalid arguments. Interface must accept at least one strided input and/or output array. Based on the provided arguments, `nin+nout` equals `0`.","1N":"invalid argument. Unexpected number of types. A type must be specified for each strided input and output array for each provided strided array function.","1O":"invalid argument. Fourth argument is incompatible with the number of strided input and output arrays.","1P":"invalid argument. Input array offset must be a nonnegative integer.","1Q":"invalid argument. Output array offset must be a nonnegative integer.","1R":"invalid argument. Input array must be an array-like object.","1S":"invalid argument. Output array must be an array-like object.","1T":"invalid argument. Input array has insufficient elements based on the associated stride and the number of indexed elements.","1U":"invalid argument. Output array has insufficient elements based on the associated stride and the number of indexed elements.","1V":"insufficient arguments. Must provide either an array of code points or one or more code points as separate arguments.","1W":"invalid argument. Third argument must not be an empty string.","1X":"invalid argument. Pad string must not be an empty string.","1Y":"insufficient arguments. Must provide multiple functions to compose.","1Z":"insufficient arguments. Must provide multiple functions to execute sequentially.","1a":"invalid arguments. First and last arguments must be the same length.","1b":"insufficient arguments. Must provide at least two objects.","1c":"invalid invocation. `this` is not a compact adjacency matrix.","1d":"invalid argument. Cannot specify one or more accessors and a value or writable attribute in the property descriptor.","1e":"invalid argument. The list does not contain the provided list node.","1f":"unexpected error. Unable to resolve global object.","1g":"invalid argument. The output ndarray must be writable. Cannot write to a read-only ndarray.","1h":"invalid arguments. Input and output arrays must have the same length.","1i":"invalid arguments. Input and output arrays must have the same number of elements (i.e., length).","1j":"invalid arguments. Input ndarrays must be broadcast compatible.","1k":"invalid arguments. Input arrays must have the same number of elements (i.e., length).","1l":"insufficient arguments. Must provide both a target object and one or more source objects.","1m":"invalid invocation. `this` is not host tuple.","1n":"invalid invocation. `this` is not the host tuple factory.","1o":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented.","1p":"invalid argument. Second argument must have a length equal to the size of the outermost input array dimension.","1q":"evaluation error. Did not receive timing results.","1r":"evaluation error. Unable to retrieve evaluation results. Ensure that the provided snippet does not return prematurely.","1s":"invalid argument. Must provide a zipped array.","1t":"invalid argument. Array must only contain arrays.","1u":"invalid argument. Indices must be specified as an array.","1v":"invalid argument. All indices must be integers.","1w":"invalid argument. Must provide valid indices (i.e., an index must be on the interval [0, len], where len is the tuple length).","1x":"insufficient arguments. Must provide at least one array.","1y":"invalid argument. Must provide a username or, to get who an authenticated user is following, an access token.","1z":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user has starred, an access token.","2A":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","2B":"invalid argument. First argument must be an ArrayBuffer. Value: `%s`.","2C":"invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.","2D":"invalid argument. Byte offset must be a multiple of `%u`. Value: `%u`.","2E":"invalid arguments. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","2F":"invalid argument. Length must be a nonnegative integer. Value: `%s`.","2G":"invalid arguments. ArrayBuffer has insufficient capacity. Either decrease the array length or provide a bigger buffer. Minimum capacity: `%u`.","2H":"invalid argument. Second argument must be a function. Value: `%s`.","2I":"invalid argument. First argument must have a length which is a multiple of two. Length: `%u`.","2J":"invalid argument. First argument must be an array-like object or an iterable. Value: `%s`.","2K":"invalid argument. Must provide a nonnegative integer. Value: `%s`.","2L":"invalid argument. Index argument must be a nonnegative integer. Value: `%s`.","2M":"invalid argument. Index argument is out-of-bounds. Value: `%u`.","2N":"invalid argument. First argument must be either a complex number, an array-like object, or a complex number array. Value: `%s`.","2O":"invalid argument. First argument must be an array-like object. Value: `%s`.","2P":"invalid argument. Second argument must be a recognized array data type. Value: `%s`.","2Q":"invalid argument. Second argument must have a recognized/supported data type. Type: `%s`. Value: `%s`.","2R":"invalid argument. Unable to parse %s date.","2S":"invalid argument. Numeric %s date must be either a Unix or JavaScript timestamp.","2T":"invalid argument. %s date must either be a date string, Date object, Unix timestamp, or JavaScript timestamp.","2U":"invalid argument. Length must be a positive integer. Value: `%s`.","2V":"invalid argument. Options argument must be an object. Value: `%s`.","2W":"invalid option. `%s` option must be a string. Option: `%s`.","2X":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","2Y":"invalid argument. Must provide a recognized data type. Value: `%s`.","2Z":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, typed array, or array-like object. Value: `%s`.","2a":"invalid argument. Must provide a length, typed array, array-like object, or an iterable. Value: `%s`.","2b":"invalid argument. Callback argument must be a function. Value: `%s`.","2c":"invalid argument. Iterator argument must be an iterator protocol-compliant object. Value: `%s`.","2d":"invalid argument. First argument must be a nonnegative integer. Value: `%s`.","2e":"invalid argument. Third argument must be a recognized data type. Value: `%s`.","2f":"invalid argument. First argument must be either an array, typed array, or complex typed array. Value: `%s`.","2g":"invalid argument. Start must be numeric. Value: `%s`.","2h":"invalid argument. Stop must be numeric. Value: `%s`.","2i":"invalid argument. Increment must be numeric. Value: `%s`.","2j":"invalid argument. First argument must be either a real or complex number. Value: `%s`.","2k":"invalid argument. Second argument must be either a real or complex number. Value: `%s`.","2l":"invalid argument. Third argument must be an array-like object. Value: `%s`.","2m":"invalid argument. Third argument must be a nonnegative integer. Value: `%s`.","2n":"invalid option. `%s` option must be a real or complex floating-point data type or \"generic\". Option: `%s`.","2o":"invalid option. `%s` option must be a boolean. Option: `%s`.","2p":"invalid argument. Exponent of start value must be numeric. Value: `%s`.","2q":"invalid argument. Exponent of stop value must be numeric. Value: `%s`.","2r":"invalid argument. First argument must be either an array length or an array-like object. Value: `%s`.","2s":"invalid argument. Must provide a typed array or ArrayBuffer. Value: `%s`.","2t":"invalid option. `%s` option must be a nonnegative integer. Option: `%s`.","2u":"invalid argument. Must provide an array-like object. Value: `%s`.","2v":"invalid option. `%s` option must be either `1` or `-1`. Option: `%s`.","2w":"invalid argument. Second argument must be either a function or an options object. Value: `%s`.","2x":"invalid argument. Must provide a typed array. Value: `%s`.","2y":"invalid argument. Second argument must be an array-like object. Value: `%s`.","2z":"invalid argument. Third argument must be an integer. Value: `%s`.","3A":"invalid argument. Key path must be a string or a key array. Value: `%s`.","3B":"invalid argument. Must provide a string. Value: `%s`.","3C":"invalid argument. Must provide a valid position (i.e., a nonnegative integer). Value: `%s`.","3D":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%u`.","3E":"invalid argument. Second argument must be callable. Value: `%s`.","3F":"invalid argument. First argument must be a string. Value: `%s`.","3G":"invalid argument. Fourth argument must be one of the following: \"%s\". Value: `%s`.","3H":"invalid argument. Fifth argument must be one of the following: \"%s\". Value: `%s`.","3I":"invalid argument. Second argument must be either an object (except null) or a function. Value: `%s`.","3J":"invalid argument. Must provide a function. Value: `%s`.","3K":"invalid argument. Must provide either an options object or a callback function. Value: `%s`.","3L":"invalid argument. First argument must be an object. Value: `%s`.","3M":"invalid option. `%s` option must be a writable stream. Option: `%s`.","3N":"invalid argument. Third argument must be a function. Value: `%s`.","3O":"invalid option. `%s` option must be either a positive integer or `null`. Option: `%s`.","3P":"invalid option. `%s` option must be a positive integer. Option: `%s`.","3Q":"invalid argument. First argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3R":"invalid argument. Second argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3S":"invalid argument. Arrays must be the same length. First argument length: `%u`. Second argument length: `%u`.","3T":"invalid argument. First argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3U":"invalid argument. Second argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3V":"invalid argument. First argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3W":"invalid argument. Second argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3X":"invalid argument. Second argument must be a nonnegative integer. Value: `%s`.","3Y":"invalid argument. Second argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3Z":"invalid argument. Last argument must be a nonnegative integer. Value: `%s`.","3a":"invalid argument. Last argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3b":"invalid argument. Must provide a Buffer. Value: `%s`.","3c":"invalid argument. First argument must be a function. Value: `%s`.","3d":"invalid argument. Third argument must be a constructor function. Value: `%s`.","3e":"invalid argument. Real component must be a number. Value: `%s`.","3f":"invalid argument. Imaginary component must be a number. Value: `%s`.","3g":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","3h":"invalid argument. Unsupported/unrecognized dataset name. Value: `%s`.","3i":"invalid option. Unrecognized `%s`. Option: `[%s]`.","3j":"invalid option. `%s` option must be a string or an array of strings. Option: `%s`.","3k":"invalid option. `%s` option must be a positive integer or an array of positive integers. Option: `%s`.","3l":"invalid option. `%s` option must be a positive integer array of length two. Option: `%s`.","3m":"invalid option. `%s` option cannot be less than 1790. Option: `%s`.","3n":"invalid option. `%s` option cannot be greater than 5000. Option: `%s`.","3o":"invalid argument. Must provide an error object. Value: `%s`.","3p":"invalid argument. First argument must be a valid file descriptor (i.e., nonnegative integer). Value: `%s`.","3q":"invalid argument. Last argument must be a function. Value: `%s`.","3r":"invalid argument. Must provide a valid file descriptor (i.e., a nonnegative integer). Value: `%s`.","3s":"invalid argument. First argument must be an array of strings. Value: `%s`.","3t":"invalid argument. Options argument must be either a string or an object. Value: `%s`.","3u":"invalid argument. Predicate function must be a function. Value: `%s`.","3v":"invalid argument. First argument must be an iterator. Value: `%s`.","3w":"invalid argument. Must provide an iterator. Value: `%s`.","3x":"invalid argument. Must provide an iterator protocol-compliant object. Argument: `%u`. Value: `%s`.","3y":"invalid argument. Must provide an iterator protocol-compliant object. Value: `%s`.","3z":"invalid argument. Unable to parse date string. Value: `%s`.","4A":"invalid argument. Second argument must be a number. Value: `%s`.","4B":"invalid argument. Third argument must be a number. Value: `%s`.","4C":"invalid argument. Hash function argument must be a function. Value: `%s`.","4D":"invalid option. `%s` option must be a positive number. Option: `%s`.","4E":"invalid argument. Third argument must be either a nonnegative integer or an object. Value: `%s`.","4F":"invalid arguments. All arguments must be functions. Value: `%s`.","4G":"invalid argument. Each iterator function, except the last iterator function, within an iterator pipeline must return an iterator. Value: `%s`.","4H":"invalid argument. Must provide an an iterator. Value: `%s`.","4I":"invalid return value. Callback function must return an integer. Value: `%s`.","4J":"invalid argument. Fourth argument must be a boolean. Value: `%s`.","4K":"invalid return value. Callback function must return a positive integer. Value: `%s`.","4L":"invalid argument. Fifth argument must be a callback function. Value: `%s`.","4M":"invalid argument. Third argument must be either an integer (starting index) or a callback function. Value: `%s`.","4N":"invalid argument. Fourth argument must be either an integer (ending index) or a callback function. Value: `%s`.","4O":"invalid argument. Unrecognized/unsupported scale function. Value: `%s`.","4P":"invalid argument. Must provide an iterator protocol-compliant object or a number. Argument: `%u`. Value: `%s`.","4Q":"invalid argument. First argument must be a finite number. Value: `%s`.","4R":"invalid option. `%s` option must be a positive finite number. Option: `%s`.","4S":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","4T":"invalid option. `%s` option must be less than or equal to 79. Option: `%u`.","4U":"invalid option. `%s` option must be less than or equal to 77. Option: `%u`.","4V":"invalid argument. Must provide an argument having a supported data type. Value: `%s`.","4W":"invalid option. Unsupported policy for determining an output array data type. Option: `%s`.","4X":"invalid option. `%s` option must be a recognized/supported data type. Option: `%s`.","4Y":"invalid option. `%s` option must be a recognized/supported output array data type policy. Option: `%s`.","4Z":"invalid argument. Resolution table must be an object. Value: `%s`.","4a":"invalid argument. Resolution table `%s` field value must be either a function or null. Value: `%s`.","4b":"invalid argument. First argument must be a positive integer. Value: `%s`.","4c":"invalid argument. First argument must be a one-dimensional ndarray. Value: `%s`.","4d":"invalid argument. Second argument must be either +1 or -1. Value: `%s`.","4e":"invalid argument. First argument must be a one-dimensional ndarray of length %u. Actual length: `%u`.","4f":"invalid argument. First argument must be an ndarray. Value: `%s`.","4g":"invalid argument. First argument must be an ndarray whose last dimension is of size `%u`. Actual size: `%u`.","4h":"invalid argument. Second argument is incompatible with model loss function. Probability predictions are only supported when the loss function is one of the following: \"%s\". Model loss function: `%s`.","4i":"invalid argument. Second argument must be a string value equal to either \"label\", \"probability\", or \"linear\". Value: `%s`.","4j":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of `eta*lambda`. Value: `%f`.","4k":"invalid option. `%s` option must be a nonnegative number. Option: `%s`.","4l":"invalid option. `%s` option must be an array-like object. Option: `%s`.","4m":"invalid option. First `%s` option must be one of the following: \"%s\". Option: `%s`.","4n":"invalid option. Second `%s` option must be a positive number. Option: `%s`.","4o":"invalid option. Third `%s` option must be a number. Option: `%s`.","4p":"invalid argument. Argument specifying number of dimensions must be a positive integer. Value: `%s`.","4q":"invalid argument. First argument must either be a positive integer specifying the number of clusters or a matrix containing initial centroids. Value: `%s`.","4r":"invalid option. First `%s` parameter option must be greater than or equal to the number of clusters. Options: `%f`.","4s":"invalid argument. Must provide a 1-dimensional ndarray. Value: `%s`.","4t":"invalid argument. Vector length must match centroid dimensions. Expected: `%u``. Actual: `%u``.","4u":"invalid argument. Output argument must be a 1-dimensional ndarray. Value: `%s`.","4v":"invalid argument. Must provide a 2-dimensional ndarray. Value: `%s`.","4w":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u``. Actual: `%u`.","4x":"invalid argument. Output vector length must match the number of data points. Expected: `%u`. Actual: `%u`.","4y":"invalid option. `%s` option method must be one of the following: \"%s\". Option: `%s`.","4z":"invalid option. First `%s` parameter option must be a positive integer. Option: `%s`.","5A":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","5B":"invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.","5C":"invalid option. `%s` option must be a recognized order. Option: `%s`.","5D":"invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.","5E":"invalid argument. Linear index must not exceed array dimensions. Number of array elements: `%u`. Value: `%d`.","5F":"invalid argument. Input array cannot be broadcast to the specified shape, as the specified shape has a dimension whose size is less than the size of the corresponding dimension in the input array. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5G":"invalid argument. Input array and the specified shape are broadcast incompatible. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5H":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.","5I":"invalid argument. Index must be on the interval: [0, %f]. Value: `%f`.","5J":"invalid argument. Subscripts must not exceed array dimensions. Subscript: `%u`. Value: `%d`.","5K":"invalid argument. First argument must be a recognized data type. Value: `%s`.","5L":"invalid argument. First argument must have a recognized data type. Value: `%s`.","5M":"invalid arguments. Number of indices must match the number of dimensions. ndims: `%u`. nargs: `%u`.","5N":"invalid argument. Indices must be integer valued. Argument: `%u`. Value: `%s`.","5O":"invalid argument. Index must be an integer. Value: `%s`.","5P":"invalid argument. First argument must be a supported ndarray data type. Value: `%s`.","5Q":"invalid argument. Second argument must be an array-like object, typed-array-like, or a Buffer. Value: `%s`.","5R":"invalid argument. Second argument `get` and `set` properties must be functions. Value: `%s`.","5S":"invalid argument. Third argument must be an array-like object containing nonnegative integers. Value: `%s`.","5T":"invalid argument. Number of dimensions must not exceed %u due to stack limits. Value: `%u`.","5U":"invalid argument. Fourth argument must be an array-like object containing integers. Value: `%s`.","5V":"invalid argument. Fourth argument length must match the number of dimensions. Expected number of dimensions: `%u`. Strides length: `%u`.","5W":"invalid argument. Fourth argument must contain a single element equal to `0`. Value: `%d`.","5X":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.","5Y":"invalid argument. Sixth argument must be a supported order. Value: `%s`.","5Z":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%u`.","5a":"invalid option. `%s` option must be a recognized mode. Option: `%s`.","5b":"invalid option. `%s` option must be an array containing recognized modes. Option: `%s`.","5c":"invalid option. Each submode must be a recognized mode. Option: `%s`.","5d":"invalid argument. First argument must be either a function or an array of functions. Value: `%s`.","5e":"invalid argument. Third argument must be an array-like object or null. Value: `%s`.","5f":"invalid argument. Fourth argument must be a positive integer. Value: `%s`.","5g":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%s`.","5h":"invalid argument. Input array must be an ndarray-like object. Value: `%s`.","5i":"invalid argument. Output array must be an ndarray-like object. Value: `%s`.","5j":"invalid argument. Output argument must be either an array, typed array, or object. Value: `%s`.","5k":"invalid argument. Shape argument must be an array-like object containing nonnegative integers. Value: `%s`.","5l":"invalid argument. Linear index must be integer valued. Value: `%s`.","5m":"invalid option. `%s` option must be a supported/recognized mode. Option: `%s`.","5n":"invalid option. `%s` option must be a supported/recognized order. Option: `%s`.","5o":"invalid argument. First argument must be an array-like object containing nonnegative integers. Value: `%s`.","5p":"invalid argument. Number of provided subscripts must match the number of dimensions. ndims: `%u`. Number of subscripts: `%u`.","5q":"invalid argument. Subscripts must be integer valued. Argument: `%u`. Value: `%s`.","5r":"invalid option. `%s` option cannot be an empty array.","5s":"invalid argument. First argument must be either a nonnegative integer or an array of nonnegative integers. Value: `%s`.","5t":"invalid argument. First argument must be an ndarray-like object. Value: `%s`.","5u":"invalid option. `%s` option must either be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","5v":"invalid option. `%s` option must be either a Buffer or a string. Option: `%s`.","5w":"invalid argument. Request listener must be a function. Value: `%s`.","5x":"invalid argument. Third argument must be a positive integer. Value: `%s`.","5y":"invalid argument. Number of topics must be a positive integer. Value: `%s`.","5z":"invalid argument. First argument must be a nonnegative integer which is less than the total number of topics. Value: `%s`.","6A":"invalid assignment. `%s` must be a nonnegative integer or nonnegative integer array. Value: `%s`.","6B":"invalid assignment. `%s` must be a nonnegative integer. Value: `%s`.","6C":"invalid assignment. Unrecognized/unsupported `%s`. Must be one of the following: \"%s\". Value: `%s`.","6D":"invalid assignment. Unrecognized/unsupported `%s`. Value: `%s`.","6E":"invalid assignment. `%s` must be a nonnegative integer or null. Value: `%s`.","6F":"invalid assignment. `%s` must be a string or null. Value: `%s`.","6G":"invalid argument. Must provide a supported viewer. Value: `%s`.","6H":"invalid assignment. `%s` must be a function. Value: `%s`.","6I":"invalid assignment. `%s` must be either null or an array. Value: `%s`.","6J":"invalid assignment. `%s` must be a string, function, or null. Value: `%s`.","6K":"invalid argument. `options` argument must be an object. Value: `%s`.","6L":"invalid assignment. `%s` must be a number. Value: `%s`.","6M":"invalid assignment. `%s` must be a number on the interval `[0,1]`. Value: `%f`.","6N":"invalid assignment. `%s` must be array-like. Value: `%s`.","6O":"invalid arguments. Must provide equal length array-like objects. x length: `%u`, y length: `%u`.","6P":"invalid assignment. `%s` must be a string or a function. Value: `%s`.","6Q":"invalid assignment. `%s` must be a number or a function. Value: `%s`.","6R":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","6S":"invalid assignment. `%s` must be a nonnegative integer or a function. Value: `%s`.","6T":"invalid assignment. `%s` must be a supported symbol. Symbols: \"%s\". Value: `%s`.","6U":"invalid argument. `options` argument must be a plain object. Value: `%s`.","6V":"invalid assignment. `%s` must be either a string or a string array. Value: `%s`.","6W":"invalid assignment. `%s` must be a string or a string array. Value: `%s`.","6X":"invalid assignment. `%s` must be a string or string array. Value: `%s`.","6Y":"invalid assignment. Unrecognized/unsupported symbol. Value: `[%s]`.","6Z":"invalid assignment. `%s` must be an array. Value: `%s`.","6a":"invalid assignment. `%s` must be either a finite number, Date, or null. Value: `%s`.","6b":"invalid assignment. `%s` must be a boolean or boolean array. Value: `%s`.","6c":"invalid assignment. `%s` must be either a string or string array. Value: `%s`.","6d":"invalid assignment. Unrecognized/unsupported orientation. A `%s` value must be one of the following: \"%s\". Value: `%s`.","6e":"invalid assignment. `%s` must be either a finite number or null. Value: `%s`.","6f":"invalid state. x and y are different lengths. x length: `%u`, y length: `%u`.","6g":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[","6h":"invalid assignment. `%s` must be a positive integer or null. Value: `%s`.","6i":"invalid assignment. `%s` size is smaller than the number of data elements. Number of elements: `%u`. Value: `%u`.","6j":"invalid assignment. `%s` must be an array-like object or an ndarray. Value: `%s`.","6k":"invalid assignment. `%s` length exceeds maximum data buffer size. Buffer size: `%u`. Length: `%u`.","6l":"invalid assignment. `%s` must be a finite number or null. Value: `%s`.","6m":"invalid assignment. `%s` must be a finite number or null. Value: `%s.","6n":"invalid assignment. Must be an array or typed array. Value: `%s`.","6o":"invalid option. `%s` option must be an array or typed array. Option: `%s`.","6p":"invalid option. `%s` option must be a function. Option: `%s`.","6q":"invalid argument. Encoding argument must be a string. Value: `%s`.","6r":"invalid argument. Must provide either a string, nonnegative integer, or an options object. Value: `%s`.","6s":"invalid argument. First argument must be either a string or nonnegative integer. Value: `%s`.","6t":"invalid argument. Unable to parse mask expression. Ensure the expression is properly formatted, only uses the class letters \"u\", \"g\", \"o\", and \"a\", only uses the operators \"+\", \"-\", and \"=\", and only uses the permission symbols \"r\", \"w\", and \"x\". Value: `%s`.","6u":"invalid option. `%s` option must be a pseudorandom number generator function. Option: `%s`.","6v":"invalid argument. First argument must be a number and not NaN. Value: `%s`.","6w":"invalid argument. Second argument must be a number and not NaN. Value: `%s`.","6x":"invalid argument. Minimum support must be less than maximum support. Value: `[%f,%f]`.","6y":"invalid argument. First argument must be a probability. Value: `%s`.","6z":"invalid option. `%s` option must be a Uint32Array. Option: `%s`.","7A":"invalid argument. First argument must be a positive number and not NaN. Value: `%s`.","7B":"invalid argument. Second argument must be a positive number and not NaN. Value: `%s`.","7C":"invalid argument. Third argument must be a number and not NaN. Value: `%s`.","7D":"invalid argument. Third argument must be less than or equal to the first argument. Value: `%u`.","7E":"invalid argument. Second argument must be less than or equal to the first argument. Value: `%u`.","7F":"invalid %s. State array has insufficient length.","7G":"invalid %s. State array has an incompatible schema version. Expected: `%s`. Actual: `%s`.","7H":"invalid %s. State array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","7I":"invalid %s. State array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7J":"invalid %s. State array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7K":"invalid option. `%s` option must be an Int32Array. Option: `%s`.","7L":"invalid option. `%s` option must be a positive integer less than the maximum signed 32-bit integer. Option: `%u`.","7M":"invalid option. `%s` option must be either a positive integer less than the maximum signed 32-bit integer or an array-like object containing integer values less than the maximum signed 32-bit integer. Option: `%s`.","7N":"invalid argument. Must provide an Int32Array. Value: `%s`.","7O":"invalid %s. State array has an incompatible table length. Expected: `%s`. Actual: `%s`.","7P":"invalid %s. `state` array has insufficient length.","7Q":"invalid %s. `state` array has an incompatible schema version. Expected: %s. Actual: %s.","7R":"invalid %s. `state` array has an incompatible number of sections. Expected: %s. Actual: %s.","7S":"invalid %s. `state` array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7T":"invalid %s. `state` array has an incompatible section length. Expected: `%u`. Actual: `%u`.","7U":"invalid %s. `state` array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7V":"invalid option. `%s` option must be a positive integer less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7W":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7X":"invalid argument. Second argument must be on the interval: (0, 1). Value: `%f`.","7Y":"invalid option. `%s` option cannot be undefined. Option: `%s`.","7Z":"invalid option. Unrecognized/unsupported PRNG. Option: `%s`.","7a":"invalid argument. First argument must be a positive number or an options object. Value: `%s`.","7b":"invalid arguments. Parameters must satisfy the following condition: %s. Value: `[%f, %f, %f]`.","7c":"invalid argument. Scale parameter must be a positive number. Value: `%s`.","7d":"invalid argument. Shape parameter must be a positive number. Value: `%s`.","7e":"invalid argument. First argument must be an integer. Value: `%s`.","7f":"invalid argument. Second argument must be an integer. Value: `%s`.","7g":"invalid argument. `n` must be less than or equal to `N`. Value: `%u`.","7h":"invalid argument. `K` must be less than or equal to `N`. Value: `%u`.","7i":"invalid argument. `%s` argument must be array-like. Value: `%s`.","7j":"invalid input option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","7k":"invalid input option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","7l":"invalid option. `%s` option must be an array of probabilities that sum to one. Option: `%s`.","7m":"invalid argument. Minimum support must be less than maximum support. Value: `[%s,%s]`.","7n":"invalid option. `%s` option must be a string or null. Option: `%s`.","7o":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%s,%s]`.","7p":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7q":"invalid argument. Mode must be one of the following: \"%s\". Value: `%s`.","7r":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7s":"invalid operation. Alias already exists in the provided context. Alias: `%s`. Value: `%s`.","7t":"invalid argument. Unrecognized workspace name. Value: `%s`.","7u":"invalid operation. Cannot read from write-only variable `%s`.","7v":"Cannot assign to read only property %s of object #","7w":"invalid option. `%s` option must be a regular expression or an array-like object. Option: `%s`.","7x":"invalid option. `%s` option must be one of `%s`. Option: `%s`.","7y":"invalid argument. Must provide either an options object or a workspace name. Value: `%s`.","7z":"invalid argument. Must provide either a string or regular expression. Value: `%s`.","8A":"invalid argument. Must provide an integer. Value: `%s`.","8B":"invalid argument. Must provide a positive integer. Value: `%s`.","8C":"invalid argument. Presentation text must be a string. Value: `%s`.","8D":"invalid argument. REPL argument must be a REPL instance. Value: `%s`.","8E":"unexpected error. Unable to reload presentation. Error: %s","8F":"unexpected error. Unable to watch presentation source file. Error: %s","8G":"invalid option. `%s` option must be either a recognized string or boolean. Option: `%s`.","8H":"invalid option. `%s` option must be either a positive integer or null. Option: `%s`.","8I":"invalid operation. Alias already exists in REPL context. Alias: `%s`. Value: `%s`.","8J":"invalid argument. Third argument must be an object. Value: `%s`.","8K":"invalid option. `%s` option must be less than or equal to the period. Option: `%u`.","8L":"invalid option. `%s` option must be greater than 2. Option: `%s`.","8M":"invalid option. `%s` option must be an integer. Option: `%s`.","8N":"invalid option. `%s` option must be an positive integer. Option: `%s`.","8O":"invalid option. `%s` option must be less than the period. Option: `%s`.","8P":"invalid option. `%s` option must be a number. Option: `%s`.","8Q":"invalid option. `%s` option must be an positive even integer. Option: `%s`.","8R":"invalid argument. First argument must be a numeric array. Value: `%s`.","8S":"invalid argument. First argument must contain at least two elements. Value: `%s`.","8T":"invalid argument. Second argument must be an array. Value: `%s`.","8U":"invalid argument. Second argument must contain at least two unique elements. Value: `%s`.","8V":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%f`.","8W":"invalid option. `%s` option must be an array containing at least two unique elements. Option: `%s`.","8X":"invalid argument. Must provide array-like arguments. Value: `%s`.","8Y":"invalid argument. Supplied arrays cannot be empty. Value: `%s`.","8Z":"invalid option. `%s` option must be an array. Option: `%s`.","8a":"invalid argument. Minimum support must be a number. Value: `%s`.","8b":"invalid argument. Maximum support must be a number. Value: `%s`.","8c":"invalid arguments. Minimum support must be less than maximum support. Value: `%f, %f`.","8d":"invalid assignment. Must be a number. Value: `%s`.","8e":"invalid assignment. Must be less than %f. Value: `%f`.","8f":"invalid assignment. Must be greater than %f. Value: `%f`.","8g":"invalid argument. Mean parameter `p` must be a probability. Value: `%s`.","8h":"invalid assignment. Must be a probability. Value: `%s`.","8i":"invalid argument. First shape parameter must be a positive number. Value: `%s`.","8j":"invalid argument. Second shape parameter must be a positive number. Value: `%s`.","8k":"invalid assignment. Must be a positive number. Value: `%s`.","8l":"invalid argument. Number of trials must be a positive integer. Value: `%s`.","8m":"invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.","8n":"invalid assignment. Must be a positive integer. Value: `%s`.","8o":"invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.","8p":"invalid argument. Location parameter must be a number. Value: `%s`.","8q":"invalid argument. Rate parameter must be a positive number. Value: `%s`.","8r":"invalid argument. Mean parameter `%s` must be a number. Value: `%s`.","8s":"invalid argument. Minimum support must be an integer. Value: `%s`.","8t":"invalid argument. Maximum support must be an integer. Value: `%s`.","8u":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `%d, %d`.","8v":"invalid assignment. Must be an integer. Value: `%s`.","8w":"invalid assignment. Must be less than or equal to %u. Value: `%d`.","8x":"invalid assignment. Must be greater than or equal to %u. Value: `%s`.","8y":"invalid argument. Shape parameter must be a positive integer. Value: `%s`.","8z":"invalid argument. Numerator degrees of freedom must be a positive number. Value: `%s`.","9A":"invalid argument. Mean parameter `lambda` must be a positive number. Value: `%s`.","9B":"invalid argument. Mode must be a number. Value: `%s`.","9C":"invalid arguments. Parameters must satisfy the following condition: %s. a: `%f`. b: `%f`. c: `%f`.","9D":"invalid assignment. Must be less than or equal to both the maximum support and the mode. Value: `%f`.","9E":"invalid assignment. Must be greater than or equal to both the minimum support and the mode. Value: `%f`.","9F":"invalid assignment. Must be greater than or equal to the minimum support and less than or equal to the maximum support. Value: `%f`.","9G":"invalid argument. An array argument must contain two elements. Value: `%s`.","9H":"invalid argument. Must provide a nonnegative integer or a two-element array. Value: `%s`.","9I":"invalid arguments. Number of successes cannot be larger than the total number of observations. x: `%u`. n: `%u`.","9J":"invalid option. `%s` option must be a probability. Option: `%f`.","9K":"invalid argument. Unsupported/unrecognized distribution name. Value: `%s`.","9L":"invalid argument. First argument must contain nonnegative integers. Index: `%u`. Value: `%s`.","9M":"invalid argument. Probability mass function (PMF) arguments must be numbers. Argument: `%u`. Value: `%s`.","9N":"invalid argument. Second argument must be either an array-like object (or one-dimensional ndarray) of probabilities summing to one, an array-like object (or one-dimensional ndarray) of expected frequencies, or a discrete probability distribution name. Value: `%s`.","9O":"invalid argument. Second argument must only contain numbers. Index: `%u`. Value: `%s`.","9P":"invalid argument. Second argument must only contain nonnegative numbers. Index: `%u`. Value: `%d`.","9Q":"invalid option. `%s` option must be a number on the interval: [0, 1]. Value: `%s`.","9R":"invalid argument. First argument must be an array of arrays or ndarray-like object with dimension two. Value: `%s`.","9S":"invalid argument. First argument must contain nonnegative integers. Value: `%s`.","9T":"invalid argument. First argument must either specify the order of the covariance matrix or be a square 2-dimensional ndarray for storing the covariance matrix. Value: `%s`.","9U":"invalid argument. Second argument must be a 1-dimensional ndarray. Value: `%s`.","9V":"invalid argument. The number of elements (means) in the second argument must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9W":"invalid argument. Vector length must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9X":"invalid argument. Must provide a number. Value: `%s`.","9Y":"invalid argument. Must provide a nonnegative number. Value: `%s`.","9Z":"invalid argument. Must provide a nonnegative number on the interval [0,1]. Value: `%f`.","9a":"invalid argument. Output argument must be an array-like object. Value: `%s`.","9b":"invalid argument. Window size must be a positive integer. Value: `%s`.","9c":"invalid argument. Window size must be greater than or equal to 3. Value: `%s`.","9d":"invalid option. `%s` option must be on the interval [0,1]. Option: `%f`.","9e":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square 2-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","9f":"invalid argument. The number of elements (means) in the second argument must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9g":"invalid argument. Vector length must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","9h":"invalid argument. Vector length must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9i":"invalid argument. First argument must either specify the order of the correlation matrix or be a square 2-dimensional ndarray for storing the correlation matrix. Value: `%s`.","9j":"invalid argument. Unsupported/unrecognized kernel. Value: `%s`.","9k":"invalid argument. Second argument must be a numeric array. Value: `%s`.","9l":"invalid option. Lower bound `%s` must be strictly less than the upper bound `%s`.","9m":"invalid option. `%s` option must be an array of positive numbers. Option: `%s`.","9n":"invalid option. `%s` option must be an array of length two. Option: `%s`.","9o":"invalid option. `%s` option must be a string denoting a known kernel function or a custom function. Option: `%s`.","9p":"invalid arguments. First argument and `%s` must be arrays having the same length.","9q":"invalid invocation. Incorrect number of arguments. Must provide at least two array-like arguments. Value: `%s`.","9r":"invalid option. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","9s":"invalid argument. First argument must be a typed array or number array. Value: `%s`.","9t":"invalid argument. Second argument must be either a CDF function or a string. Value: `%s`.","9u":"invalid argument. Distribution parameter must be a number. Value: `%s`.","9v":"invalid option. `%s` option must contain at least two unique elements. Value: `%s`.","9w":"invalid argument. Provided arrays cannot be empty. Value: `%s`.","9x":"invalid argument. First argument must be an array of probabilities. Value: `%s`.","9y":"invalid argument. When specified, `%s` arguments must contain at least a length of %u. Value: `%u`.","9z":"invalid argument. Second argument must be one of the following: %s. Value: `%s`.","A0":"invalid option. `%s` option must be a number in `[0,1]`. Option: `%s`.","A1":"invalid option. `%s` option must be a number on the interval: [-1, 1]. Option: `%s`.","A2":"invalid argument. First argument must contain at least two elements. Value: `%s`.","A3":"invalid argument. Second argument must be either a numeric array or an options object. Value: `%s`.","A4":"invalid option. `%s` option must be either `equal` or `unequal`. Option: `%s`.","A5":"invalid argument. `%s` argument must be a numeric array. Value: `%s`.","A6":"invalid option. `%s` option must be one of the following: %s. Option: `%s`.","A7":"invalid argument. Third argument must be a positive number. Value: `%s`.","A8":"invalid argument. Fourth argument must be a positive number. Value: `%s`.","A9":"invalid operation. Serialization function must return a string or Buffer. Value: `%s`.","AA":"invalid argument. In binary mode, a provided value must be a string, Buffer, or Uint8Array. Value: `%s`.","AB":"invalid option. `%s` option must be either a string or a regular expression. Option: `%s`.","AC":"invalid argument. First input array offset must be a nonnegative integer. Value: `%s`.","AD":"invalid argument. Second input array offset must be a nonnegative integer. Value: `%s`.","AE":"invalid argument. Output array offset must be a nonnegative integer. Value: `%s`.","AF":"invalid argument. Must provided recognized data types. Unable to resolve a data type string. Value: `%s`.","AG":"invalid argument. Input array offset must be a nonnegative integer. Value: `%s`.","AH":"invalid argument. Input array stride must be an integer. Value: `%s`.","AI":"invalid argument. Output array stride must be an integer. Value: `%s`.","AJ":"invalid option. `%s` option must be an array of strings. Option: `%s`.","AK":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%s`.","AL":"invalid argument. Third argument must be a boolean. Value: `%s`.","AM":"invalid argument. Must provide valid code points (i.e., nonnegative integers). Value: `%s`.","AN":"invalid argument. Must provide a valid code point (cannot exceed max). Value: `%s`.","AO":"invalid argument. Third argument must be a string. Value: `%s`.","AP":"invalid argument. Output string length exceeds maximum allowed string length. Value: `%u`.","AQ":"invalid argument. Third argument must be a string or an array of strings. Value: `%s`.","AR":"invalid argument. At least one padding option must have a length greater than 0. Left padding: `%s`. Right padding: `%s`.","AS":"invalid argument. Second argument must be an array of strings. Value: `%s`.","AT":"invalid argument. Second argument must be a string or regular expression. Value: `%s`.","AU":"invalid argument. Third argument must be a string or replacement function. Value: `%s`.","AV":"invalid argument. Must provide a string or an array of strings. Value: `%s`.","AW":"invalid argument. If only providing a single argument, must provide a Date object. Value: `%s`.","AX":"invalid argument. First argument must be either a string or integer. Value: `%s`.","AY":"invalid argument. Day number must be on the interval: `[1, %u]`. Value: `%d`.","AZ":"invalid argument. First argument must be either a string, integer, or Date object. Value: `%s`.","Aa":"invalid argument. An integer month value must be on the interval: [1, 12]. Value: `%s`.","Ab":"invalid argument. Must provide a recognized month. Value: `%s`.","Ac":"invalid argument. Must provide either an integer or a `Date` object. Value: `%s`.","Ad":"invalid argument. Must provide either a string, integer, or Date object. Value: `%s`.","Ae":"invalid argument. Must provide an array of nonnegative integers. Value: `%s`.","Af":"invalid argument. Input array must contain two elements. Value: `%s`.","Ag":"invalid argument. Must provide a collection. Value: `%s`.","Ah":"invalid argument. First argument must be a collection. Value: `%s`.","Ai":"invalid argument. First argument must be either an array, typed array, or an array-like object. Value: `%s`.","Aj":"invalid argument. All arguments must be functions. Value: `%s`.","Ak":"invalid argument. Number of function invocations must be a nonnegative integer. Value: `%s`.","Al":"invalid argument. First argument must be an array of functions. Value: `%s`.","Am":"invalid argument. Last argument must be a collection. Value: `%s`.","An":"invalid argument. Must provide either a valid buffer size (i.e., a positive integer) or an array-like object which can serve as the underlying buffer. Value: `%s`.","Ao":"invalid argument. An iterator must return an array-like object containing vertices. Value: `%s`.","Ap":"invalid argument. Callback must return an array-like object containing vertices. Value: `%s`.","Aq":"invalid argument. Callback must return an array-like object. Value: `%s`.","Ar":"invalid argument. Each element of the adjacency list must be an array-like object. Value: `%s`.","As":"invalid argument. Each element of the edge list must be an array-like object. Value: `%s`.","At":"invalid argument. Second argument must be an array-like object or an iterable. Value: `%s`.","Au":"invalid argument. First argument exceeds matrix dimensions. Value: `%u`.","Av":"invalid argument. Second argument exceeds matrix dimensions. Value: `%u`.","Aw":"invalid argument. Vertex cannot exceed matrix dimensions. Value: `%u`.","Ax":"invalid argument. Second argument must be a recognized output path convention. Value: `%s`.","Ay":"invalid argument. Cannot convert Windows extended-length paths to POSIX paths. Value: `%s`.","Az":"invalid argument. Arity argument must be a positive integer. Value: `%s`.","B0":"invalid argument. Property descriptor must be an object. Value: `%s`.","B1":"invalid argument. The `value` property of the property descriptor must be a function. Value: `%s`.","B2":"invalid argument. Second argument must be an object of property descriptors. Value: `%s`.","B3":"invalid argument. Path must be a string. Value: `%s`.","B4":"invalid argument. Third argument must be a recognized location. Value: `%s`.","B5":"invalid argument. Must provide a recognized iteration direction. Value: `%s`.","B6":"invalid argument. Must provide an object-like value. Value: `%s`.","B7":"invalid argument. Must provide a regular expression string. Value: `%s`.","B8":"invalid argument. Filename must be a string. Value: `%s`.","B9":"invalid argument. First argument must be an array of positive integers. Value: `%s`.","BA":"invalid argument. First argument must be object-like. Value: `%s`.","BB":"invalid argument. Must provide an array of arrays. Value: `%s`.","BC":"invalid argument. Must provide a boolean. Value: `%s`.","BD":"invalid argument. Second argument must have a prototype from which another object can inherit. Value: `%s`.","BE":"invalid argument. A provided constructor must be either an object (except null) or a function. Value: `%s`.","BF":"invalid argument. If the input array is an ndarray, the output array must also be an ndarray. Value: `%s`.","BG":"invalid argument. If the input array is an array-like object, the output array must also be an array-like object. Value: `%s`.","BH":"invalid argument. First argument must be an array-like object or an ndarray. Value: `%s`.","BI":"invalid argument. If the first input array is an ndarray, the second input array must also be an ndarray. Value: `%s`.","BJ":"invalid argument. If the input arrays are ndarrays, the output array must also be an ndarray. Value: `%s`.","BK":"invalid argument. If the first input array is an array-like object, the second input array must also be an array-like object. Value: `%s`.","BL":"invalid argument. If the input arrays are array-like objects, the output array must also be an array-like object. Value: `%s`.","BM":"invalid argument. First argument must be an array-like object containing array-like objects. Index: `%u`. Value: `%s`.","BN":"invalid argument. First argument must be a three-dimensional nested array. Index: `%u`. Value: `%s`.","BO":"invalid argument. First argument must be a four-dimensional nested array. Index: `%u`. Value: `%s`.","BP":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BQ":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BR":"invalid argument. First argument must be a five-dimensional nested array. Index: `%u`. Value: `%s`.","BS":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BT":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BU":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u, %u). Value: `%s`.","BV":"invalid argument. A merge source must be an object. Value: `%s`.","BW":"invalid option. `%s` option must be either a boolean or a function. Option: `%s`.","BX":"invalid argument. Source argument must be an object. Value: `%s`.","BY":"invalid argument. Target argument must be an object. Value: `%s`.","BZ":"invalid argument. Must provide an array of strings. Value: `%s`.","Ba":"invalid argument. Field names must be distinct. Value: `%s`.","Bb":"invalid argument. Provided field name is reserved. Name: `%s`.","Bc":"invalid arguments. Arguments are incompatible with the number of tuple fields. Number of fields: `%u`. Number of data elements: `%u`.","Bd":"invalid argument. Source is incompatible with the number of tuple fields. Number of fields: `%u`. Source length: `%u`.","Be":"invalid invocation. Number of arguments is incompatible with the number of tuple fields. Number of fields: `%u`. Number of arguments: `%u`.","Bf":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","Bg":"invalid argument. Second argument must be either a string or an array of strings. Value: `%s`.","Bh":"invalid argument. Must provide a valid URI. Value: `%s`.","Bi":"unexpected error. Child process failed with exit code: `%u`.","Bj":"unexpected error. Child process failed due to termination signal: `%s`.","Bk":"invalid argument. Reviver argument must be a function. Value: `%s`.","Bl":"invalid argument. Second argument must be an array-like object containing nonnegative integers. Value: `%s`.","Bm":"invalid argument. Must provide either an array, typed array, or an array-like object. Value: `%s`.","Bn":"invalid argument. Must provide a recognized type. Value: `%s`.","Bo":"invalid argument. Second argument must be an array containing only nonnegative integers. Value: `%s`.","Bp":"invalid invocation. Unexpected number of input arguments. Expected: `%u`. Actual: `%u`.","Bq":"evaluation error. Encountered an error when evaluating snippet. %s","Br":"invalid option. `%s` option must be a positive integer or null. Option: `%s`.","Bs":"insufficient arguments. Expected %u argument(s) and only received %u argument(s).","Bt":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: %u. Actual: %u.","Bu":"invalid invocation. Number of arguments exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bv":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bw":"invalid argument. Must provide array arguments. Value: `%s`.","Bx":"invalid argument. Last argument must be either an array or an options object. Value: `%s`.","By":"invalid argument. Repository slug must be a string. Value: `%s`.","Bz":"invalid argument. Issue title must be a string. Value: `%s`.","C0":"invalid option. `%s` must be one of the following: \"%s\". Option: `%s`.","C1":"invalid argument. Repository name must be a string. Value: `%s`.","C2":"invalid option. `%s` option must be a valid URI. Option: `%s`.","C3":"invalid option. `%s` option must be a 20-character string. Option: `%s`.","C4":"invalid option. `%s` option must be a 40-character string. Option: `%s`.","C5":"invalid argument. Token id must be a nonnegative integer. Value: `%s`.","C6":"invalid argument. Workflow identifier must be a string. Value: `%s`.","C7":"invalid option. `%s` option must be an object of input key-value pairs. Option: `%s`.","C8":"invalid option. `%s` option must be a positive integer or \"last\". Option: `%s`.","C9":"invalid option. `%s` organization name option must be a string. Option: `%s`.","CA":"invalid option. Unknown method. Option: `%s`.","CB":"invalid option. Unrecognized `%s` option. Must be one of the following: \"%s\". Option: `%s`.","CC":"invalid argument. Repository slug must consist of an owner and a repository (e.g., \"stdlib-js/utils\"). Value: `%s`.","CD":"invalid argument. Topics argument must be an array of strings. Value: `%s`.","CE":"invalid option. `%s` option must be one of the following: \"%s\" or \"%s\". Option: `%s`.","CF":"invalid argument. Must provide a supported license SPDX identifier. Value: `%s`.","CG":"invalid argument. Must provide a supported file type. Value: `%s`.","CH":"invalid argument. First argument must be either a string or Buffer. Value: `%s`.","CI":"invalid argument. Second argument must be either a string or Buffer. Value: `%s`.","CJ":"invalid argument. A header object must map each filename extension to a license header string. `%s: %s`. Value: `%s`.","CK":"invalid argument. Second argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CL":"invalid argument. Second argument must be either a string, Buffer, or regular expression. Value: `%s`.","CM":"invalid argument. A header object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CN":"invalid argument. Second argument must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Value: `%s`.","CO":"invalid argument. Third argument must be either a string or Buffer. Value: `%s`.","CP":"invalid argument. Third argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CQ":"invalid argument. Database already contains an entry for the provided URI: `%s`.","CR":"invalid argument. Database already contains an entry for the provided id: `%s`.","CS":"invalid argument. First argument must be a URI. Value: `%s`.","CT":"invalid argument. Second argument must be either a string or regular expression. Value: `%s`.","CU":"invalid option. A `%s` option object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CV":"invalid option. `%s` option must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Option: `%s`.","CW":"invalid option. `%s` option must end with \"package.json\". Option: `%s`.","CX":"invalid argument. Last argument must be a callback function. Value: `%s`.","CY":"invalid option. `%s` option must be an array of package names. Option: `%s`.","CZ":"invalid argument. Version argument must be a string. Value: `%s`.","Ca":"invalid argument. Must provide either a string or a Buffer. Value: `%s`.","Cb":"invalid argument. Must provide either a string or Buffer. Value: `%s`.","Cc":"invalid argument. First argument must be either a string or array of strings. Value: `%s`.","Cd":"invalid option. `%s` option must be an object. Option: `%s`.","Ce":"unexpected error. File does not exist. Unable to resolve file: %s.","Cf":"invalid argument. Must provide either a string or an array of strings. Value: `%s`.","Cg":"invalid argument. Must provide either a string or an array of strings. Value: `%s`. Index: `%u`.","Ch":"unexpected error. Failed to sort packages. Detected the following dependency chain containing a cycle: `%s`.","Ci":"invalid node. Equation comments must have a valid label. Node: `%s`.","Cj":"invalid node. Equation comments must have valid alternate text. Node: `%s`.","Ck":"invalid node. Equation comments must have valid raw equation text. Node: `%s`.","Cl":"invalid node. Invalid equation comment. Ensure that the Markdown file includes both starting and ending equation comments. Node: `%s`.","Cm":"invalid node. Equation element must have a valid label. Node: `%s`.","Cn":"unexpected error. Code block configuration settings should be provided as comma-separated `key:value` pairs (e.g., `foo:true, bar:\"string\", baz:[\"error\",2]`). Value: `%s`.","Co":"unexpected error. Code block configuration values should be parseable as JSON. Value: `%s`.","Cp":"unexpected error. Encountered an error when executing code block. File: `%s`. Message: `%s`.","Cq":"unexpected error. Expected code block to throw an exception. File: `%s`.","Cr":"invalid node. Ensure that the Markdown file includes both a starting `
` and closing `
\\n\\n`. Node: `%s`.","Cs":"invalid node. Equation comments must have valid equation text. Node: `%s`.","Ct":"invalid node. Equation comments must have valid labels. Node: `%s`.","Cu":"invalid option. `%s` option must begin with \"@stdlib/\". Option: `%s`.","Cv":"invalid argument. First argument must be a list of file paths. Value: `%s`.","Cw":"invalid arguments. Subpopulation size must be less than or equal to the population size.","Cx":"invalid arguments. Number of draws must be less than or equal to the population size.","Cy":"invalid arguments. Fourth argument is not compatible with the number of input and output ndarrays.","Cz":"invalid arguments. Input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","D0":"invalid arguments. Length of the first argument is incompatible with the second and third arguments.","D1":"invalid argument. Provided collections must have the same length.","D2":"invalid argument. First argument must be an array-like object containing nonnegative integers.","D3":"invalid arguments. Input arrays must have the same length.","D4":"invalid argument. Must provide valid indices (i.e., must be a nonnegative integer less than or equal to the tuple length).","D5":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented. https://github.com/stdlib-js/stdlib/issues/new/choose","D6":"invalid operation. Parser is unable to parse new chunks, as the parser has been closed. To parse new chunks, create a new parser instance.","D7":"invalid operation. Parser is in an unrecoverable error state. To parse new chunks, create a new parser instance.","D8":"invalid argument. First argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","D9":"invalid argument. Second argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","DA":"invalid argument. First argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DB":"invalid argument. Second argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DC":"invalid assignment. `%s` size is less than the number of data elements. Number of elements: `%u`. Value: `%u`.","DD":"invalid assignment. `%s` must be a string or an array of strings. Value: `%s`.","DE":"invalid assignment. `%s` must be a number or an array of numbers. Value: `%s`.","DF":"invalid assignment. `%s` must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","DG":"invalid assignment. `%s` must be a finite number, Date, or null. Value: `%s`.","DH":"invalid assignment. `%s` must be a boolean or an array of booleans. Value: `%s`.","DI":"invalid assignment. `%s` must be a number or null. Value: `%s`.","DJ":"invalid assignment. `%s` must be an array of strings or an empty array. Value: `%s`.","DK":"invalid state. x and y are different lengths. x length: `%u`. y length: `%u`.","DL":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[%u].length: `%u`.","DM":"invalid assignment. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","DN":"invalid assignment. `%s` must be null or an array. Value: `%s`.","DO":"invalid arguments. Must provide equal length array-like objects. x length: `%u`. y length: `%u`.","DP":"invalid argument. The number of comparisons must be greater or equal to the number of p-values to be adjusted. Value: `%u`.","DQ":"invalid argument. Second argument must be one of the following: \"%s\". Value: `%s`.","DR":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%s`.","DS":"invalid argument. First argument must contain nonnegative integers. Indices: (%s). Value: `%s`.","DT":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Number of input array dimensions: %u.","DU":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Value: `%s`.","DV":"invalid arguments. Minimum support must be less than maximum support. Value: `(%f, %f)`.","DW":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `(%d, %d)`.","DX":"invalid argument. Mean parameter must be a positive number. Value: `%s`.","DY":"invalid argument. Mean parameter must be a probability. Value: `%s`.","DZ":"invalid option. `%s` option must be on the interval: [0, 1]. Option: `%f`.","Da":"invalid argument. Must provide a nonnegative number on the interval: [0, 1]. Value: `%f`.","Db":"invalid argument. First argument must either specify the order of the covariance matrix or be a square two-dimensional ndarray for storing the covariance matrix. Value: `%s`.","Dc":"invalid argument. Second argument must be a one-dimensional ndarray. Value: `%s`.","Dd":"invalid argument. Must provide a one-dimensional ndarray. Value: `%s`.","De":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square two-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","Df":"invalid argument. First argument must either specify the order of the correlation matrix or be a square two-dimensional ndarray for storing the correlation matrix. Value: `%s`.","Dg":"invalid argument. Input array must be an array-like object. Value: `%s`.","Dh":"invalid argument. Output array must be an array-like object. Value: `%s`.","Di":"invalid argument. Mask array offset must be a nonnegative integer. Value: `%s`.","Dj":"invalid argument. Must provide recognized data types. Unable to resolve a data type string. Value: `%s`.","Dk":"invalid option. `%s` option must be one of the following: ['%s']. Option: `%s`.","Dl":"invalid argument. Database already contains an entry for the provided URI. Value: `%s`.","Dm":"invalid argument. Database already contains an entry for the provided id. Value: `%s`.","Dn":"invalid argument. First argument must be an array of objects. Value: `%s`.","Do":"unexpected error. File does not exist. Unable to resolve file: `%s`.","Dp":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`.","Dq":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`. Index: `%u`.","Dr":"invalid argument. Must provide either an options object or a function. Value: `%s`.","Ds":"invalid option. `%s` option must be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","Dt":"invalid argument. Fourth argument must contain a single element equal to 0. Value: `%d`.","Du":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%s`.","Dv":"invalid argument. Must provide an ndarray. Value: `%s`.","Dw":"invalid argument. Second argument must be a supported data type policy. Value: `%s`.","Dx":"invalid argument. Must provide either an integer or a Date object. Value: `%s`.","Dy":"invalid argument. Must provide a valid duration string. Value: `%s`.","Dz":"invalid argument. Day number must be on the interval: [1, %u]. Value: `%d`.","E0":"invalid argument. First argument must be a string or integer. Value: `%s`.","E1":"invalid option. `%s` option must be one of the following: \"%s\". Value: `%s`.","E2":"invalid argument. Third argument must be either an integer (starting index) or a function. Value: `%s`.","E3":"invalid argument. Fourth argument must be either an integer (ending index) or a function. Value: `%s`.","E4":"invalid argument. Second argument must be a valid position (i.e., be within string bounds). Value: `%d`.","E5":"invalid argument. Must provide a valid code point (i.e., cannot exceed %u). Value: `%s`.","E6":"invalid argument. First argument must be astring. Value: `%s`.","E7":"invalid argument. Second argument must be either an integer (starting index) or a function. Value: `%s`.","E8":"invalid argument. Third argument must be either an integer (ending index) or a function. Value: `%s`.","E9":"invalid argument. ArrayBuffer byte length must be a multiple of %u. Byte length: `%u`.","EA":"invalid argument. Byte offset must be a multiple of %u. Value: `%u`.","EB":"invalid argument. First argument must have a length which is a multiple of %u. Length: `%u`.","EC":"invalid argument. Second argument must be a supported data type. Value: `%s`.","ED":"invalid argument. First argument must be one of the following data types: \"%s\". Value: `%s`.","EE":"invalid argument. Second argument must be either an integer (starting view index) or a function. Value: `%s`.","EF":"invalid argument. Third argument must be either an integer (ending view index) or a function. Value: `%s`.","EG":"invalid option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","EH":"invalid option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","EI":"invalid argument. Second argument must be either a scalar or an ndarray-like object. Value: `%s`.","EJ":"invalid argument. Minimum support must be less than maximum support. Value: `[%f, %f]`.","EK":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d, %d]`.","EL":"invalid %s. `state` array has an incompatible schema version. Expected: `%s`. Actual: `%s.`","EM":"invalid %s. `state` array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","EN":"invalid argument. Number of draws must be less than or equal to the population size. Value: `%u`.","EO":"invalid argument. Subpopulation size must be less than or equal to the population size. Value: `%u`.","EP":"invalid argument. Must provide a regular expression. Value: `%s`.","EQ":"invalid argument. Second argument must be an object containing property descriptors. Value: `%s`.","ER":"invalid argument. Must provide an object (except null). Value: `%s`.","ES":"invalid argument. First argument must be an object (except null). Value: `%s`.","ET":"unexpected error. Encountered an invalid record. Field %d on line %d contains a closing quote which is not immediately followed by a delimiter or newline.","EU":"unexpected error. Encountered an invalid record. Field %d on line %d contains an opening quote which does not immediately follow a delimiter or newline.","EV":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence which is not immediately followed by a special character sequence.","EW":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence within a quoted field which is not immediately followed by a quote sequence.","EX":"invalid argument. First argument must be a function having at least one parameter. Value: `%s`.","EY":"invalid argument. All arguments must be objects. Index: `%u`. Value: `%s`.","EZ":"invalid argument. First argument must be a non-null object. Value: `%s`.","Ea":"invalid argument. First argument must be an ndarray whose last dimension is of size %u. Actual size: `%u`.","Eb":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of eta * lambda. Value: `%f`.","Ec":"invalid argument. Output argument must be a one-dimensional ndarray. Value: `%s`.","Ed":"invalid argument. Must provide a two-dimensional ndarray. Value: `%s`.","Ee":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u`. Actual: `%u`.","Ef":"invalid argument. First argument must be an integer, null, or undefined. Value: `%s`.","Eg":"invalid argument. Second argument must be an integer, null, or undefined. Value: `%s`.","Eh":"invalid argument. Third argument must be an integer, null, or undefined. Value: `%s`.","Ei":"invalid argument. Third argument cannot be zero. Value: `%s`.","Ej":"invalid argument. First argument must be a valid subsequence string. Value: `%s`.","Ek":"invalid argument. A subsequence string must have a non-zero increment. Value: `%s`.","El":"invalid argument. The subsequence string resolves to a slice which exceeds index bounds. Value: `%s`.","Em":"invalid argument. Provided arguments must be either a Slice, integer, null, or undefined. Argument: `%d`. Value: `%s`.","En":"invalid operation. Unsupported slice operation. Value: `%s`.","Eo":"invalid operation. Number of array dimensions does not match the number of slice dimensions. Array shape: (%s). Slice dimensions: %u.","Ep":"invalid operation. Slice exceeds array bounds. Array shape: (%s).","Eq":"invalid operation. A subsequence increment must be a non-zero integer. Value: `%s`.","Er":"invalid operation. A subsequence may only include a single ellipsis. Value: `%s`.","Es":"invalid argument. Cannot write to a read-only array.","Et":"invalid argument. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Eu":"invalid argument. Slice arguments must be either a Slice, integer, null, or undefined. Value: `%s`.","Ev":"invalid operation. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Ew":"invalid operation. Assigned value cannot be safely cast to the target array data type. Data types: [%s, %s].","Ex":"invalid operation. Unsupported target array data type. Data type: `%s`.","Ey":"invalid argument. Index must be on the interval: [0, %d]. Value: `%d`.","Ez":"invalid argument. Slice exceeds array bounds. Array shape: (%s).","F0":"invalid argument. Input array values cannot be safely cast to the output array data type. Data types: [%s, %s].","F1":"invalid argument. Second argument must be an ndarray. Value: `%s`.","F2":"invalid argument. First argument must be an ndarray having at least two dimensions.","F3":"invalid argument. Second argument must be an array of nonnegative integers. Value: `%s`.","F4":"invalid option. Cannot write to read-only array.","F5":"invalid argument. First argument must be an array of nonnegative integers. Value: `%s`.","F6":"invalid argument. Must provide an ndarray having a supported data type. Value: `%s`.","F7":"invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.","F8":"invalid argument. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","F9":"invalid argument. Third argument must be either a Slice, integer, null, or undefined. Value: `%s`.","FA":"invalid argument. First argument must be an ndarray having at least three dimensions.","FB":"invalid argument. Index must resolve to a value on the interval: [0, %d]. Value: `%d`.","FC":"invalid argument. First argument must be a recognized index mode. Value: `%s`.","FD":"invalid argument. Third argument exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","FE":"invalid argument. Number of indices does not match the number of array dimensions. Array shape: (%s). Number of indices: %u.","FF":"invalid argument. Each index argument must be either an integer, null, or undefined. Value: `%s`.","FG":"invalid argument. First argument must be a complex number. Value: `%s`.","FH":"invalid arguments. Input arrays must be broadcast compatible.","FI":"invalid argument. The first and second arguments must have the same length.","FJ":"invalid argument. First argument must be either an ndarray or an array of ndarrays. Value: `%s`.","FK":"invalid argument. An ndarray argument must be an ndarray. Value: `%s`.","FL":"invalid argument. Second argument must be a valid property name. Value: `%s`.","FM":"invalid argument. First argument must have a `%s` method.","FN":"invalid argument. Second argument must an array of strings. Value: `%s`.","FO":"invalid argument. Third argument must be a supported data type. Value: `%s`.","FP":"invalid argument. Index argument is out-of-bounds. Value: `%s`.","FQ":"invalid argument. Second argument must be a complex number. Value: `%s`.","FR":"invalid argument. Index arguments must be integers. Value: `%s`.","FS":"invalid argument. Slice exceeds array bounds. Array length: %d.","FT":"invalid argument. Input array and the output array slice are broadcast incompatible. Array length: %u. Desired length: %u.","FU":"invalid operation. Slice exceeds array bounds.","FV":"invalid argument. First argument must be a valid index array.","FW":"invalid operation. This array index instance has already been freed and can no longer be used.","FX":"invalid argument. First argument must be a complex-valued floating-point array. Value: `%s`.","FY":"invalid operation. Index exceeds array bounds.","FZ":"invalid operation. Unrecognized array index type. Value: `%s`.","Fa":"invalid operation. Unable to resolve array index. Value: `%s`.","Fb":"invalid option. `%s` option is missing a `%s` method. Option: `%s`.","Fc":"invalid operation. If not provided an initial value, an array must contain at least one element.","Fd":"invalid arguments. Must provide equal length array-like objects.","Fe":"Index out of bounds","Ff":"invalid option. `%s` option must be less than or equal to 64. Option: `%u`.","Fg":"invalid argument. Unable to parse input string as a complex number. Value: `%s`.","Fh":"invalid operation. Cannot access settings for a REPL which has already closed.","Fi":"invalid argument. First argument must be a recognized setting. Value: `%s`.","Fj":"invalid invocation. `this` is not a boolean array.","Fk":"invalid argument. Unable to parse commits for package: `%s`.","Fl":"invalid argument. Unrecognized release type: `%s`.","Fm":"invalid argument. First argument must be a supported BLAS memory layout. Value: `%s`.","Fn":"invalid argument. First argument must be an existing theme name. Value: `%s`.","Fo":"invalid argument. First argument must not be the default theme name. Value: `%s`.","Fp":"invalid argument. Second argument must be an object. Value: `%s`.","Fq":"invalid arguments. Number of values does not equal the number of falsy values in the mask array.","Fr":"invalid arguments. Insufficient values to satisfy mask array.","Fs":"invalid arguments. Input arguments are not broadcast compatible.","Ft":"invalid arguments. Number of values does not equal the number of truthy values in the mask array.","Fu":"invalid argument. Third argument cannot be safely cast to the input array data type. Data types: [%s, %s].","Fv":"invalid argument. First argument must be a boolean. Value: `%s`.","Fw":"invalid argument. The third argument must be broadcast compatible with the second argument. Array shape: (%d). Desired shape: (%d).","Fx":"invalid argument. First argument must be a valid order. Value: `%s`.","Fy":"invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","Fz":"invalid argument. Third argument must be a nonnegative integer. Value: `%d`.","G0":"invalid argument. Eighth argument must be non-zero. Value: `%d`.","G1":"invalid argument. Twelfth argument must be non-zero. Value: `%d`.","G2":"invalid argument. Seventh argument must be non-zero. Value: `%d`.","G3":"invalid argument. Tenth argument must be non-zero. Value: `%d`.","G4":"invalid argument. Fourth argument must be greater than or equal to max(1,%d). Value: `%d`.","G5":"invalid argument. First argument must be a string or an array of strings. Value: `%s`.","G6":"invalid option. `%s` option must be a valid mode. Option: `%s`.","G7":"invalid argument. First argument must be a nonnegative integer. Value: `%d`.","G8":"invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.","G9":"invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.","GA":"invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GB":"invalid argument. Sixth argument must be non-zero. Value: `%d`.","GC":"invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.","GD":"invalid argument. First argument must specify whether the reference the lower or upper triangular matrix. Value: `%s`.","GE":"invalid argument. Second argument must be a nonnegative integer. Value: `%d`.","GF":"invalid argument. Fifth argument must be non-zero. Value: `%d`.","GG":"invalid argument. Second argument must be a valid transpose operation. Value: `%s`.","GH":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.","GI":"invalid argument. Ninth argument must be non-zero.","GJ":"invalid argument. Twelfth argument must be non-zero.","GK":"invalid argument. Eleventh argument must be non-zero.","GL":"invalid argument. Fifteenth argument must be non-zero.","GM":"invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.","GN":"invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GO":"invalid argument. Third argument must be a valid transpose operation. Value: `%s`.","GP":"invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.","GQ":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%d`.","GR":"invalid argument. Seventh argument must be greater than or equal to max(1,%d). Value: `%d`.","GS":"invalid argument. Ninth argument must be non-zero. Value: `%d`.","GT":"invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","GU":"invalid argument. Third argument must be a valid diagonal type. Value: `%s`.","GV":"invalid argument. First argument must be a valid transpose operation. Value: `%s`.","GW":"invalid argument. Tenth argument must be non-zero.","GX":"invalid argument. Fourteenth argument must be non-zero.","GY":"invalid arguments. Array must have the same shape.","GZ":"invalid argument. Second argument must be an array of integers. Value: `%s`.","Ga":"invalid argument. First argument must be an ndarray having at least %d dimensions.","Gb":"invalid argument. Dimension indices must be sorted in ascending order. Value: `%s`.","Gc":"invalid argument. Dimension indices must be unique. Value: `%s`.","Gd":"invalid argument. First argument must be an array of ndarrays. Value: `%s`.","Ge":"invalid argument. First argument must be an array of ndarrays which are broadcast-compatible. Value: `%s`.","Gf":"invalid argument. First argument must be an array of ndarrays having at least %d dimensions after broadcasting.","Gg":"invalid argument. Index argument is out-of-bounds. Value: `%d`.","Gh":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%d`.","Gi":"invalid argument. Ninth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gj":"invalid argument. Eleventh argument must be greater than or equal to max(1,%d). Value: `%d`.","Gk":"invalid argument. Fourteenth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gl":"invalid argument. First argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gm":"invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gn":"invalid argument. First argument must have at least one dimension.","Go":"invalid argument. Second argument must have at least one dimension.","Gp":"invalid argument. Third argument must be a negative integer. Value: `%s`.","Gq":"invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.","Gr":"invalid argument. The size of the contracted dimension must be the same for both input ndarrays. Dim(%s,%d) = %d. Dim(%s,%d) = %d.","Gs":"invalid arguments. Input ndarrays must be broadcast compatible. Shape(%s) = (%s). Shape(%s) = (%s).","Gt":"invalid argument. Cannot write to read-only array.","Gu":"invalid arguments. The first and second arguments must have the same shape.","Gv":"unexpected error. Environment does not support WebAssembly.","Gw":"invalid invocation. Unable to perform write operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gx":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Resize the underlying memory instance in order to accommodate the list of provided values.","Gy":"invalid invocation. Unable to perform read operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gz":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Not enough values to fill the provided output array.","H0":"invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.","H1":"invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H2":"invalid argument. Second argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H3":"invalid invocation. `this` is not a Float64ArrayFE.","H4":"invalid argument. First argument must be a supported byte order. Value: `%s`.","H5":"invalid argument. Second argument must a data type. Value: `%s`.","H6":"invalid argument. First argument must be an ndarray-like object having a supported data type. Value: `%s`.","H7":"invalid argument. Second argument must be an ndarray-like object having a supported data type. Value: `%s`.","H8":"invalid invocation. `this` is not %s %s.","H9":"invalid argument. First argument must be a supported data type. Value: `%s`.","HA":"invalid argument. Must provide an ArrayBuffer. Value: `%s`.","HB":"invalid argument. Second argument must be a data type. Value: `%s`.","HC":"invalid option. Each key object must have a `name` property. Value: `%s`.","HD":"invalid option. Each key object's `name` property must be a string. Value: `%s`.","HE":"invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","HF":"invalid option. Each action must be an array of objects. Value: `%s`.","HG":"invalid argument. First argument must be a valid index ndarray.","HH":"invalid operation. This ndarray index instance has already been freed and can no longer be used.","HI":"invalid operation. Unrecognized ndarray index type. Value: `%s`.","HJ":"invalid operation. Index exceeds ndarray bounds.","HK":"invalid operation. Number of indices does not match the number of array dimensions. Array shape: (%s). Index dimensions: %u.","HL":"invalid operation. Unable to resolve ndarray index. Value: `%s`.","HM":"invalid argument. First argument is not compatible with the specified index \"kind\". Type: %s. Kind: %s.","HN":"invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.","HO":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.","HP":"invalid argument. Must provide unique dimension indices. Value: `[%s]`.","HQ":"invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.","HR":"invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.","HS":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","HT":"invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`","HU":"invalid argument. First argument must be a valid action name. Value: `%s`.","HV":"invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`"} diff --git a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv index bbb9f63bc193..ae482a5b192e 100644 --- a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv @@ -138,6 +138,36 @@ "237",@stdlib/constants-float32-max-base10-exponent "238",@stdlib/constants/float32/min-base10-exponent-subnormal "239",@stdlib/constants-float32-min-base10-exponent-subnormal +"240",@stdlib/array/base/broadcasted-ternary5d +"241",@stdlib/array-base-broadcasted-ternary5d +"242",@stdlib/array/base/mskbinary4d +"243",@stdlib/array-base-mskbinary4d +"244",@stdlib/array/base/mskbinary5d +"245",@stdlib/array-base-mskbinary5d +"246",@stdlib/array/base/mskunary4d +"247",@stdlib/array-base-mskunary4d +"248",@stdlib/array/base/mskunary5d +"249",@stdlib/array-base-mskunary5d +"250",@stdlib/ndarray/index +"251",@stdlib/ndarray-index +"252",@stdlib/ndarray/map +"253",@stdlib/ndarray-map +"254",@stdlib/ndarray/reject +"255",@stdlib/ndarray-reject +"256",@stdlib/ndarray/to-fancy +"257",@stdlib/ndarray-to-fancy +"258",@stdlib/ndarray/to-json +"259",@stdlib/ndarray-to-json +"260",@stdlib/ndarray/base/spread-dimensions +"261",@stdlib/ndarray-base-spread-dimensions +"262",@stdlib/ndarray/base/to-normalized-indices +"263",@stdlib/ndarray-base-to-normalized-indices +"264",@stdlib/ndarray/base/to-unique-normalized-indices +"265",@stdlib/ndarray-base-to-unique-normalized-indices +"266",@stdlib/blas/base/zdscal +"267",@stdlib/blas-base-zdscal +"268",@stdlib/lapack/base/zlacgv +"269",@stdlib/lapack-base-zlacgv "1Yi",@stdlib/array/base/accessor-getter "1Yj",@stdlib/array-base-accessor-getter "1Yk",@stdlib/array/base/accessor-setter @@ -198,6 +228,8 @@ "1rB",@stdlib/array-base-assert-is-same-kind-data-type-cast "1rC",@stdlib/array/base/assert/is-signed-integer-data-type "1rD",@stdlib/array-base-assert-is-signed-integer-data-type +"25a",@stdlib/array/base/assert/is-sorted-ascending +"25b",@stdlib/array-base-assert-is-sorted-ascending "1rE",@stdlib/array/base/assert/is-unsigned-integer-data-type "1rF",@stdlib/array-base-assert-is-unsigned-integer-data-type "1Yu",@stdlib/array/base/assert @@ -248,10 +280,22 @@ "1iH",@stdlib/array-base-broadcasted-binary5d "1ke",@stdlib/array/base/broadcasted-quaternary2d "1kf",@stdlib/array-base-broadcasted-quaternary2d +"23o",@stdlib/array/base/broadcasted-quaternary3d +"23p",@stdlib/array-base-broadcasted-quaternary3d +"23q",@stdlib/array/base/broadcasted-quaternary4d +"23r",@stdlib/array-base-broadcasted-quaternary4d +"23s",@stdlib/array/base/broadcasted-quaternary5d +"23t",@stdlib/array-base-broadcasted-quaternary5d "1kg",@stdlib/array/base/broadcasted-quinary2d "1kh",@stdlib/array-base-broadcasted-quinary2d +"23u",@stdlib/array/base/broadcasted-quinary4d +"23v",@stdlib/array-base-broadcasted-quinary4d "1ki",@stdlib/array/base/broadcasted-ternary2d "1kj",@stdlib/array-base-broadcasted-ternary2d +"23w",@stdlib/array/base/broadcasted-ternary3d +"23x",@stdlib/array-base-broadcasted-ternary3d +"23y",@stdlib/array/base/broadcasted-ternary4d +"23z",@stdlib/array-base-broadcasted-ternary4d "1iI",@stdlib/array/base/broadcasted-unary2d "1iJ",@stdlib/array-base-broadcasted-unary2d "1iK",@stdlib/array/base/broadcasted-unary3d @@ -316,6 +360,8 @@ "1rH",@stdlib/array-base-fancy-slice-assign "1rI",@stdlib/array/base/fancy-slice "1rJ",@stdlib/array-base-fancy-slice +"25c",@stdlib/array/base/fill +"25d",@stdlib/array-base-fill "004",@stdlib/array/base/filled-by "005",@stdlib/array-base-filled-by "006",@stdlib/array/base/filled @@ -400,6 +446,8 @@ "009",@stdlib/array-base-incrspace "1mo",@stdlib/array/base/index-of "1mp",@stdlib/array-base-index-of +"25e",@stdlib/array/base/indices-complement +"25f",@stdlib/array-base-indices-complement "1t0",@stdlib/array/base/join "1t1",@stdlib/array-base-join "1mq",@stdlib/array/base/last-index-of @@ -430,6 +478,10 @@ "1uN",@stdlib/array-base-mskfilter-map "1oq",@stdlib/array/base/mskfilter "1or",@stdlib/array-base-mskfilter +"25g",@stdlib/array/base/mskfilter2 +"25h",@stdlib/array-base-mskfilter2 +"25i",@stdlib/array/base/mskfiltern +"25j",@stdlib/array-base-mskfiltern "1wE",@stdlib/array/base/mskput "1wF",@stdlib/array-base-mskput "1uO",@stdlib/array/base/mskreject-map @@ -494,6 +546,10 @@ "1oz",@stdlib/array-base-resolve-setter "1p0",@stdlib/array/base/reverse "1p1",@stdlib/array-base-reverse +"25k",@stdlib/array/base/scatter-filled +"25l",@stdlib/array-base-scatter-filled +"25m",@stdlib/array/base/scattered +"25n",@stdlib/array-base-scattered "1ZW",@stdlib/array/base/setter "1ZX",@stdlib/array-base-setter "1ms",@stdlib/array/base/slice @@ -508,6 +564,8 @@ "1kv",@stdlib/array-base-strided2array5d "1ly",@stdlib/array/base/take-indexed "1lz",@stdlib/array-base-take-indexed +"25o",@stdlib/array/base/take-indexed2 +"25p",@stdlib/array-base-take-indexed2 "1t2",@stdlib/array/base/take-map "1t3",@stdlib/array-base-take-map "1ZY",@stdlib/array/base/take @@ -534,10 +592,16 @@ "1ih",@stdlib/array-base-unary2d-by "1hq",@stdlib/array/base/unary2d "1hr",@stdlib/array-base-unary2d +"24A",@stdlib/array/base/unary3d-by +"24B",@stdlib/array-base-unary3d-by "1iS",@stdlib/array/base/unary3d "1iT",@stdlib/array-base-unary3d +"24C",@stdlib/array/base/unary4d-by +"24D",@stdlib/array-base-unary4d-by "1iU",@stdlib/array/base/unary4d "1iV",@stdlib/array-base-unary4d +"24E",@stdlib/array/base/unary5d-by +"24F",@stdlib/array-base-unary5d-by "1iW",@stdlib/array/base/unary5d "1iX",@stdlib/array-base-unary5d "1iY",@stdlib/array/base/unarynd @@ -2061,6 +2125,12 @@ "1tB",@stdlib/constants-float32-fourth-pi "1tC",@stdlib/constants/float32/half-pi "1tD",@stdlib/constants-float32-half-pi +"24G",@stdlib/constants/float32/ln-half +"24H",@stdlib/constants-float32-ln-half +"24I",@stdlib/constants/float32/ln-pi +"24J",@stdlib/constants-float32-ln-pi +"24K",@stdlib/constants/float32/ln-ten +"24L",@stdlib/constants-float32-ln-ten "1zC",@stdlib/constants/float32/max-base2-exponent-subnormal "1zD",@stdlib/constants-float32-max-base2-exponent-subnormal "1zE",@stdlib/constants/float32/max-base2-exponent @@ -2069,6 +2139,8 @@ "21l",@stdlib/constants-float32-max-safe-fibonacci "0I0",@stdlib/constants/float32/max-safe-integer "0I1",@stdlib/constants-float32-max-safe-integer +"24M",@stdlib/constants/float32/max-safe-nth-lucas +"24N",@stdlib/constants-float32-max-safe-nth-lucas "0I2",@stdlib/constants/float32/max "0I3",@stdlib/constants-float32-max "23A",@stdlib/constants/float32/min-base10-exponent @@ -2105,6 +2177,20 @@ "0IJ",@stdlib/constants-float32-smallest-subnormal "0IK",@stdlib/constants/float32/sqrt-eps "0IL",@stdlib/constants-float32-sqrt-eps +"24O",@stdlib/constants/float32/sqrt-half-pi +"24P",@stdlib/constants-float32-sqrt-half-pi +"24Q",@stdlib/constants/float32/sqrt-half +"24R",@stdlib/constants-float32-sqrt-half +"24S",@stdlib/constants/float32/sqrt-phi +"24T",@stdlib/constants-float32-sqrt-phi +"24U",@stdlib/constants/float32/sqrt-pi +"24V",@stdlib/constants-float32-sqrt-pi +"24W",@stdlib/constants/float32/sqrt-three +"24X",@stdlib/constants-float32-sqrt-three +"24Y",@stdlib/constants/float32/sqrt-two-pi +"24Z",@stdlib/constants-float32-sqrt-two-pi +"24a",@stdlib/constants/float32/sqrt-two +"24b",@stdlib/constants-float32-sqrt-two "1tG",@stdlib/constants/float32/two-pi "1tH",@stdlib/constants-float32-two-pi "0IM",@stdlib/constants/float64/apery @@ -2181,6 +2267,8 @@ "0JN",@stdlib/constants-float64-max-safe-nth-fibonacci "0JO",@stdlib/constants/float64/max-safe-nth-lucas "0JP",@stdlib/constants-float64-max-safe-nth-lucas +"24c",@stdlib/constants/float64/max-safe-nth-tribonacci +"24d",@stdlib/constants-float64-max-safe-nth-tribonacci "0JQ",@stdlib/constants/float64/max "0JR",@stdlib/constants-float64-max "0JS",@stdlib/constants/float64/min-base10-exponent-subnormal @@ -2659,6 +2747,10 @@ "1zP",@stdlib/lapack-base-slaswp "1yw",@stdlib/lapack/base/spttrf "1yx",@stdlib/lapack-base-spttrf +"26A",@stdlib/lapack/base/zlacpy +"26B",@stdlib/lapack-base-zlacpy +"26C",@stdlib/lapack/base/zrot +"26D",@stdlib/lapack-base-zrot "1xl",@stdlib/lapack "0QE",@stdlib/math/base/assert/int32-is-even "0QF",@stdlib/math-base-assert-int32-is-even @@ -2708,6 +2800,8 @@ "0Ql",@stdlib/math-base-assert-is-nonpositive-integer "0Qm",@stdlib/math/base/assert/is-odd "0Qn",@stdlib/math-base-assert-is-odd +"24e",@stdlib/math/base/assert/is-oddf +"24f",@stdlib/math-base-assert-is-oddf "1b2",@stdlib/math/base/assert/is-positive-finite "1b3",@stdlib/math-base-assert-is-positive-finite "0Qo",@stdlib/math/base/assert/is-positive-integer @@ -2720,6 +2814,8 @@ "0Qv",@stdlib/math-base-assert-is-prime "0Qw",@stdlib/math/base/assert/is-probability "0Qx",@stdlib/math-base-assert-is-probability +"25q",@stdlib/math/base/assert/is-probabilityf +"25r",@stdlib/math-base-assert-is-probabilityf "0Qy",@stdlib/math/base/assert/is-safe-integer "0Qz",@stdlib/math-base-assert-is-safe-integer "0R0",@stdlib/math/base/assert @@ -3014,6 +3110,8 @@ "0UX",@stdlib/math-base-special-digamma "0UY",@stdlib/math/base/special/dirac-delta "0UZ",@stdlib/math-base-special-dirac-delta +"25s",@stdlib/math/base/special/dirac-deltaf +"25t",@stdlib/math-base-special-dirac-deltaf "0Ua",@stdlib/math/base/special/dirichlet-eta "0Ub",@stdlib/math-base-special-dirichlet-eta "0Uc",@stdlib/math/base/special/ellipe @@ -3142,6 +3240,8 @@ "0WN",@stdlib/math-base-special-haversin "0WO",@stdlib/math/base/special/heaviside "0WP",@stdlib/math-base-special-heaviside +"26E",@stdlib/math/base/special/heavisidef +"26F",@stdlib/math-base-special-heavisidef "0WQ",@stdlib/math/base/special/hypot "0WR",@stdlib/math-base-special-hypot "0WS",@stdlib/math/base/special/hypotf @@ -3174,6 +3274,8 @@ "0Wr",@stdlib/math-base-special-labs "0Ws",@stdlib/math/base/special/lcm "0Wt",@stdlib/math-base-special-lcm +"24g",@stdlib/math/base/special/lcmf +"24h",@stdlib/math-base-special-lcmf "0Wu",@stdlib/math/base/special/ldexp "0Wv",@stdlib/math-base-special-ldexp "20S",@stdlib/math/base/special/ldexpf @@ -3250,8 +3352,12 @@ "0XV",@stdlib/math-base-special-negafibonacci "0XW",@stdlib/math/base/special/negalucas "0XX",@stdlib/math-base-special-negalucas +"24i",@stdlib/math/base/special/negalucasf +"24j",@stdlib/math-base-special-negalucasf "0XY",@stdlib/math/base/special/nonfibonacci "0XZ",@stdlib/math-base-special-nonfibonacci +"24k",@stdlib/math/base/special/nonfibonaccif +"24l",@stdlib/math-base-special-nonfibonaccif "0Xa",@stdlib/math/base/special "0Xb",@stdlib/math-base-special "0Xc",@stdlib/math/base/special/pdiff @@ -3332,6 +3438,8 @@ "0Yd",@stdlib/math-base-special-sqrtf "1bS",@stdlib/math/base/special/sqrtpi "1bT",@stdlib/math-base-special-sqrtpi +"24m",@stdlib/math/base/special/sqrtpif +"24n",@stdlib/math-base-special-sqrtpif "0Ye",@stdlib/math/base/special/tan "0Yf",@stdlib/math-base-special-tan "1tu",@stdlib/math/base/special/tand @@ -4010,6 +4118,8 @@ "0hb",@stdlib/ndarray-base-assert-is-casting-mode "0hc",@stdlib/ndarray/base/assert/is-column-major-contiguous "0hd",@stdlib/ndarray-base-assert-is-column-major-contiguous +"25u",@stdlib/ndarray/base/assert/is-column-major-string +"25v",@stdlib/ndarray-base-assert-is-column-major-string "0he",@stdlib/ndarray/base/assert/is-column-major "0hf",@stdlib/ndarray-base-assert-is-column-major "1ci",@stdlib/ndarray/base/assert/is-complex-floating-point-data-type @@ -4038,6 +4148,8 @@ "1ct",@stdlib/ndarray-base-assert-is-real-floating-point-data-type "0hq",@stdlib/ndarray/base/assert/is-row-major-contiguous "0hr",@stdlib/ndarray-base-assert-is-row-major-contiguous +"25w",@stdlib/ndarray/base/assert/is-row-major-string +"25x",@stdlib/ndarray-base-assert-is-row-major-string "0hs",@stdlib/ndarray/base/assert/is-row-major "0ht",@stdlib/ndarray-base-assert-is-row-major "0hu",@stdlib/ndarray/base/assert/is-safe-data-type-cast @@ -4120,6 +4232,8 @@ "1l7",@stdlib/ndarray-base-flipud "1yW",@stdlib/ndarray/base/for-each "1yX",@stdlib/ndarray-base-for-each +"24o",@stdlib/ndarray/base/from-scalar-like +"24p",@stdlib/ndarray-base-from-scalar-like "0ig",@stdlib/ndarray/base/from-scalar "0ih",@stdlib/ndarray-base-from-scalar "0ii",@stdlib/ndarray/base/function-object @@ -4140,6 +4254,10 @@ "1nZ",@stdlib/ndarray-base-maybe-broadcast-arrays "0iu",@stdlib/ndarray/base/meta-data-props "0iv",@stdlib/ndarray-base-meta-data-props +"24q",@stdlib/ndarray/base/min-signed-integer-dtype +"24r",@stdlib/ndarray-base-min-signed-integer-dtype +"24s",@stdlib/ndarray/base/min-unsigned-integer-dtype +"24t",@stdlib/ndarray-base-min-unsigned-integer-dtype "0iw",@stdlib/ndarray/base/min-view-buffer-index "0ix",@stdlib/ndarray-base-min-view-buffer-index "0iy",@stdlib/ndarray/base/minmax-view-buffer-index @@ -4166,6 +4284,8 @@ "0jD",@stdlib/ndarray-base-nonsingleton-dimensions "1l8",@stdlib/ndarray/base/normalize-index "1l9",@stdlib/ndarray-base-normalize-index +"25y",@stdlib/ndarray/base/normalize-indices +"25z",@stdlib/ndarray-base-normalize-indices "1d8",@stdlib/ndarray/base/nullary-loop-interchange-order "1d9",@stdlib/ndarray-base-nullary-loop-interchange-order "1dA",@stdlib/ndarray/base/nullary-tiling-block-size @@ -4234,6 +4354,8 @@ "0jZ",@stdlib/ndarray-base-to-array "0ja",@stdlib/ndarray/base/transpose "0jb",@stdlib/ndarray-base-transpose +"26G",@stdlib/ndarray/base/unary-accumulate +"26H",@stdlib/ndarray-base-unary-accumulate "1dM",@stdlib/ndarray/base/unary-by "1dN",@stdlib/ndarray-base-unary-by "1dO",@stdlib/ndarray/base/unary-loop-interchange-order @@ -4278,10 +4400,16 @@ "1db",@stdlib/ndarray-empty "1j6",@stdlib/ndarray/fancy "1j7",@stdlib/ndarray-fancy +"24u",@stdlib/ndarray/filter-map +"24v",@stdlib/ndarray-filter-map +"24w",@stdlib/ndarray/filter +"24x",@stdlib/ndarray-filter "1nw",@stdlib/ndarray/flag "1nx",@stdlib/ndarray-flag "1ny",@stdlib/ndarray/flags "1nz",@stdlib/ndarray-flags +"24y",@stdlib/ndarray/for-each +"24z",@stdlib/ndarray-for-each "0ju",@stdlib/ndarray/from-scalar "0jv",@stdlib/ndarray-from-scalar "0jw",@stdlib/ndarray/ind2sub @@ -5928,6 +6056,32 @@ "16v",@stdlib/stats-base-dists-pareto-type1-stdev "16w",@stdlib/stats/base/dists/pareto-type1/variance "16x",@stdlib/stats-base-dists-pareto-type1-variance +"25A",@stdlib/stats/base/dists/planck/cdf +"25B",@stdlib/stats-base-dists-planck-cdf +"25C",@stdlib/stats/base/dists/planck/entropy +"25D",@stdlib/stats-base-dists-planck-entropy +"25E",@stdlib/stats/base/dists/planck/kurtosis +"25F",@stdlib/stats-base-dists-planck-kurtosis +"25G",@stdlib/stats/base/dists/planck/logcdf +"25H",@stdlib/stats-base-dists-planck-logcdf +"25I",@stdlib/stats/base/dists/planck/logpmf +"25J",@stdlib/stats-base-dists-planck-logpmf +"25K",@stdlib/stats/base/dists/planck/mean +"25L",@stdlib/stats-base-dists-planck-mean +"25M",@stdlib/stats/base/dists/planck/median +"25N",@stdlib/stats-base-dists-planck-median +"25O",@stdlib/stats/base/dists/planck/mode +"25P",@stdlib/stats-base-dists-planck-mode +"25Q",@stdlib/stats/base/dists/planck/pmf +"25R",@stdlib/stats-base-dists-planck-pmf +"25S",@stdlib/stats/base/dists/planck/quantile +"25T",@stdlib/stats-base-dists-planck-quantile +"25U",@stdlib/stats/base/dists/planck/skewness +"25V",@stdlib/stats-base-dists-planck-skewness +"25W",@stdlib/stats/base/dists/planck/stdev +"25X",@stdlib/stats-base-dists-planck-stdev +"25Y",@stdlib/stats/base/dists/planck/variance +"25Z",@stdlib/stats-base-dists-planck-variance "16y",@stdlib/stats/base/dists/poisson/cdf "16z",@stdlib/stats-base-dists-poisson-cdf "17A",@stdlib/stats/base/dists/poisson/median @@ -6102,8 +6256,6 @@ "1A7",@stdlib/stats-base-dists-weibull-stdev "1A8",@stdlib/stats/base/dists/weibull/variance "1A9",@stdlib/stats-base-dists-weibull-variance -"1AA",@stdlib/stats/base/dmax -"1AB",@stdlib/stats-base-dmax "1AC",@stdlib/stats/base/dmaxabs "1AD",@stdlib/stats-base-dmaxabs "1AE",@stdlib/stats/base/dmaxabssorted @@ -6825,6 +6977,8 @@ "1Ln",@stdlib/stats-pcorrtest "1Lo",@stdlib/stats/ranks "1Lp",@stdlib/stats-ranks +"26I",@stdlib/stats/strided/dmax +"26J",@stdlib/stats-strided-dmax "1Lq",@stdlib/stats/ttest "1Lr",@stdlib/stats-ttest "1Ls",@stdlib/stats/ttest2 diff --git a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json index 1536270612b9..78cb786e864a 100644 --- a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json +++ b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv index 592c595120cc..0706abf26b0c 100644 --- a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv +++ b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv @@ -7876,3 +7876,159 @@ "@stdlib/math-base-special-nanminf",23l "@stdlib/math/base/special/sec",23m "@stdlib/math-base-special-sec",23n +"@stdlib/array/base/broadcasted-quaternary3d",23o +"@stdlib/array-base-broadcasted-quaternary3d",23p +"@stdlib/array/base/broadcasted-quaternary4d",23q +"@stdlib/array-base-broadcasted-quaternary4d",23r +"@stdlib/array/base/broadcasted-quaternary5d",23s +"@stdlib/array-base-broadcasted-quaternary5d",23t +"@stdlib/array/base/broadcasted-quinary4d",23u +"@stdlib/array-base-broadcasted-quinary4d",23v +"@stdlib/array/base/broadcasted-ternary3d",23w +"@stdlib/array-base-broadcasted-ternary3d",23x +"@stdlib/array/base/broadcasted-ternary4d",23y 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diff --git a/lib/node_modules/@stdlib/iter/any-by/README.md b/lib/node_modules/@stdlib/iter/any-by/README.md index 47a1fc87d709..e00aab2ea4eb 100644 --- a/lib/node_modules/@stdlib/iter/any-by/README.md +++ b/lib/node_modules/@stdlib/iter/any-by/README.md @@ -72,8 +72,8 @@ var bool = iterAnyBy( array2iterator( [] ), predicate ); A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the execution context of the `predicate` function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/cuany-by/README.md b/lib/node_modules/@stdlib/iter/cuany-by/README.md index ee919bd1b56a..c99dba502bd0 100644 --- a/lib/node_modules/@stdlib/iter/cuany-by/README.md +++ b/lib/node_modules/@stdlib/iter/cuany-by/README.md @@ -81,8 +81,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the `predicate` function execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/cuevery-by/README.md b/lib/node_modules/@stdlib/iter/cuevery-by/README.md index d297ecb59de5..7f023b9cebec 100644 --- a/lib/node_modules/@stdlib/iter/cuevery-by/README.md +++ b/lib/node_modules/@stdlib/iter/cuevery-by/README.md @@ -81,8 +81,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the `predicate` function execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/cunone-by/README.md b/lib/node_modules/@stdlib/iter/cunone-by/README.md index 0083e9c90e87..b5370be834cb 100644 --- a/lib/node_modules/@stdlib/iter/cunone-by/README.md +++ b/lib/node_modules/@stdlib/iter/cunone-by/README.md @@ -81,8 +81,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the `predicate` function execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/cusome-by/README.md b/lib/node_modules/@stdlib/iter/cusome-by/README.md index 323c5aa9d9aa..8be0151c17a9 100644 --- a/lib/node_modules/@stdlib/iter/cusome-by/README.md +++ b/lib/node_modules/@stdlib/iter/cusome-by/README.md @@ -81,8 +81,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the `predicate` function execution context, provide a `thisArg`. @@ -131,7 +131,7 @@ var count = ctx.count;
- + ## Notes - A `predicate` function is invoked for each iterated value until the `nth` truthy `predicate` function return value. The returned iterator continues iterating until it reaches the end of the input iterator, even after the condition is met. diff --git a/lib/node_modules/@stdlib/iter/do-until-each/README.md b/lib/node_modules/@stdlib/iter/do-until-each/README.md index 935c1f845d35..6725b01dfc00 100644 --- a/lib/node_modules/@stdlib/iter/do-until-each/README.md +++ b/lib/node_modules/@stdlib/iter/do-until-each/README.md @@ -79,8 +79,8 @@ The returned iterator protocol-compliant object has the following properties: Both the `predicate` function and the function to invoke for each iterated value are provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); diff --git a/lib/node_modules/@stdlib/iter/do-while-each/README.md b/lib/node_modules/@stdlib/iter/do-while-each/README.md index 6c0a7d178c96..413067b12975 100644 --- a/lib/node_modules/@stdlib/iter/do-while-each/README.md +++ b/lib/node_modules/@stdlib/iter/do-while-each/README.md @@ -80,8 +80,8 @@ The returned iterator protocol-compliant object has the following properties: Both the `predicate` function and the function to invoke for each iterated value are provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). ```javascript var iterDoWhileEach = require( '@stdlib/iter/do-while-each' ); diff --git a/lib/node_modules/@stdlib/iter/every-by/README.md b/lib/node_modules/@stdlib/iter/every-by/README.md index 435d629d5a3e..8cf9e58ad804 100644 --- a/lib/node_modules/@stdlib/iter/every-by/README.md +++ b/lib/node_modules/@stdlib/iter/every-by/README.md @@ -72,8 +72,8 @@ var bool = iterEveryBy( array2iterator( [] ), predicate ); A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the execution context of the `predicate` function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/flow/README.md b/lib/node_modules/@stdlib/iter/flow/README.md index 92cf1e5621d9..0210b858d957 100644 --- a/lib/node_modules/@stdlib/iter/flow/README.md +++ b/lib/node_modules/@stdlib/iter/flow/README.md @@ -63,8 +63,8 @@ function iterFcn( iterator[, ...args] ) {...} where -- **iterator**: an [iterator][mdn-iterator-protocol] -- **...args**: additional [iterator][mdn-iterator-protocol] function arguments +- **iterator**: an [iterator][mdn-iterator-protocol]. +- **...args**: additional [iterator][mdn-iterator-protocol] function arguments. When a fluent interface [iterator][mdn-iterator-protocol] method is invoked, the method invokes the corresponding [iterator][mdn-iterator-protocol] function with an [iterator][mdn-iterator-protocol] and provided method arguments. diff --git a/lib/node_modules/@stdlib/iter/for-each/README.md b/lib/node_modules/@stdlib/iter/for-each/README.md index 00b73b26648a..48dae207c694 100644 --- a/lib/node_modules/@stdlib/iter/for-each/README.md +++ b/lib/node_modules/@stdlib/iter/for-each/README.md @@ -75,8 +75,8 @@ The returned iterator protocol-compliant object has the following properties: The invoked function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); diff --git a/lib/node_modules/@stdlib/iter/intersection-by-hash/README.md b/lib/node_modules/@stdlib/iter/intersection-by-hash/README.md index 38941ef050e2..39811284e368 100644 --- a/lib/node_modules/@stdlib/iter/intersection-by-hash/README.md +++ b/lib/node_modules/@stdlib/iter/intersection-by-hash/README.md @@ -71,7 +71,7 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A hash function is provided one argument: -- **v**: the current iterated value +- **v**: the current iterated value. To set the execution context of the hash function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/mapn/README.md b/lib/node_modules/@stdlib/iter/mapn/README.md index b9083c6cf15d..b17aa50c9cd3 100644 --- a/lib/node_modules/@stdlib/iter/mapn/README.md +++ b/lib/node_modules/@stdlib/iter/mapn/README.md @@ -74,8 +74,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the The invoked `function` is provided `N+1` arguments, where `N` is the number of provided [iterators][mdn-iterator-protocol] and the last argument is the iteration index: -- `...value`: iterated values -- `index`: iteration index (zero-based) +- `...value`: iterated values. +- `index`: iteration index (zero-based). ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); diff --git a/lib/node_modules/@stdlib/iter/none-by/README.md b/lib/node_modules/@stdlib/iter/none-by/README.md index 316c49837810..31f1819887e4 100644 --- a/lib/node_modules/@stdlib/iter/none-by/README.md +++ b/lib/node_modules/@stdlib/iter/none-by/README.md @@ -72,8 +72,8 @@ var bool = iterNoneBy( array2iterator( [] ), predicate ); A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the execution context of the `predicate` function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/pipeline-thunk/README.md b/lib/node_modules/@stdlib/iter/pipeline-thunk/README.md index a7ee56479906..0cb5a7ea1a93 100644 --- a/lib/node_modules/@stdlib/iter/pipeline-thunk/README.md +++ b/lib/node_modules/@stdlib/iter/pipeline-thunk/README.md @@ -67,12 +67,12 @@ function iterFcn( iterator[, ...args] ) {...} where -- **iterator**: an [iterator][mdn-iterator-protocol] -- **...args**: additional [iterator][mdn-iterator-protocol] function arguments +- **iterator**: an [iterator][mdn-iterator-protocol]. +- **...args**: additional [iterator][mdn-iterator-protocol] function arguments. The returned function expects a single argument -- **iterator**: an [iterator][mdn-iterator-protocol] +- **iterator**: an [iterator][mdn-iterator-protocol]. and invokes `iterFcn` with the provided [iterator][mdn-iterator-protocol] and any previously provided `args`. diff --git a/lib/node_modules/@stdlib/iter/pop/README.md b/lib/node_modules/@stdlib/iter/pop/README.md index e0b4895581cb..0af9c3a5bde3 100644 --- a/lib/node_modules/@stdlib/iter/pop/README.md +++ b/lib/node_modules/@stdlib/iter/pop/README.md @@ -96,7 +96,7 @@ var bool = it.next().done; The callback function is provided a single argument: -- **v**: the skipped value +- **v**: the skipped value. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/reject/README.md b/lib/node_modules/@stdlib/iter/reject/README.md index 128efd3c5b5c..a1522e292531 100644 --- a/lib/node_modules/@stdlib/iter/reject/README.md +++ b/lib/node_modules/@stdlib/iter/reject/README.md @@ -71,8 +71,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the The `predicate` function is provided two arguments: -- `value`: iterated value -- `index`: iteration index (zero-based) +- `value`: iterated value. +- `index`: iteration index (zero-based). ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); diff --git a/lib/node_modules/@stdlib/iter/replicate-by/README.md b/lib/node_modules/@stdlib/iter/replicate-by/README.md index 7520f24774e0..75ddc2e84d7e 100644 --- a/lib/node_modules/@stdlib/iter/replicate-by/README.md +++ b/lib/node_modules/@stdlib/iter/replicate-by/README.md @@ -85,9 +85,9 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the The callback function is provided three arguments: -- **value**: iterated value -- **index**: source iteration index (zero-based) -- **n**: iteration index (zero-based) +- **value**: iterated value. +- **index**: source iteration index (zero-based). +- **n**: iteration index (zero-based). To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/shift/README.md b/lib/node_modules/@stdlib/iter/shift/README.md index b0b0dc4b8ddb..b48c77bc08a7 100644 --- a/lib/node_modules/@stdlib/iter/shift/README.md +++ b/lib/node_modules/@stdlib/iter/shift/README.md @@ -96,7 +96,7 @@ var bool = it.next().done; The callback function is provided a single argument: -- **v**: the skipped value +- **v**: the skipped value. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/some-by/README.md b/lib/node_modules/@stdlib/iter/some-by/README.md index 27805a61cc9f..2f7c01665639 100644 --- a/lib/node_modules/@stdlib/iter/some-by/README.md +++ b/lib/node_modules/@stdlib/iter/some-by/README.md @@ -72,8 +72,8 @@ var bool = iterSomeBy( array2iterator( [] ), 1, predicate ); A `predicate` function is provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). To set the execution context of the `predicate` function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/strided-by/README.md b/lib/node_modules/@stdlib/iter/strided-by/README.md index ff989d86573c..1b6990cf0f60 100644 --- a/lib/node_modules/@stdlib/iter/strided-by/README.md +++ b/lib/node_modules/@stdlib/iter/strided-by/README.md @@ -74,10 +74,10 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the The callback function is provided four arguments: -- **value**: iterated value -- **i**: source iteration index (zero-based) -- **n**: iteration index (zero-based) -- **curr**: current stride +- **value**: iterated value. +- **i**: source iteration index (zero-based). +- **n**: iteration index (zero-based). +- **curr**: current stride. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/unique-by-hash/README.md b/lib/node_modules/@stdlib/iter/unique-by-hash/README.md index f454d558460e..1fd68d1c46c3 100644 --- a/lib/node_modules/@stdlib/iter/unique-by-hash/README.md +++ b/lib/node_modules/@stdlib/iter/unique-by-hash/README.md @@ -79,7 +79,7 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A hash function is provided one argument: -- **v**: the current iterated value +- **v**: the current iterated value. To set the execution context of the hash function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/unique-by/README.md b/lib/node_modules/@stdlib/iter/unique-by/README.md index 5f3f273a6e74..27481e3f8218 100644 --- a/lib/node_modules/@stdlib/iter/unique-by/README.md +++ b/lib/node_modules/@stdlib/iter/unique-by/README.md @@ -79,8 +79,8 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the A `predicate` function is provided two arguments: -- **a**: a previously identified unique value -- **b**: the value whose uniqueness is being determined +- **a**: a previously identified unique value. +- **b**: the value whose uniqueness is being determined. To set the execution context of the `predicate` function, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/iter/until-each/README.md b/lib/node_modules/@stdlib/iter/until-each/README.md index 34359e1ef4c4..2b791ac9eb2f 100644 --- a/lib/node_modules/@stdlib/iter/until-each/README.md +++ b/lib/node_modules/@stdlib/iter/until-each/README.md @@ -79,8 +79,8 @@ The returned iterator protocol-compliant object has the following properties: Both the `predicate` function and the function to invoke for each iterated value are provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); @@ -220,6 +220,12 @@ while ( true ) {
+* * * + +## See Also + +- [`@stdlib/iter/while-each`][@stdlib/iter/while-each]: create an iterator which, while a test condition is true, invokes a function for each iterated value before returning the iterated value. +
@@ -228,6 +234,12 @@ while ( true ) {
+ + +[@stdlib/iter/while-each]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/iter/while-each + + +
diff --git a/lib/node_modules/@stdlib/iter/while-each/README.md b/lib/node_modules/@stdlib/iter/while-each/README.md index 485998c40c77..dcbf1cee1b80 100644 --- a/lib/node_modules/@stdlib/iter/while-each/README.md +++ b/lib/node_modules/@stdlib/iter/while-each/README.md @@ -79,8 +79,8 @@ The returned iterator protocol-compliant object has the following properties: Both the `predicate` function and the function to invoke for each iterated value are provided two arguments: -- **value**: iterated value -- **index**: iteration index (zero-based) +- **value**: iterated value. +- **index**: iteration index (zero-based). ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); @@ -220,6 +220,12 @@ while ( true ) {
+* * * + +## See Also + +- [`@stdlib/iter/until-each`][@stdlib/iter/until-each]: create an iterator which, while a test condition is false, invokes a function for each iterated value before returning the iterated value. +
@@ -228,6 +234,12 @@ while ( true ) {
+ + +[@stdlib/iter/until-each]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/iter/until-each + + +
diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/README.md b/lib/node_modules/@stdlib/lapack/base/clacgv/README.md new file mode 100644 index 000000000000..18ee208e5644 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/README.md @@ -0,0 +1,225 @@ + + +# clacgv + +> Conjugate each element in a single-precision complex floating-point vector. + +
+ +## Usage + +```javascript +var clacgv = require( '@stdlib/lapack/base/clacgv' ); +``` + +#### clacgv( N, cx, strideCX ) + +Conjugates each element in a single-precision complex floating-point vector. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + +clacgv( 2, cx, 1 ); + +var z = cx.get( 0 ); +// returns + +var re = realf( z ); +// returns 1.0 + +var im = imagf( z ); +// returns -2.0 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **cx**: input [`Complex64Array`][@stdlib/array/complex64]. +- **strideCX**: stride length for `cx`. + +The `N` and stride parameters determine which elements in `cx` are conjugated. For example, to conjugate every other element in `cx`, + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +clacgv( 2, cx, 2 ); + +var z = cx.get( 0 ); +// returns + +var re = realf( z ); +// returns 1.0 + +var im = imagf( z ); +// returns -2.0 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +// Initial array: +var cx0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +// Create an offset view: +var cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Conjugate every element in `cx1`: +clacgv( 3, cx1, 1 ); + +var z = cx0.get( 1 ); +// returns + +var re = realf( z ); +// returns 3.0 + +var im = imagf( z ); +// returns -4.0 +``` + +#### clacgv.ndarray( N, cx, strideCX, offsetCX ) + +Conjugates each element in a single-precision floating-point vector using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +clacgv.ndarray( 3, cx, 1, 0 ); + +var z = cx.get( 0 ); +// returns + +var re = realf( z ); +// returns 1.0 + +var im = imagf( z ); +// returns -2.0 +``` + +The function has the following additional parameters: + +- **offsetCX**: starting index for `cx`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to conjugate every other element in the input strided array starting from the second element, + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +clacgv.ndarray( 2, cx, 2, 1 ); + +var z = cx.get( 3 ); +// returns + +var re = realf( z ); +// returns 7.0 + +var im = imagf( z ); +// returns -8.0 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `cx` unchanged. +- `clacgv()` corresponds to the [LAPACK][lapack] BLAS-like level 1 routine [`clacgv`][clacgv]. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var clacgv = require( '@stdlib/lapack/base/clacgv' ); + +function rand() { + return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +var cx = filledarrayBy( 10, 'complex64', rand ); +console.log( cx.toString() ); + +// Conjugate elements: +clacgv( cx.length, cx, 1 ); +console.log( cx.get( cx.length-1 ).toString() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: https://www.netlib.org/lapack + +[clacgv]: https://www.netlib.org/lapack/explore-html/d9/d50/group__lacgv_ga689d8db6749fa9b193ff8520bfd6b2e9.html#ga689d8db6749fa9b193ff8520bfd6b2e9 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/clacgv/benchmark/benchmark.js new file mode 100644 index 000000000000..21e579c1c3d8 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/benchmark/benchmark.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var pkg = require( './../package.json' ).name; +var clacgv = require( './../lib/clacgv.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var cxbuf; + var cx; + + cxbuf = uniform( len*2, -100.0, 100.0, options ); + cx = new Complex64Array( cxbuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + clacgv( cx.length, cx, 1 ); + if ( isnanf( cxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( cxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacgv/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..e538f6f823af --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/benchmark/benchmark.ndarray.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var pkg = require( './../package.json' ).name; +var clacgv = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var cxbuf; + var cx; + + cxbuf = uniform( len*2, -100.0, 100.0, options ); + cx = new Complex64Array( cxbuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + clacgv( cx.length, cx, 1, 0 ); + if ( isnanf( cxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( cxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':ndarray:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/clacgv/docs/repl.txt new file mode 100644 index 000000000000..59c6932e96ac --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/docs/repl.txt @@ -0,0 +1,108 @@ + +{{alias}}( N, cx, strideCX ) + Conjugates each element in a single-precision complex floating-point vector. + + The `N` and stride parameters determine which elements in `cx` are + conjugated. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N` is less than or equal to `0`, the function returns `cx` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + cx: Complex64Array + Input array. + + strideCX: integer + Stride length for `cx`. + + Returns + ------- + cx: Complex64Array + Input array. + + Examples + -------- + // Standard usage: + > var cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > {{alias}}( 2, cx, 1 ); + > var z = cx.get( 0 ); + > var re = {{alias:@stdlib/complex/float32/real}}( z ) + 1.0 + > var im = {{alias:@stdlib/complex/float32/imag}}( z ) + -2.0 + + // Advanced indexing: + > cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > {{alias}}( 2, cx, 2 ); + > z = cx.get( 0 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + 1.0 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + -2.0 + + // Using typed array views: + > var cx0 = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var cx1 = new {{alias:@stdlib/array/complex64}}( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, cx1, 1 ); + > z = cx0.get( 1 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + 3.0 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + -4.0 + + +{{alias}}.ndarray( N, cx, strideCX, offsetCX ) + Conjugates each element in a single-precision complex floating-point vector + using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + cx: Complex64Array + Input array. + + strideCX: integer + Stride length for `cx`. + + offsetCX: integer + Starting index for `cx`. + + Returns + ------- + cx: Complex64Array + Input array. + + Examples + -------- + // Standard usage: + > var cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > {{alias}}.ndarray( 2, cx, 1, 0 ); + > var z = cx.get( 0 ); + > var re = {{alias:@stdlib/complex/float32/real}}( z ) + 1.0 + > var im = {{alias:@stdlib/complex/float32/imag}}( z ) + -2.0 + + // Advanced indexing: + > cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + > {{alias}}.ndarray( 2, cx, 1, 2 ); + > z = cx.get( 2 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + 5.0 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + -6.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/clacgv/docs/types/index.d.ts new file mode 100644 index 000000000000..0a47bd98abb7 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/docs/types/index.d.ts @@ -0,0 +1,136 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex64Array } from '@stdlib/types/array'; + +/** +* Interface describing `clacgv`. +*/ +interface Routine { + /** + * Conjugates each element in a single-precision complex floating-point vector. + * + * @param N - number of indexed elements + * @param cx - input array + * @param strideCX - `cx` stride length + * @returns input array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var realf = require( '@stdlib/complex/float32/real' ); + * var imagf = require( '@stdlib/complex/float32/imag' ); + * + * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * clacgv( 3, cx, 1 ); + * + * var z = cx.get( 0 ); + * // returns + * + * var re = realf( z ); + * // returns 1.0 + * + * var im = imagf( z ); + * // returns -2.0 + */ + ( N: number, cx: Complex64Array, strideCX: number ): Complex64Array; + + /** + * Conjugates each element in a single-precision complex floating-point vector. + * + * @param N - number of indexed elements + * @param cx - input array + * @param strideCX - `cx` stride length + * @param offsetCX - starting index for `cx` + * @returns input array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var realf = require( '@stdlib/complex/float32/real' ); + * var imagf = require( '@stdlib/complex/float32/imag' ); + * + * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * clacgv.ndarray( 3, cx, 1, 0 ); + * + * var z = cx.get( 0 ); + * // returns + * + * var re = realf( z ); + * // returns 1.0 + * + * var im = imagf( z ); + * // returns -2.0 + */ + ndarray( N: number, cx: Complex64Array, strideCX: number, offsetCX: number ): Complex64Array; +} + +/** +* Conjugates each element in a single-precision complex floating-point vector. +* +* @param N - number of indexed elements +* @param cx - input array +* @param strideCX - `cx` stride length +* @returns input array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* clacgv( 3, cx, 1 ); +* +* var z = cx.get( 1 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns -4.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* clacgv.ndarray( 2, cx, 1, 1 ); +* +* var z = cx.get( 1 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns -4.0 +*/ +declare var clacgv: Routine; + + +// EXPORTS // + +export = clacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/clacgv/docs/types/test.ts new file mode 100644 index 000000000000..e593bb27175f --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/docs/types/test.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import clacgv = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + + clacgv( cx.length, cx, 1 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + + clacgv( '10', cx, 1 ); // $EcxpectError + clacgv( true, cx, 1 ); // $ExpectError + clacgv( false, cx, 1 ); // $ExpectError + clacgv( null, cx, 1 ); // $ExpectError + clacgv( undefined, cx, 1 ); // $ExpectError + clacgv( [], cx, 1 ); // $ExpectError + clacgv( {}, cx, 1 ); // $ExpectError + clacgv( ( cx: number ): number => cx, cx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + + clacgv( cx.length, 10, 1 ); // $ExpectError + clacgv( cx.length, '10', 1 ); // $ExpectError + clacgv( cx.length, true, 1 ); // $ExpectError + clacgv( cx.length, false, 1 ); // $ExpectError + clacgv( cx.length, null, 1 ); // $ExpectError + clacgv( cx.length, undefined, 1 ); // $ExpectError + clacgv( cx.length, [ '1' ], 1 ); // $ExpectError + clacgv( cx.length, {}, 1 ); // $ExpectError + clacgv( cx.length, ( cx: number ): number => cx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + + clacgv( cx.length, cx, '10' ); // $ExpectError + clacgv( cx.length, cx, true ); // $ExpectError + clacgv( cx.length, cx, false ); // $ExpectError + clacgv( cx.length, cx, null ); // $ExpectError + clacgv( cx.length, cx, undefined ); // $ExpectError + clacgv( cx.length, cx, [] ); // $ExpectError + clacgv( cx.length, cx, {} ); // $ExpectError + clacgv( cx.length, cx, ( cx: number ): number => cx ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const cx = new Complex64Array( 10 ); + + clacgv(); // $ExpectError + clacgv( cx.length ); // $ExpectError + clacgv( cx.length, cx ); // $ExpectError + clacgv( cx.length, cx, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + + clacgv.ndarray( cx.length, cx, 1, 0 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + + clacgv.ndarray( '10', cx, 1, 0 ); // $ExpectError + clacgv.ndarray( true, cx, 1, 0 ); // $ExpectError + clacgv.ndarray( false, cx, 1, 0 ); // $ExpectError + clacgv.ndarray( null, cx, 1, 0 ); // $ExpectError + clacgv.ndarray( undefined, cx, 1, 0 ); // $ExpectError + clacgv.ndarray( [], cx, 1, 0 ); // $ExpectError + clacgv.ndarray( {}, cx, 1, 0 ); // $ExpectError + clacgv.ndarray( ( cx: number ): number => cx, cx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + + clacgv( cx.length, 10, 1, 0 ); // $ExpectError + clacgv( cx.length, '10', 1, 0 ); // $ExpectError + clacgv( cx.length, true, 1, 0 ); // $ExpectError + clacgv( cx.length, false, 1, 0 ); // $ExpectError + clacgv( cx.length, null, 1, 0 ); // $ExpectError + clacgv( cx.length, undefined, 1, 0 ); // $ExpectError + clacgv( cx.length, [ '1' ], 1, 0 ); // $ExpectError + clacgv( cx.length, {}, 1, 0 ); // $ExpectError + clacgv( cx.length, ( cx: number ): number => cx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + + clacgv.ndarray( cx.length, cx, '10', 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, true, 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, false, 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, null, 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, undefined, 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, [], 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, {}, 0 ); // $ExpectError + clacgv.ndarray( cx.length, cx, ( cx: number ): number => cx, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + + clacgv.ndarray( cx.length, cx, 1, '10' ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, true ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, false ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, null ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, undefined ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, [] ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, {} ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, ( cx: number ): number => cx ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const cx = new Complex64Array( 10 ); + + clacgv.ndarray(); // $ExpectError + clacgv.ndarray( cx.length ); // $ExpectError + clacgv.ndarray( cx.length, cx ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1 ); // $ExpectError + clacgv.ndarray( cx.length, cx, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/examples/index.js b/lib/node_modules/@stdlib/lapack/base/clacgv/examples/index.js new file mode 100644 index 000000000000..88be8f7fe351 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var clacgv = require( './../lib' ); + +function rand() { + return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +var cx = filledarrayBy( 10, 'complex64', rand ); +console.log( cx.toString() ); + +// Conjugate elements: +clacgv( cx.length, cx, 1 ); +console.log( cx.get( cx.length-1 ).toString() ); diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/lib/clacgv.js b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/clacgv.js new file mode 100644 index 000000000000..623378ce49d9 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/clacgv.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Conjugates each element in a single-precision complex floating-point vector. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} cx - input array +* @param {integer} strideCX - `cx` stride length +* @returns {Complex64Array} input array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* clacgv( 3, cx, 1 ); +* +* var z = cx.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 1.0 +* +* var im = imagf( z ); +* // returns -2.0 +*/ +function clacgv( N, cx, strideCX ) { + return ndarray( N, cx, strideCX, stride2offset( N, strideCX ) ); +} + + +// EXPORTS // + +module.exports = clacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/lib/index.js b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/index.js new file mode 100644 index 000000000000..8ca5c7d3ff78 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/index.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK BLAS-like level-1 routine to conjugate each element in a single-precision complex floating-point vector. +* +* @module @stdlib/lapack/base/clacgv +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var clacgv = require( '@stdlib/lapack/base/clacgv' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* clacgv( 3, cx, 1 ); +* +* var z = cx.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 1.0 +* +* var im = imagf( z ); +* // returns -2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var clacgv = require( '@stdlib/lapack/base/clacgv' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* clacgv.ndarray( 3, 1, 0 ); +* +* var z = cx.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 1.0 +* +* var im = imagf( z ); +* // returns -2.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var clacgv; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + clacgv = main; +} else { + clacgv = tmp; +} + + +// EXPORTS // + +module.exports = clacgv; + +// exports: { "ndarray": "clacgv.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/lib/main.js b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/main.js new file mode 100644 index 000000000000..60873b80d682 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var clacgv = require( './clacgv.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( clacgv, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = clacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js new file mode 100644 index 000000000000..233a388a5665 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); + + +// MAIN // + +/** +* Conjugates each element in a single-precision complex floating-point vector. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} cx - input array +* @param {integer} strideCX - `cx` stride length +* @param {NonNegativeInteger} offsetCX - starting `cx` index +* @returns {Complex64Array} input array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* clacgv( 3, cx, 1, 0 ); +* +* var z = cx.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 1.0 +* +* var im = imagf( z ); +* // returns -2.0 +*/ +function clacgv( N, cx, strideCX, offsetCX ) { + var cx32; + var ix; + var sx; + var i; + + if ( N <= 0 ) { + return cx; + } + // Reinterpret the input array as a real-valued array of interleaved real and imaginary components: + cx32 = reinterpret( cx, 0 ); + + // Adjust the strides and offset: + sx = strideCX * 2; + ix = ( offsetCX * 2 ) + 1; // index of the first imaginary component + + // Conjugate each element by negating the imaginary components... + for ( i = 0; i < N; i++ ) { + cx32[ ix ] = -cx32[ ix ]; + ix += sx; + } + return cx; +} + + +// EXPORTS // + +module.exports = clacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/package.json b/lib/node_modules/@stdlib/lapack/base/clacgv/package.json new file mode 100644 index 000000000000..c8ef43948763 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/lapack/base/clacgv", + "version": "0.0.0", + "description": "Conjugate each element in a single-precision complex floating-point vector.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "blas", + "level 1", + "linear", + "algebra", + "subroutines", + "clacgv", + "conjugate", + "vector", + "typed", + "array", + "ndarray", + "complex", + "complex64", + "float", + "float32", + "float32array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.clacgv.js b/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.clacgv.js new file mode 100644 index 000000000000..0cb5193399a1 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.clacgv.js @@ -0,0 +1,235 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var clacgv = require( './../lib/clacgv.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof clacgv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', function test( t ) { + t.strictEqual( clacgv.length, 3, 'arity of 3' ); + t.end(); +}); + +tape( 'the function conjugates elements in a strided array', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 0.3, // 1 + 0.1, // 1 + 0.5, // 2 + 0.0, // 2 + 0.0, // 3 + 0.5, // 3 + 0.0, // 4 + 0.2 // 4 + ]); + + clacgv( 4, cx, 1 ); + + expected = new Complex64Array([ + 0.3, // 1 + -0.1, // 1 + 0.5, // 2 + -0.0, // 2 + 0.0, // 3 + -0.5, // 3 + 0.0, // 4 + -0.2 // 4 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `cx` stride', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0, + 9.0, // 3 + 10.0, // 3 + 11.0, + 12.0 + ]); + + clacgv( 3, cx, 2 ); + + expected = new Complex64Array([ + 1.0, // 1 + -2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + -6.0, // 2 + 7.0, + 8.0, + 9.0, // 3 + -10.0, // 3 + 11.0, + 12.0 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a negative `cx` stride', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 1.0, // 3 + 2.0, // 3 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0, + 9.0, // 1 + 10.0, // 1 + 11.0, + 12.0 + ]); + + clacgv( 3, cx, -2 ); + + expected = new Complex64Array([ + 1.0, // 3 + -2.0, // 3 + 3.0, + 4.0, + 5.0, // 2 + -6.0, // 2 + 7.0, + 8.0, + 9.0, // 1 + -10.0, // 1 + 11.0, + 12.0 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var cx; + + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + out = clacgv( 4, cx, 1 ); + + t.strictEqual( out, cx, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0 + ]); + + clacgv( -1, cx, 1 ); + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + clacgv( 0, cx, 1 ); + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var cx0; + var cx1; + + // Initial arrays... + cx0 = new Complex64Array([ + 0.1, + -0.3, + 8.0, // 1 + 9.0, // 1 + 0.5, // 2 + -0.1, // 2 + 2.0, // 3 + 5.0, // 3 + 2.0, + 3.0 + ]); + + // Create offset views... + cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + + clacgv( 3, cx1, 1 ); + + expected = new Complex64Array([ + 0.1, + -0.3, + 8.0, // 1 + -9.0, // 1 + 0.5, // 2 + 0.1, // 2 + 2.0, // 3 + -5.0, // 3 + 2.0, + 3.0 + ]); + + t.ok( isSameComplex64Array( cx0, expected ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.js b/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.js new file mode 100644 index 000000000000..2ec9b3078f91 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var isBrowser = require( '@stdlib/assert/is-browser' ); +var clacgv = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': isBrowser +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof clacgv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof clacgv.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var clacgv = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( clacgv, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var clacgv; + var main; + + main = require( './../lib/clacgv.js' ); + + clacgv = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( clacgv, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.ndarray.js new file mode 100644 index 000000000000..40efefd10e04 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/test/test.ndarray.js @@ -0,0 +1,283 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var clacgv = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof clacgv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( clacgv.length, 4, 'arity of 4' ); + t.end(); +}); + +tape( 'the function conjugates elements in a strided array', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 0.3, // 1 + 0.1, // 1 + 0.5, // 2 + 0.0, // 2 + 0.0, // 3 + 0.5, // 3 + 0.0, // 4 + 0.2, // 4 + 2.0, + 3.0, + 2.0, + 3.0 + ]); + + clacgv( 4, cx, 1, 0 ); + + expected = new Complex64Array([ + 0.3, // 1 + -0.1, // 1 + 0.5, // 2 + -0.0, // 2 + 0.0, // 3 + -0.5, // 3 + 0.0, // 4 + -0.2, // 4 + 2.0, + 3.0, + 2.0, + 3.0 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `cx` stride', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 0.1, // 1 + 0.1, // 1 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 3 + -0.3, // 3 + 7.0, + 2.0 + ]); + + clacgv( 3, cx, 2, 0 ); + + expected = new Complex64Array([ + 0.1, // 1 + -0.1, // 1 + 3.0, + 6.0, + -0.6, // 2 + -0.1, // 2 + 4.0, + 7.0, + 0.1, // 3 + 0.3, // 3 + 7.0, + 2.0 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `cx` stride', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 0.1, // 3 + 0.1, // 3 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 1 + -0.3, // 1 + 7.0, + 2.0 + ]); + + clacgv( 3, cx, -2, 4 ); + + expected = new Complex64Array([ + 0.1, // 3 + -0.1, // 3 + 3.0, + 6.0, + -0.6, // 2 + -0.1, // 2 + 4.0, + 7.0, + 0.1, // 1 + 0.3, // 1 + 7.0, + 2.0 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `cx` offset', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + 6.0, // 1 + 0.1, // 2 + -0.3, // 2 + 7.0, // 3 + 2.0 // 3 + ]); + + clacgv( 3, cx, 1, 3 ); + + expected = new Complex64Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + -6.0, // 1 + 0.1, // 2 + 0.3, // 2 + 7.0, // 3 + -2.0 // 3 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var cx; + + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + out = clacgv( 4, cx, 1, 0 ); + + t.strictEqual( out, cx, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0 + ]); + + clacgv( -1, cx, 1, 0 ); + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + clacgv( 0, cx, 1, 0 ); + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var cx; + + cx = new Complex64Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + 6.0, // 1 + 0.1, + -0.3, + 7.0, + 2.0, + 2.0, // 2 + 3.0 // 2 + ]); + + clacgv( 2, cx, -3, 6 ); + + expected = new Complex64Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + -6.0, // 1 + 0.1, + -0.3, + 7.0, + 2.0, + 2.0, // 2 + -3.0 // 2 + ]); + + t.ok( isSameComplex64Array( cx, expected ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/README.md b/lib/node_modules/@stdlib/lapack/base/clacpy/README.md new file mode 100644 index 000000000000..9d4e17ec16b3 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/README.md @@ -0,0 +1,275 @@ + + +# clacpy + +> Copy all or part of a matrix `A` to another matrix `B`. + +
+ +## Usage + +```javascript +var clacpy = require( '@stdlib/lapack/base/clacpy' ); +``` + +#### clacpy( order, uplo, M, N, A, LDA, B, LDB ) + +Copies all or part of a matrix `A` to another matrix `B`. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); + +var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var B = new Complex64Array( 4 ); + +clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); + +var viewB = reinterpret( B, 0 ); +// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] +``` + +The function has the following parameters: + +- **order**: storage layout. +- **uplo**: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **A**: input [`Complex64Array`][@stdlib/array/complex64]. +- **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`). +- **B**: output [`Complex64Array`][@stdlib/array/complex64]. +- **LDB**: stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`). + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); + +// Initial arrays... +var A0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var B0 = new Complex64Array( 5 ); + +// Create offset views... +var A1 = new Complex64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var B1 = new Complex64Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +clacpy( 'row-major', 'all', 2, 2, A1, 2, B1, 2 ); + +var viewB = reinterpret( B0, 0 ); +// returns [ 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] +``` + +#### clacpy.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob ) + +Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); + +var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var B = new Complex64Array( 4 ); + +clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); + +var viewB = reinterpret( B, 0 ); +// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] +``` + +The function has the following parameters: + +- **uplo**: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **A**: input [`Complex64Array`][@stdlib/array/complex64]. +- **sa1**: stride of the first dimension of `A`. +- **sa2**: stride of the second dimension of `A`. +- **oa**: starting index for `A`. +- **B**: output [`Complex64Array`][@stdlib/array/complex64]. +- **sb1**: stride of the first dimension of `B`. +- **sb2**: stride of the second dimension of `B`. +- **ob**: starting index for `B`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); + +var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var B = new Complex64Array( 6 ); + +clacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); + +var viewB = reinterpret( B, 0 ); +// returns [ 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] +``` + +
+ + + +
+ +## Notes + +- `clacpy()` corresponds to the [LAPACK][lapack] routine [`clacpy`][lapack-clacpy]. + +
+ + + +
+ +## Examples + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var uniform = require( '@stdlib/random/array/discrete-uniform' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var clacpy = require( '@stdlib/lapack/base/clacpy' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex64Array( uniform( 2*N, -10, 10, { + 'dtype': 'generic' +})); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var B = new Complex64Array( uniform( 2*N, -10, 10, { + 'dtype': 'generic' +})); +console.log( ndarray2array( B, shape, strides, 0, order ) ); + +clacpy( order, 'all', shape[ 0 ], shape[ 1 ], A, strides[ 0 ], B, strides[ 0 ] ); +console.log( ndarray2array( B, shape, strides, 0, order ) ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +TODO +``` + +#### TODO + +TODO. + +```c +TODO +``` + +TODO + +```c +TODO +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +TODO +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: https://www.netlib.org/lapack/explore-html/ + +[lapack-clacpy]: https://netlib.org/lapack/explore-html/d0/d9e/group__lacpy_ga4eb69fef93799574c785add4eeb619f3.html#ga4eb69fef93799574c785add4eeb619f3 + +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/clacpy/benchmark/benchmark.js new file mode 100644 index 000000000000..c63a3504abfe --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var clacpy = require( './../lib/clacpy.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var opts; + var A; + var B; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + B = new Complex64Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = clacpy( 'column-major', 'all', N, N, A, N, B, N ); + if ( isnanf( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+':order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacpy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..de88c59ce289 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/benchmark/benchmark.ndarray.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var clacpy = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var opts; + var A; + var B; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + B = new Complex64Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = clacpy( 'all', N, N, A, 1, N, 0, B, 1, N, 0 ); + if ( isnanf( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+':ndarray:order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/clacpy/docs/repl.txt new file mode 100644 index 000000000000..8895a7e90500 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/docs/repl.txt @@ -0,0 +1,120 @@ + +{{alias}}( order, uplo, M, N, A, LDA, B, LDB ) + Copies all or part of a matrix `A` to another matrix `B`. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + Parameters + ---------- + order: string + Row-major (C-style) or column-major (Fortran-style) order. Must be + either 'row-major' or 'column-major'. + + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + A: Complex64Array + Input matrix `A`. + + LDA: integer + Stride of the first dimension of `A` (a.k.a., leading dimension of the + matrix `A`). + + B: Complex64Array + Output matrix `B`. + + LDB: integer + Stride of the first dimension of `B` (a.k.a., leading dimension of the + matrix `B`). + + Returns + ------- + B: Complex64Array + Output matrix. + + Examples + -------- + > var abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]; + > var bbuf = [ 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ]; + > var A = new {{alias:@stdlib/array/complex64}}( abuf ); + > var B = new {{alias:@stdlib/array/complex64}}( bbuf ); + > {{alias}}( 'row-major', 'all', 2, 2, A, 2, B, 2 ); + > var z = B.get( 0 ); + > {{alias:@stdlib/complex/float32/real}}( z ) + 1.0 + > {{alias:@stdlib/complex/float32/imag}}( z ) + 2.0 + + +{{alias}}.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob ) + Copies all or part of a matrix `A` to another matrix `B` using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + A: Complex64Array + Input matrix `A`. + + sa1: integer + Stride of the first dimension of `A`. + + sa2: integer + Stride of the second dimension of `A`. + + oa: integer + Starting index for `A`. + + B: Complex64Array + Output matrix `B`. + + sb1: integer + Stride of the first dimension of `B`. + + sb2: integer + Stride of the second dimension of `B`. + + ob: integer + Starting index for `B`. + + Returns + ------- + B: Complex64Array + Output matrix. + + Examples + -------- + > var abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]; + > var bbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var A = new {{alias:@stdlib/array/complex64}}( abuf ); + > var B = new {{alias:@stdlib/array/complex64}}( bbuf ); + > {{alias}}.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); + > var z = B.get( 2 ); + > {{alias:@stdlib/complex/float32/real}}( z ) + 3.0 + > {{alias:@stdlib/complex/float32/imag}}( z ) + 4.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/clacpy/docs/types/index.d.ts new file mode 100644 index 000000000000..9f6b7aa27961 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/docs/types/index.d.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Layout } from '@stdlib/types/blas'; +import { Complex64Array } from '@stdlib/types/array'; + +/** +* Interface describing `clacpy`. +*/ +interface Routine { + /** + * Copies all or part of a matrix `A` to another matrix `B`. + * + * @param order - storage layout of `A` and `B` + * @param uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param A - input matrix + * @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) + * @param B - output matrix + * @param LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) + * @returns `B` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var realf = require( '@stdlib/complex/float32/real' ); + * var imagf = require( '@stdlib/complex/float32/imag' ); + * + * var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var B = new Complex64Array( 4 ); + * + * clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); + * + * var z = B.get( 0 ); + * // returns + * + * var v = realf( z ); + * // returns 1.0 + * + * v = imagf( z ); + * // returns 2.0 + */ + ( order: Layout, uplo: string, M: number, N: number, A: Complex64Array, LDA: number, B: Complex64Array, LDB: number ): Complex64Array; + + /** + * Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics. + * + * @param uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param A - input matrix + * @param strideA1 - stride of the first dimension of `A` + * @param strideA2 - stride of the second dimension of `A` + * @param offsetA - starting index for `A` + * @param B - output matrix + * @param strideB1 - stride of the first dimension of `B` + * @param strideB2 - stride of the second dimension of `B` + * @param offsetB - starting index for `B` + * @returns `B` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var realf = require( '@stdlib/complex/float32/real' ); + * var imagf = require( '@stdlib/complex/float32/imag' ); + * + * var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); + * var B = new Complex64Array( 12 ); + * + * clacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); + * + * var z = B.get( 2 ); + * // returns + * + * var v = realf( z ); + * // returns 3.0 + * + * v = imagf( z ); + * // returns 4.0 + */ + ndarray( uplo: string, M: number, N: number, A: Complex64Array, strideA1: number, strideA2: number, offsetA: number, B: Complex64Array, strideB1: number, strideB2: number, offsetB: number ): Complex64Array; +} + +/** +* Copies all or part of a matrix `A` to another matrix `B`. +* +* @param order - storage layout of `A` and `B` +* @param uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param M - number of rows in matrix `A` +* @param N - number of columns in matrix `A` +* @param A - input matrix +* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @param B - output matrix +* @param LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) +* @returns `B` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex64Array( 12 ); +* +* clacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +*/ +declare var clacpy: Routine; + + +// EXPORTS // + +export = clacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/clacpy/docs/types/test.ts new file mode 100644 index 000000000000..2441dc2a7bdb --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/docs/types/test.ts @@ -0,0 +1,359 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import clacpy = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a string... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 5, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( true, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( false, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( null, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( void 0, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( [], 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( {}, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( ( x: number ): number => x, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a string... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 5, 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', true, 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', false, 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', null, 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', void 0, 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', [], 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', {}, 2, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', ( x: number ): number => x, 2, 2, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 'all', '5', 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', true, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', false, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', null, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', void 0, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', [], 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', {}, 2, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', ( x: number ): number => x, 2, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 'all', 2, '5', A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, true, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, false, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, null, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, void 0, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, [], A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, {}, A, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, ( x: number ): number => x, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Complex64Array... +{ + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 'all', 2, 2, '5', 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, 5, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, true, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, false, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, null, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, void 0, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, [], 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, {}, 2, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, ( x: number ): number => x, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 'all', 2, 2, A, '5', B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, true, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, false, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, null, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, void 0, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, [], B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, {}, B, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, ( x: number ): number => x, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a Complex64Array... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + clacpy( 'row-major', 'all', 2, 2, A, 2, '5', 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, 5, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, true, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, false, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, null, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, void 0, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, [], 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, {}, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, ( x: number ): number => x, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy( 'row-major', 'all', 2, 2, A, 2, B, '5' ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, true ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, false ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, null ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, void 0 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, [] ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, {} ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy(); // $ExpectError + clacpy( 'row-major' ); // $ExpectError + clacpy( 'row-major', 'all' ); // $ExpectError + clacpy( 'row-major', 'all', 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2 ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B ); // $ExpectError + clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex64Array... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a string... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 5, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( true, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( false, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( null, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( void 0, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( [], 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( {}, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( ( x: number ): number => x, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', '5', 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', true, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', false, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', null, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', void 0, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', [], 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', {}, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', ( x: number ): number => x, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, '5', A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, true, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, false, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, null, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, void 0, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, [], A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, {}, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, ( x: number ): number => x, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex64Array... +{ + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, '5', 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, 5, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, true, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, false, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, null, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, void 0, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, [], 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, {}, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, ( x: number ): number => x, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, '5', 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, true, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, false, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, null, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, void 0, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, [], 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, {}, 1, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, ( x: number ): number => x, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, 2, '5', 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, true, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, false, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, null, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, void 0, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, [], 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, {}, 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, ( x: number ): number => x, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, 2, 1, '5', B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, true, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, false, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, null, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, void 0, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, [], B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, {}, B, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, ( x: number ): number => x, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a Complex64Array... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, '5', 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, 5, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, true, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, false, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, null, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, void 0, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, [], 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, {}, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, ( x: number ): number => x, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a ninth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, '5', 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, true, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, false, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, null, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, void 0, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, [], 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, {}, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a tenth argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, '5', 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, true, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, false, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, null, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, void 0, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, [], 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, {}, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eleventh argument which is not a number... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, '5' ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, true ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, false ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, null ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, void 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, [] ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, {} ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex64Array( 4 ); + + clacpy.ndarray(); // $ExpectError + clacpy.ndarray( 'all' ); // $ExpectError + clacpy.ndarray( 'all', 2 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1 ); // $ExpectError + clacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/examples/index.js b/lib/node_modules/@stdlib/lapack/base/clacpy/examples/index.js new file mode 100644 index 000000000000..06fef80b504c --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var uniform = require( '@stdlib/random/array/discrete-uniform' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var dlacpy = require( './../lib' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex64Array( uniform( 2*N, -10, 10, { + 'dtype': 'float32' +})); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var B = new Complex64Array( uniform( 2*N, -10, 10, { + 'dtype': 'float32' +})); +console.log( ndarray2array( B, shape, strides, 0, order ) ); + +dlacpy( order, 'all', shape[ 0 ], shape[ 1 ], A, strides[ 0 ], B, strides[ 0 ] ); +console.log( ndarray2array( B, shape, strides, 0, order ) ); diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/lib/base.js b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/base.js new file mode 100644 index 000000000000..2dd7721d1cc7 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/base.js @@ -0,0 +1,614 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len, max-params */ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); +var loopOrder = require( '@stdlib/ndarray/base/unary-loop-interchange-order' ); +var min = require( '@stdlib/math/base/special/fast/min' ); + + +// FUNCTIONS // + +/** +* Copies all of a matrix `A` to another matrix `B`. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Float32Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Float32Array} B - output matrix view +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Float32Array} `B` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, 4, 2, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, 4, -2, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 1.0, 2.0, 7.0, 8.0, 5.0, 6.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, -4, 2, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 7.0, 8.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, -4, -2, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 5.0, 6.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, 2, 4, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 5.0, 6.0, 3.0, 4.0, 7.0, 8.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, -2, 4, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 7.0, 8.0, 1.0, 2.0, 5.0, 6.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, 2, -4, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 1.0, 2.0, 7.0, 8.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyAll( 2, 2, A, -2, -4, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 3.0, 4.0, 5.0, 6.0, 1.0, 2.0 ] +*/ +function copyAll( M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var da0; + var da1; + var db0; + var db1; + var sh; + var S0; + var S1; + var sa; + var sb; + var ia; + var ib; + var i0; + var i1; + var o; + + // Resolve the loop interchange order: + o = loopOrder( [ M, N ], [ strideA1, strideA2 ], [ strideB1, strideB2 ] ); + sh = o.sh; + sa = o.sx; + sb = o.sy; + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + da0 = sa[ 0 ]; + da1 = sa[ 1 ] - ( S0*sa[0] ); + db0 = sb[ 0 ]; + db1 = sb[ 1 ] - ( S0*sb[0] ); + + // Set the pointers to the first indexed elements in the respective matrices... + ia = offsetA; + ib = offsetB; + + // Iterate over the matrix dimensions... + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + B[ ib ] = A[ ia ]; + B[ ib+1 ] = A[ ia+1 ]; + ia += da0; + ib += db0; + } + ia += da1; + ib += db1; + } + return B; +} + +/** +* Copies the upper triangular/trapezoidal part of a matrix `A` to another matrix `B`. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Float32Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Float32Array} B - output matrix view +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Float32Array} `B` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, 4, 2, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, 4, -2, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 5.0, 6.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, -4, 2, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 7.0, 8.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, -4, -2, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 5.0, 6.0, 0.0, 0.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, 2, 4, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 5.0, 6.0, 0.0, 0.0, 7.0, 8.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, -2, 4, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 7.0, 8.0, 0.0, 0.0, 5.0, 6.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, 2, -4, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyUpper( 2, 2, A, -2, -4, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 3.0, 4.0, 0.0, 0.0, 1.0, 2.0 ] +*/ +function copyUpper( M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var ia; + var ib; + var i0; + var i1; + var ja; + var jb; + + ia = offsetA; + ib = offsetB; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + ja = ia + ( i1*strideA2 ); + jb = ib + ( i1*strideB2 ); + for ( i0 = i1; i0 < N; i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA2; + jb += strideB2; + } + ia += strideA1; + ib += strideB1; + } + return B; + } + for ( i1 = 0; i1 < N; i1++ ) { + jb = ib; + ja = ia; + for ( i0 = 0; i0 <= min( i1, M-1 ); i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA1; + jb += strideB1; + } + ia += strideA2; + ib += strideB2; + } + return B; +} + +/** +* Copies the lower triangular/trapezoidal part of a matrix `A` to another matrix `B`. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Float32Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Float32Array} B - output matrix +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Float32Array} `B` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, 4, 2, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 7.0, 8.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, 4, -2, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 0.0, 0.0, 7.0, 8.0, 5.0, 6.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, -4, 2, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, -4, -2, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, 2, 4, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 7.0, 8.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, -2, 4, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 5.0, 6.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, 2, -4, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float32Array( 8 ); +* +* copyLower( 2, 2, A, -2, -4, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 0.0, 0.0, 5.0, 6.0, 1.0, 2.0 ] +*/ +function copyLower( M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var ia; + var ib; + var i0; + var i1; + var ja; + var jb; + + ia = offsetA; + ib = offsetB; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + ja = ia; + jb = ib; + for ( i0 = 0; i0 <= min( i1, N-1 ); i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA2; + jb += strideB2; + } + ia += strideA1; + ib += strideB1; + } + return B; + } + for ( i1 = 0; i1 < N; i1++ ) { + ja = ia + ( i1*strideA1 ); + jb = ib + ( i1*strideB1 ); + for ( i0 = i1; i0 < M; i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA1; + jb += strideB1; + } + ia += strideA2; + ib += strideB2; + } + return B; +} + + +// MAIN // + +/** +* Copies all or part of a matrix `A` to another matrix `B`. +* +* @private +* @param {string} uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex64Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Complex64Array} B - output matrix +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Complex64Array} `B` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +* +* z = B.get( 2 ); +* // returns +* +* v = realf( z ); +* // returns 5.0 +* +* v = imagf( z ); +* // returns 6.0 +* +* z = B.get( 3 ); +* // returns +* +* v = realf( z ); +* // returns 7.0 +* +* v = imagf( z ); +* // returns 8.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'upper', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); +* // B => +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +* +* z = B.get( 2 ); +* // returns +* +* v = realf( z ); +* // returns 0.0 +* +* v = imagf( z ); +* // returns 0.0 +* +* z = B.get( 3 ); +* // returns +* +* v = realf( z ); +* // returns 7.0 +* +* v = imagf( z ); +* // returns 8.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'lower', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = realf( z ); +* // returns 0.0 +* +* v = imagf( z ); +* // returns 0.0 +* +* z = B.get( 2 ); +* // returns +* +* v = realf( z ); +* // returns 5.0 +* +* v = imagf( z ); +* // returns 6.0 +* +* z = B.get( 3 ); +* // returns +* +* v = realf( z ); +* // returns 7.0 +* +* v = imagf( z ); +* // returns 8.0 +*/ +function clacpy( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var viewA; + var viewB; + + // Reinterpret the input and output arrays as real-valued arrays of interleaved real and imaginary components: + viewA = reinterpret( A, 0 ); + viewB = reinterpret( B, 0 ); + + // Adjust the strides and offsets accordingly: + strideA1 *= 2; + strideA2 *= 2; + strideB1 *= 2; + strideB2 *= 2; + + offsetA *= 2; + offsetB *= 2; + + if ( uplo === 'upper' ) { + copyUpper( M, N, viewA, strideA1, strideA2, offsetA, viewB, strideB1, strideB2, offsetB ); + } else if ( uplo === 'lower' ) { + copyLower( M, N, viewA, strideA1, strideA2, offsetA, viewB, strideB1, strideB2, offsetB ); + } else { + copyAll( M, N, viewA, strideA1, strideA2, offsetA, viewB, strideB1, strideB2, offsetB ); + } + return B; +} + + +// EXPORTS // + +module.exports = clacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/lib/clacpy.js b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/clacpy.js new file mode 100644 index 000000000000..71fa0c403747 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/clacpy.js @@ -0,0 +1,152 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); +var format = require( '@stdlib/string/format' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Copies all or part of a matrix `A` to another matrix `B`. +* +* @param {string} order - storage layout of `A` and `B` +* @param {string} uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex64Array} A - input matrix +* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @param {Complex64Array} B - output matrix +* @param {PositiveInteger} LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) +* @throws {TypeError} first argument must be a valid order +* @throws {RangeError} sixth argument must be greater than or equal to `N` +* @throws {RangeError} eighth argument must be greater than or equal to `N` +* @returns {Complex64Array} `B` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'row-major', 'upper', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* z = B.get( 2 ); +* // returns +* +* v = realf( z ); +* // returns 0.0 +* +* v = imagf( z ); +* // returns 0.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'row-major', 'lower', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = realf( z ); +* // returns 0.0 +* +* v = imagf( z ); +* // returns 0.0 +*/ +function clacpy( order, uplo, M, N, A, LDA, B, LDB ) { + var sa1; + var sa2; + var sb1; + var sb2; + if ( !isLayout( order ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); + } + if ( order === 'column-major' ) { + sa1 = 1; + sa2 = LDA; + sb1 = 1; + sb2 = LDB; + } else { // order === 'row-major' + if ( LDA < N ) { + throw new RangeError( format( 'invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.', N, LDA ) ); + } + if ( LDB < N ) { + throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.', N, LDB ) ); + } + sa1 = LDA; + sa2 = 1; + sb1 = LDB; + sb2 = 1; + } + return base( uplo, M, N, A, sa1, sa2, 0, B, sb1, sb2, 0 ); +} + + +// EXPORTS // + +module.exports = clacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/lib/index.js b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/index.js new file mode 100644 index 000000000000..5bb151065ecd --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/index.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK routine to copy all or part of a matrix `A` to another matrix `B`. +* +* @module @stdlib/lapack/base/clacpy +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var clacpy = require( '@stdlib/lapack/base/clacpy' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex64Array( 4 ); +* +* clacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = realf( z ); +* // returns 1.0 +* +* v = imagf( z ); +* // returns 2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var clacpy = require( '@stdlib/lapack/base/clacpy' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex64Array( 12 ); +* +* clacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var clacpy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + clacpy = main; +} else { + clacpy = tmp; +} + + +// EXPORTS // + +module.exports = clacpy; + +// exports: { "ndarray": "clacpy.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/lib/main.js b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/main.js new file mode 100644 index 000000000000..27a91924eef1 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var clacpy = require( './clacpy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( clacpy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = clacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/ndarray.js new file mode 100644 index 000000000000..10755cee242e --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/lib/ndarray.js @@ -0,0 +1,126 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var base = require( './base.js' ); + + +// MAIN // + +/** +* Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics. +* +* @param {string} uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex64Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Complex64Array} B - output matrix +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Complex64Array} `B` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex64Array( 12 ); +* +* clacpy( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex64Array( 12 ); +* +* clacpy( 'upper', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +* +* z = B.get( 4 ); +* // returns +* +* v = realf( z ); +* // returns 0.0 +* +* v = imagf( z ); +* // returns 0.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex64Array( 12 ); +* +* clacpy( 'lower', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = realf( z ); +* // returns 3.0 +* +* v = imagf( z ); +* // returns 4.0 +* +* z = B.get( 1 ); +* // returns +* +* v = realf( z ); +* // returns 0.0 +* +* v = imagf( z ); +* // returns 0.0 +*/ +function clacpy( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { // eslint-disable-line max-len, max-params + return base( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = clacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/package.json b/lib/node_modules/@stdlib/lapack/base/clacpy/package.json new file mode 100644 index 000000000000..ae90a2aad64d --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/lapack/base/clacpy", + "version": "0.0.0", + "description": "Copy all or part of a matrix A to another matrix B.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "clacpy", + "copy", + "linear", + "algebra", + "subroutines", + "array", + "ndarray", + "matrix", + "complex64", + "complex64array" + ] +} diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.clacpy.js b/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.clacpy.js new file mode 100644 index 000000000000..8f230352ac4e --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.clacpy.js @@ -0,0 +1,283 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var clacpy = require( './../lib/clacpy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof clacpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( clacpy.length, 8, 'returns expected value' ); + t.end(); +}); + +tape( 'the function throws an error if provided an invalid first argument', function test( t ) { + var values; + var A; + var B; + var i; + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + + A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + B = new Complex64Array( 4 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + clacpy( value, 'all', 2, 2, A, 2, B, 2 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid sixth argument (row-major)', function test( t ) { + var values; + var A; + var B; + var i; + + values = [ + 0, + 1 + ]; + + A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + B = new Complex64Array( 4 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + clacpy( 'row-major', 'all', 2, 2, A, value, B, 2 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid eighth argument (row-major)', function test( t ) { + var values; + var A; + var B; + var i; + + values = [ + 0, + 1 + ]; + + A = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + B = new Complex64Array( 4 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + clacpy( 'row-major', 'all', 2, 2, A, 2, B, value ); + }; + } +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (row-major)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex64Array( M*N ); + + out = clacpy( 'row-major', 'all', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (row-major, upper)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex64Array( M*N ); + + out = clacpy( 'row-major', 'lower', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + + out = clacpy( 'row-major', 'upper', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (row-major, lower)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex64Array( M*N ); + + out = clacpy( 'row-major', 'upper', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + + out = clacpy( 'row-major', 'lower', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (column-major)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex64Array( M*N ); + + out = clacpy( 'column-major', 'all', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (column-major, upper)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex64Array( M*N ); + + out = clacpy( 'column-major', 'lower', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + + out = clacpy( 'column-major', 'upper', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (column-major, lower)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float32' + }; + + A = new Complex64Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex64Array( M*N ); + + out = clacpy( 'column-major', 'upper', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + + out = clacpy( 'column-major', 'lower', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.js b/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.js new file mode 100644 index 000000000000..271623ab9c49 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var clacpy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof clacpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof clacpy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var clacpy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( clacpy, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var clacpy; + var main; + + main = require( './../lib/clacpy.js' ); + + clacpy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( clacpy, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.ndarray.js new file mode 100644 index 000000000000..27f2120094f0 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/clacpy/test/test.ndarray.js @@ -0,0 +1,270 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var clacpy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof clacpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 11', function test( t ) { + t.strictEqual( clacpy.length, 11, 'returns expected value' ); + t.end(); +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (row-major)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0] ); + + out = clacpy( 'all', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 22.0, 23.0, 20.0, 21.0, 18.0, 19.0, 16.0, 17.0, 14.0, 15.0, 12.0, 13.0 ] ); + + out = clacpy( 'all', 2, 3, A, -3, -1, 6, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'all', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major, upper)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 0.0, 0.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'upper', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 22.0, 23.0, 20.0, 21.0, 18.0, 19.0, 0.0, 0.0, 14.0, 15.0, 12.0, 13.0 ] ); + + out = clacpy( 'upper', 2, 3, A, -3, -1, 6, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 0.0, 0.0, 18.0, 19.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = clacpy( 'upper', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok(isSameComplex64Array(out, expected), 'returns expected value'); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major, lower)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 20.0, 21.0, 0.0, 0.0 ] ); + + out = clacpy( 'lower', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok(isSameComplex64Array(out, expected), 'returns expected value'); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 0.0, 0.0 ] ); + + out = clacpy( 'lower', 2, 3, A, -3, 1, 4, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'lower', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + t.end(); +}); +tape( 'the function copies all of a matrix `A` to another matrix `B` (column-major)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'all', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 22.0, 23.0, 20.0, 21.0, 18.0, 19.0, 16.0, 17.0, 14.0, 15.0, 12.0, 13.0 ] ); + + out = clacpy( 'all', 2, 3, A, 1, 2, 1, B, -1, -2, 8 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'all', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (column-major, upper)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'upper', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 18.0, 19.0, 16.0, 17.0, 22.0, 23.0, 20.0, 21.0 ] ); + + out = clacpy( 'upper', 2, 3, A, 1, 2, 1, B, -1, 2, 4 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 20.0, 21.0, 0.0, 0.0 ] ); + + out = clacpy( 'upper', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (column-major, lower)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 0.0, 0.0, 18.0, 19.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = clacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 12.0, 13.0, 14.0, 15.0 ] ); + + out = clacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, -2, 7 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + A = new Complex64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 0.0, 0.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = clacpy( 'lower', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (column-major, lower, complex access patterns)', function test( t ) { + var out; + var A; + var B; + + /* eslint-disable array-element-newline, no-multi-spaces */ + + A = new Complex64Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 1, 2, 999, 999, 3, 4, 999, 999, 5, 6, + 999, 999, 7, 8, 999, 999, 9, 10, 999, 999, 11, 12, + 999, 999, 13, 14, 999, 999, 15, 16, 999, 999, 17, 18, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + B = new Complex64Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + + /* eslint-enable array-element-newline, no-multi-spaces */ + + out = clacpy( 'all', 3, 3, A, 2, 6, 7, B, 2, 6, 7 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex64Array( out, A ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/claset/README.md b/lib/node_modules/@stdlib/lapack/base/claset/README.md new file mode 100644 index 000000000000..f60e15a96a80 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/README.md @@ -0,0 +1,333 @@ + + +# claset + +> Set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. + +
+ +## Usage + +```javascript +var claset = require( '@stdlib/lapack/base/claset' ); +``` + +#### claset( order, uplo, M, N, alpha, beta, A, LDA ) + +Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var A = new Complex64Array( 4 ); + +var alpha = new Complex64( 1.0, 2.0 ); +var beta = new Complex64( 3.0, 4.0 ); + +claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); + +var z = A.get( 0 ); +// returns + +var re = realf( z ); +// returns 3.0 + +var im = imagf( z ); +// returns 4.0 + +z = A.get( 1 ); +// returns + +re = realf( z ); +// returns 1.0 + +im = imagf( z ); +// returns 2.0 +``` + +The function has the following parameters: + +- **order**: storage layout. +- **uplo**: specifies whether to set the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **alpha**: value assigned to off-diagonal elements. +- **beta**: value assigned to diagonal elements. +- **A**: input [`Complex64Array`][@stdlib/array/complex64]. +- **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`). + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +// Initial array: +var A0 = new Complex64Array( 5 ); + +// Create offset view: +var A1 = new Complex64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var alpha = new Complex64( 1.0, 2.0 ); +var beta = new Complex64( 3.0, 4.0 ); + +claset( 'row-major', 'all', 2, 2, alpha, beta, A1, 2 ); + +var z = A0.get( 1 ); +// returns + +var re = realf( z ); +// returns 3.0 + +var im = imagf( z ); +// returns 4.0 +``` + +#### claset.ndarray( uplo, M, N, alpha, beta, A, sa1, sa2, oa ) + +Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var A = new Complex64Array( 4 ); + +var alpha = new Complex64( 1.0, 2.0 ); +var beta = new Complex64( 3.0, 4.0 ); + +claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); + +var z = A.get( 0 ); +// returns + +var re = realf( z ); +// returns 3.0 + +var im = imagf( z ); +// returns 4.0 + +z = A.get( 1 ); +// returns + +re = realf( z ); +// returns 1.0 + +im = imagf( z ); +// returns 2.0 +``` + +The function has the following parameters: + +- **uplo**: specifies whether to set the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **alpha**: value assigned to off-diagonal elements. +- **beta**: value assigned to diagonal elements. +- **A**: input [`Complex64Array`][@stdlib/array/complex64]. +- **sa1**: stride of the first dimension of `A`. +- **sa2**: stride of the second dimension of `A`. +- **oa**: starting index for `A`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var A = new Complex64Array( 5 ); + +var alpha = new Complex64( 1.0, 2.0 ); +var beta = new Complex64( 3.0, 4.0 ); + +claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); + +var z = A.get( 0 ); +// returns + +var re = realf( z ); +// returns 0.0 + +var im = imagf( z ); +// returns 0.0 + +z = A.get( 1 ); +// returns + +re = realf( z ); +// returns 3.0 + +im = imagf( z ); +// returns 4.0 +``` + +
+ + + +
+ +## Notes + +- `claset()` corresponds to the [LAPACK][lapack] routine [`claset`][lapack-claset]. + +
+ + + +
+ +## Examples + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var claset = require( '@stdlib/lapack/base/claset' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex64Array( N ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var alpha = new Complex64( 1.0, 2.0 ); +var beta = new Complex64( 3.0, 4.0 ); + +claset( order, 'all', shape[ 0 ], shape[ 1 ], alpha, beta, A, strides[ 0 ] ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +TODO +``` + +#### TODO + +TODO. + +```c +TODO +``` + +TODO + +```c +TODO +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +TODO +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: https://www.netlib.org/lapack/explore-html/ + +[lapack-claset]: https://www.netlib.org/lapack/explore-html/d0/de5/group__laset_ga7149b3d5cf0e2b410d4664110a43139f.html#ga7149b3d5cf0e2b410d4664110a43139f + +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/claset/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/claset/benchmark/benchmark.js new file mode 100644 index 000000000000..ee0a861b67a6 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/benchmark/benchmark.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var claset = require( './../lib/claset.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var alpha; + var beta; + var abuf; + var A; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + abuf = new Float32Array( N*N*2 ); + A = new Complex64Array( abuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + claset( 'column-major', 'all', N, N, alpha, beta, A, N ); + if ( isnanf( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+'::equidimensional:order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/claset/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/claset/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..ea333566f854 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/benchmark/benchmark.ndarray.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var claset = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var alpha; + var beta; + var abuf; + var A; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + abuf = new Float32Array( N*N*2 ); + A = new Complex64Array( abuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + claset( 'all', N, N, alpha, beta, A, 1, N, 0 ); + if ( isnanf( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+'::equidimensional:ndarray:order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/claset/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/claset/docs/repl.txt new file mode 100644 index 000000000000..974d0ce3e14f --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/docs/repl.txt @@ -0,0 +1,113 @@ + +{{alias}}( order, uplo, M, N, alpha, beta, A, LDA ) + Sets the off-diagonal elements and the diagonal elements of a single- + precision complex floating-point matrix `A` to specified values. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + Parameters + ---------- + order: string + Row-major (C-style) or column-major (Fortran-style) order. Must be + either 'row-major' or 'column-major'. + + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + alpha: Complex64 + Value assigned to off-diagonal elements. + + beta: Complex64 + Value assigned to diagonal elements. + + A: Complex64Array + Input matrix `A`. + + LDA: integer + Stride of the first dimension of `A` (a.k.a., leading dimension of the + matrix `A`). + + Returns + ------- + A: Complex64Array + Input matrix. + + Examples + -------- + > var A = new {{alias:@stdlib/array/complex64}}( 4 ); + > var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 2.0 ); + > var beta = new {{alias:@stdlib/complex/float32/ctor}}( 3.0, 4.0 ); + > {{alias}}( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); + > var z = A.get( 0 ); + > {{alias:@stdlib/complex/float32/real}}( z ) + 3.0 + > {{alias:@stdlib/complex/float32/imag}}( z ) + 4.0 + + +{{alias}}.ndarray( uplo, M, N, alpha, beta, A, sa1, sa2, oa ) + Sets the off-diagonal elements and the diagonal elements of a single- + precision complex floating-point matrix `A` to specified values using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + alpha: Complex64 + Value assigned to off-diagonal elements. + + beta: Complex64 + Value assigned to diagonal elements. + + A: Complex64Array + Input matrix `A`. + + sa1: integer + Stride of the first dimension of `A`. + + sa2: integer + Stride of the second dimension of `A`. + + oa: integer + Starting index for `A`. + + Returns + ------- + A: Complex64Array + Input matrix. + + Examples + -------- + > var A = new {{alias:@stdlib/array/complex64}}( 5 ); + > var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 2.0 ); + > var beta = new {{alias:@stdlib/complex/float32/ctor}}( 3.0, 4.0 ); + > {{alias}}.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); + > var z = A.get( 1 ); + > {{alias:@stdlib/complex/float32/real}}( z ) + 3.0 + > {{alias:@stdlib/complex/float32/imag}}( z ) + 4.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/lapack/base/claset/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/claset/docs/types/index.d.ts new file mode 100644 index 000000000000..6196d421765d --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/docs/types/index.d.ts @@ -0,0 +1,127 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex64Array } from '@stdlib/types/array'; +import { Complex64 } from '@stdlib/types/complex'; +import { Layout } from '@stdlib/types/blas'; + +/** +* Interface describing `claset`. +*/ +interface Routine { + /** + * Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. + * + * @param order - storage layout of `A` + * @param uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param alpha - value assigned to off-diagonal elements + * @param beta - value assigned to diagonal elements + * @param A - input matrix + * @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) + * @returns `A` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * + * var A = new Complex64Array( 4 ); + * + * var alpha = new Complex64( 1.0, 2.0 ); + * var beta = new Complex64( 3.0, 4.0 ); + * + * claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); + * // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] + */ + ( order: Layout, uplo: string, M: number, N: number, alpha: Complex64, beta: Complex64, A: Complex64Array, LDA: number ): Complex64Array; + + /** + * Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values using alternative indexing semantics. + * + * @param uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param alpha - value assigned to off-diagonal elements + * @param beta - value assigned to diagonal elements + * @param A - input matrix + * @param strideA1 - stride of the first dimension of `A` + * @param strideA2 - stride of the second dimension of `A` + * @param offsetA - starting index for `A` + * @returns `A` + * + * @example + * var Complex64Array = require( '@stdlib/array/float32' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * + * var A = new Complex64Array( 4 ); + * + * var alpha = new Complex64( 1.0, 2.0 ); + * var beta = new Complex64( 3.0, 4.0 ); + * + * claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); + * // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] + */ + ndarray( uplo: string, M: number, N: number, alpha: Complex64, beta: Complex64, A: Complex64Array, strideA1: number, strideA2: number, offsetA: number ): Complex64Array; +} + +/** +* Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. +* +* @param order - storage layout of `A` +* @param uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param M - number of rows in matrix `A` +* @param N - number of columns in matrix `A` +* @param alpha - value assigned to off-diagonal elements +* @param beta - value assigned to diagonal elements +* @param A - input matrix +* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @returns `A` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var A = new Complex64Array( 5 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset.ndarray( 'all', 2, 2, A, 2, 1, 1 ); +* // A => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +*/ +declare var claset: Routine; + + +// EXPORTS // + +export = claset; diff --git a/lib/node_modules/@stdlib/lapack/base/claset/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/claset/docs/types/test.ts new file mode 100644 index 000000000000..f834d4c97441 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/docs/types/test.ts @@ -0,0 +1,348 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import Complex64 = require( '@stdlib/complex/float32/ctor' ); +import claset = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a string... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 5, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( true, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( false, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( null, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( void 0, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( [], 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( {}, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( ( x: number ): number => x, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a string... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 5, 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', true, 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', false, 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', null, 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', void 0, 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', [], 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', {}, 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', ( x: number ): number => x, 2, 2, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 'all', '5', 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', true, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', false, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', null, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', void 0, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', [], 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', {}, 2, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', ( x: number ): number => x, 2, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 'all', 2, '5', alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, true, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, false, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, null, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, void 0, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, [], alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, {}, alpha, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, ( x: number ): number => x, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a complex number... +{ + const A = new Complex64Array( 4 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 'all', 2, 2, '5', beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, 5, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, true, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, false, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, null, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, void 0, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, [], beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, {}, beta, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, ( x: number ): number => x, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a complex number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + + claset( 'row-major', 'all', 2, 2, alpha, '5', A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, true, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, false, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, null, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, void 0, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, [], A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, {}, A, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, ( x: number ): number => x, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a Complex64Array... +{ + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 'all', 2, 2, alpha, beta, '5', 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, 5, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, true, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, false, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, null, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, void 0, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, [], 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, {}, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, ( x: number ): number => x, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset( 'row-major', 'all', 2, 2, alpha, beta, A, '5' ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, true ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, false ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, null ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, void 0 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, [] ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, {} ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset(); // $ExpectError + claset( 'row-major' ); // $ExpectError + claset( 'row-major', 'all' ); // $ExpectError + claset( 'row-major', 'all', 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2 ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A ); // $ExpectError + claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2, 3 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex64Array... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a string... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 5, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( true, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( false, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( null, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( void 0, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( [], 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( {}, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( ( x: number ): number => x, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', '5', 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', true, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', false, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', null, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', void 0, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', [], 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', {}, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', ( x: number ): number => x, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, '5', alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, true, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, false, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, null, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, void 0, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, [], alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, {}, alpha, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, ( x: number ): number => x, alpha, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a complex number... +{ + const A = new Complex64Array( 4 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, '5', beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, 5, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, true, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, false, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, null, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, void 0, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, [], beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, {}, beta, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, ( x: number ): number => x, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a complex number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, alpha, '5', A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, 5, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, true, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, false, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, null, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, void 0, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, [], A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, {}, A, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, ( x: number ): number => x, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Complex64Array... +{ + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, alpha, beta, '5', 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, 5, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, true, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, false, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, null, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, void 0, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, [], 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, {}, 2, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, ( x: number ): number => x, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, alpha, beta, A, '5', 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, true, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, false, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, null, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, void 0, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, [], 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, {}, 1, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, '5', 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, true, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, false, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, null, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, void 0, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, [], 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, {}, 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a number... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, '5' ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, true ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, false ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, null ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, void 0 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, [] ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, {} ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const A = new Complex64Array( 4 ); + const alpha = new Complex64( 1.0, 2.0 ); + const beta = new Complex64( 3.0, 4.0 ); + + claset.ndarray(); // $ExpectError + claset.ndarray( 'all' ); // $ExpectError + claset.ndarray( 'all', 2 ); // $ExpectError + claset.ndarray( 'all', 2, 2 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1 ); // $ExpectError + claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0, 3 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/claset/examples/index.js b/lib/node_modules/@stdlib/lapack/base/claset/examples/index.js new file mode 100644 index 000000000000..a8a892db368c --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var claset = require( './../lib' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex64Array( N ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var alpha = new Complex64( 1.0, 2.0 ); +var beta = new Complex64( 3.0, 4.0 ); + +claset( order, 'all', shape[ 0 ], shape[ 1 ], alpha, beta, A, strides[ 0 ] ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); diff --git a/lib/node_modules/@stdlib/lapack/base/claset/lib/base.js b/lib/node_modules/@stdlib/lapack/base/claset/lib/base.js new file mode 100644 index 000000000000..88149428e120 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/lib/base.js @@ -0,0 +1,630 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); +var min = require( '@stdlib/math/base/special/fast/min' ); + + +// FUNCTIONS // + +/** +* Sets the diagonal of a single-precision complex floating-point matrix `A` to a specified value. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float32Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float32Array} `A` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* setDiagonal( 2, 3, 1.0, 2.0, A, 6, 2, 0 ); +* // A => [ 1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 0.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* setDiagonal( 2, 2, 1.0, 2.0, A, 4, 2, 0 ); +* // A => [ 1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* setDiagonal( 3, 2, 1.0, 2.0, A, 4, 2, 0 ); +* // A => [ 1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ] +*/ +function setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ) { + var sa; + var ia; + var i; + + sa = strideA1 + strideA2; + ia = offsetA; + for ( i = 0; i < min( M, N ); i++ ) { + A[ ia ] = breal; + A[ ia+1 ] = bimag; + ia += sa; + } + return A; +} + +/** +* Sets all elements of a single-precision complex floating-point matrix `A` to specified values. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} areal - real component of the value to assign to off-diagonal elements +* @param {number} aimag - imaginary component of the value to assign to off-diagonal elements +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float32Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float32Array} `A` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, 2, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, -2, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, 2, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, -2, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, 4, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, 4, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, -4, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, -4, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +*/ +function setAll( M, N, areal, aimag, breal, bimag, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len + var da0; + var da1; + var sh; + var S0; + var S1; + var sa; + var ia; + var i0; + var i1; + var o; + + // Resolve the loop interchange order: + o = loopOrder( [ M, N ], [ strideA1, strideA2 ] ); + sh = o.sh; + sa = o.sx; + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + da0 = sa[ 0 ]; + da1 = sa[ 1 ] - ( S0*sa[0] ); + + // Set the pointer to the first indexed element: + ia = offsetA; + + // Fill the array with a scalar value... + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + A[ ia ] = areal; + A[ ia+1 ] = aimag; + ia += da0; + } + ia += da1; + } + // Replace the diagonal: + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + + return A; +} + +/** +* Sets the upper triangular/trapezoidal part of a single-precision complex floating-point matrix `A` to specified values. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} areal - real component of the value to assign to off-diagonal elements +* @param {number} aimag - imaginary component of the value to assign to off-diagonal elements +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float32Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float32Array} `A` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, 2, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, -2, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, 2, 4 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, -2, 6 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, 4, 0 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, 4, 2 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, -4, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, -4, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +*/ +function setUpper( M, N, areal, aimag, breal, bimag, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len + var idx; + var ia; + var i0; + var i1; + + ia = offsetA; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + idx = ia + ( i1*strideA2 ); + for ( i0 = i1; i0 < N; i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA2; + } + ia += strideA1; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; + } + for ( i1 = 0; i1 < N; i1++ ) { + idx = ia; + for ( i0 = 0; i0 <= min( i1, M-1 ); i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA1; + } + ia += strideA2; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; +} + +/** +* Sets the lower triangular/trapezoidal part of a single-precision complex floating-point matrix `A` to specified values. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} areal - real component of the value to assign to off-diagonal elements +* @param {number} aimag - imaginary component of the value to assign to off-diagonal elements +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float32Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float32Array} `A` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, 2, 0 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, -2, 2 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, 2, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, -2, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, 4, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, 4, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, -4, 4 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var A = new Float32Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, -4, 6 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +*/ +function setLower( M, N, areal, aimag, breal, bimag, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len + var idx; + var ia; + var i0; + var i1; + + ia = offsetA; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + idx = ia; + for ( i0 = 0; i0 <= min( i1, N-1 ); i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA2; + } + ia += strideA1; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; + } + for ( i1 = 0; i1 < N; i1++ ) { + idx = ia + ( i1*strideA1 ); + for ( i0 = i1; i0 < M; i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA1; + } + ia += strideA2; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; +} + + +// MAIN // + +/** +* Sets elements of matrix `A` to specified values. +* +* @private +* @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex64} alpha - value assigned to off-diagonal elements +* @param {Complex64} beta - value assigned to diagonal elements +* @param {Complex64Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Complex64Array} `A` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'upper', 2, 2, alpha, beta, A, 2, 1, 0 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 0.0 +* +* im = imagf( z ); +* // returns 0.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'lower', 2, 2, alpha, beta, A, 2, 1, 0 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = realf( z ); +* // returns 0.0 +* +* im = imagf( z ); +* // returns 0.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +*/ +function claset( uplo, M, N, alpha, beta, A, strideA1, strideA2, offsetA ) { + var viewA; + var ar; + var ai; + var br; + var bi; + + // Reinterpret the input array as a real-valued array of interleaved real and imaginary components: + viewA = reinterpret( A, 0 ); + + // Adjust the strides and offset accordingly: + strideA1 *= 2; + strideA2 *= 2; + + offsetA *= 2; + + // Decompose the scalars to real and imaginary components: + ar = realf( alpha ); + ai = imagf( alpha ); + br = realf( beta ); + bi = imagf( beta ); + + if ( uplo === 'upper' ) { + setUpper( M, N, ar, ai, br, bi, viewA, strideA1, strideA2, offsetA ); + } else if ( uplo === 'lower' ) { + setLower( M, N, ar, ai, br, bi, viewA, strideA1, strideA2, offsetA ); + } else { + setAll( M, N, ar, ai, br, bi, viewA, strideA1, strideA2, offsetA ); + } + return A; +} + + +// EXPORTS // + +module.exports = claset; diff --git a/lib/node_modules/@stdlib/lapack/base/claset/lib/claset.js b/lib/node_modules/@stdlib/lapack/base/claset/lib/claset.js new file mode 100644 index 000000000000..05a316016d27 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/lib/claset.js @@ -0,0 +1,187 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); +var format = require( '@stdlib/string/format' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. +* +* @param {string} order - storage layout of `A` +* @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex64} alpha - value assigned to off-diagonal elements +* @param {Complex64} beta - value assigned to diagonal elements +* @param {Complex64Array} A - input matrix +* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @throws {TypeError} first argument must be a valid order +* @throws {RangeError} eighth argument must be greater than or equal to `N` +* @returns {Complex64Array} `A` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'row-major', 'upper', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 0.0 +* +* im = imagf( z ); +* // returns 0.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 4 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'row-major', 'lower', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = realf( z ); +* // returns 0.0 +* +* im = imagf( z ); +* // returns 0.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +*/ +function claset( order, uplo, M, N, alpha, beta, A, LDA ) { + var sa1; + var sa2; + if ( !isLayout( order ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); + } + if ( order === 'column-major' ) { + sa1 = 1; + sa2 = LDA; + } else { // order === 'row-major' + if ( LDA < N ) { + throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.', N, LDA ) ); + } + sa1 = LDA; + sa2 = 1; + } + return base( uplo, M, N, alpha, beta, A, sa1, sa2, 0 ); +} + + +// EXPORTS // + +module.exports = claset; diff --git a/lib/node_modules/@stdlib/lapack/base/claset/lib/index.js b/lib/node_modules/@stdlib/lapack/base/claset/lib/index.js new file mode 100644 index 000000000000..f936983e4ac9 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/lib/index.js @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK routine to set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. +* +* @module @stdlib/lapack/base/claset +* +* @example +* var Complex64Array = require( '@stdlib/array/float32' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var claset = require( '@stdlib/lapack/base/claset' ); +* +* var A = new Complex64Array( 4 ); +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ) +* // returns 4.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/float32' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var claset = require( '@stdlib/lapack/base/claset' ); +* +* var A = new Complex64Array( 5 ); +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var claset; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + claset = main; +} else { + claset = tmp; +} + + +// EXPORTS // + +module.exports = claset; + +// exports: { "ndarray": "claset.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/claset/lib/main.js b/lib/node_modules/@stdlib/lapack/base/claset/lib/main.js new file mode 100644 index 000000000000..8aaa0211fff4 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var claset = require( './claset.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( claset, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = claset; diff --git a/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js new file mode 100644 index 000000000000..54007def2f97 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js @@ -0,0 +1,167 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var base = require( './base.js' ); + + +// MAIN // + +/** +* Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. +* +* @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex64} alpha - value assigned to off-diagonal elements +* @param {Complex64} beta - value assigned to diagonal elements +* @param {Complex64Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Complex64Array} `A` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 5 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* z = A.get( 3 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var A = new Complex64Array( 5 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'upper', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +* +* z = A.get( 3 ); +* // returns +* +* re = realf( z ); +* // returns 0.0 +* +* im = imagf( z ); +* // returns 0.0 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* var A = new Complex64Array( 5 ); +* +* var alpha = new Complex64( 1.0, 2.0 ); +* var beta = new Complex64( 3.0, 4.0 ); +* +* claset( 'lower', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = realf( z ); +* // returns 3.0 +* +* var im = imagf( z ); +* // returns 4.0 +* +* z = A.get( 2 ); +* // returns +* +* re = realf( z ); +* // returns 0.0 +* +* im = imagf( z ); +* // returns 0.0 +* +* z = A.get( 3 ); +* // returns +* +* re = realf( z ); +* // returns 1.0 +* +* im = imagf( z ); +* // returns 2.0 +*/ +function claset( uplo, M, N, alpha, beta, A, strideA1, strideA2, offsetA ) { + return base( uplo, M, N, alpha, beta, A, strideA1, strideA2, offsetA ); +} + + +// EXPORTS // + +module.exports = claset; diff --git a/lib/node_modules/@stdlib/lapack/base/claset/package.json b/lib/node_modules/@stdlib/lapack/base/claset/package.json new file mode 100644 index 000000000000..047809b2bdc9 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/lapack/base/claset", + "version": "0.0.0", + "description": "Set the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "claset", + "copy", + "linear", + "algebra", + "subroutines", + "array", + "ndarray", + "matrix", + "float32", + "float", + "float32array", + "complex", + "cmplx", + "complex64array" + ] +} diff --git a/lib/node_modules/@stdlib/lapack/base/claset/test/test.claset.js b/lib/node_modules/@stdlib/lapack/base/claset/test/test.claset.js new file mode 100644 index 000000000000..121cc5b3a1aa --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/test/test.claset.js @@ -0,0 +1,489 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var claset = require( './../lib/claset.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof claset, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( claset.length, 8, 'returns expected value' ); + t.end(); +}); + +tape( 'the function throws an error if provided an invalid first argument', function test( t ) { + var values; + var alpha; + var beta; + var A; + var i; + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + + A = new Complex64Array( 4 ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + claset( value, 'all', 2, 2, alpha, beta, A, 2 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid eighth argument (row-major)', function test( t ) { + var values; + var alpha; + var beta; + var A; + var i; + + values = [ + 0, + 1 + ]; + + A = new Complex64Array( 4 ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + claset( 'row-major', 'all', 2, 2, alpha, beta, A, value ); + }; + } +}); + +tape( 'the function assigns values to matrix `A` (row-major, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'row-major', 'all', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'row-major', 'all', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, upper, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'row-major', 'upper', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, upper, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'row-major', 'upper', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, lower, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'row-major', 'lower', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, lower, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'row-major', 'lower', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'column-major', 'all', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'column-major', 'all', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, upper, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'column-major', 'upper', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, upper, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'column-major', 'upper', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'column-major', 'lower', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex64Array( M*N ); + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'column-major', 'lower', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/claset/test/test.js b/lib/node_modules/@stdlib/lapack/base/claset/test/test.js new file mode 100644 index 000000000000..b703b0798ced --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var claset = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof claset, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof claset.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var claset = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( claset, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var claset; + var main; + + main = require( './../lib/claset.js' ); + + claset = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( claset, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/claset/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/claset/test/test.ndarray.js new file mode 100644 index 000000000000..7d5e89df9f73 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/claset/test/test.ndarray.js @@ -0,0 +1,466 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var claset = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof claset, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 9', function test( t ) { + t.strictEqual( claset.length, 9, 'returns expected value' ); + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var M; + var N; + var A; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + M = 2; + N = 3; + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'all', 2, 3, alpha, beta, A, 3, 1, 1 ); + + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'all', 2, 3, alpha, beta, A, -3, -1, 6 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'all', 3, 2, alpha, beta, A, 2, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, upper)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var M; + var N; + var A; + + M = 3; + N = 2; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + A = new Complex64Array( ( M * N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'upper', 2, 3, alpha, beta, A, 3, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'upper', 2, 3, alpha, beta, A, 3, -1, 3 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'upper', 3, 2, alpha, beta, A, 2, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, lower)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'lower', 2, 3, alpha, beta, A, 3, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'lower', 2, 3, alpha, beta, A, -3, 1, 4 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'lower', 3, 2, alpha, beta, A, 2, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'all', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'all', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'all', 3, 2, alpha, beta, A, 1, 3, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, upper)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'upper', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'upper', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'upper', 3, 2, alpha, beta, A, 1, 3, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'lower', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'lower', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + A = new Complex64Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex64Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = claset( 'lower', 3, 2, alpha, beta, A, 1, 3, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower, complex access patterns)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + + alpha = new Complex64( 1.0, 2.0 ); + beta = new Complex64( 3.0, 4.0 ); + + /* eslint-disable array-element-newline, no-multi-spaces */ + + A = new Complex64Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + + expected = new Complex64Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 3, 4, 999, 999, 1, 2, 999, 999, 1, 2, + 999, 999, 1, 2, 999, 999, 3, 4, 999, 999, 1, 2, + 999, 999, 1, 2, 999, 999, 1, 2, 999, 999, 3, 4, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + + /* eslint-enable array-element-newline, no-multi-spaces */ + + out = claset( 'all', 3, 3, alpha, beta, A, 2, 6, 7 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/crot/README.md b/lib/node_modules/@stdlib/lapack/base/crot/README.md new file mode 100644 index 000000000000..cce8cef9b535 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/README.md @@ -0,0 +1,299 @@ + + +# crot + +> Apply a plane rotation with real cosine and complex sine to a pair of single-precision complex floating-point vectors. + +
+ +## Usage + +```javascript +var crot = require( '@stdlib/lapack/base/crot' ); +``` + +#### crot( N, cx, strideCX, cy, strideCY, c, s ) + +Applies a plane rotation with real cosine and complex sine. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex64( 0.0, 0.75 ); + +crot( cx.length, cx, 1, cy, 1, 1.25, s ); + +var z = cy.get( 0 ); +// returns + +var re = realf( z ); +// returns ~-1.5 + +var im = imagf( z ); +// returns ~0.75 + +z = cx.get( 0 ); +// returns + +re = realf( z ); +// returns ~1.25 + +im = imagf( z ); +// returns ~2.5 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **cx**: first input [`Complex64Array`][@stdlib/array/complex64]. +- **strideCX**: stride length for `cx`. +- **cy**: second input [`Complex64Array`][@stdlib/array/complex64]. +- **strideCY**: stride length for `cy`. + +The `N` and stride parameters determine how values from `cx` and `cy` are accessed at runtime. For example, to apply a plane rotation to every other element, + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex64( 0.0, 0.75 ); + +crot( 2, cx, 2, cy, 2, 1.25, s ); + +var z = cy.get( 0 ); +// returns + +var re = realf( z ); +// returns ~-1.5 + +var im = imagf( z ); +// returns ~0.75 + +z = cx.get( 0 ); +// returns + +re = realf( z ); +// returns ~1.25 + +im = imagf( z ); +// returns ~2.5 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +// Initial arrays... +var cx0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var cy0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var cy1 = new Complex64Array( cy0.buffer, cy0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +var s = new Complex64( 0.0, 0.75 ); + +crot( 2, cx1, -2, cy1, 1, 1.25, s ); + +var z = cy0.get( 2 ); +// returns + +var re = realf( z ); +// returns ~-6 + +var im = imagf( z ); +// returns ~5.25 + +z = cx0.get( 3 ); +// returns + +re = realf( z ); +// returns ~8.75 + +im = imagf( z ); +// returns ~10 +``` + +#### crot.ndarray( N, cx, strideCX, offsetCX, cy, strideCY, offsetCY, c, s ) + +Applies a plane rotation with real cosine and complex sine using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex64( 0.0, 0.75 ); + +crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 1.25, s ); + +var z = cy.get( 0 ); +// returns + +var re = realf( z ); +// returns ~-1.5 + +var im = imagf( z ); +// returns ~0.75 + +z = cx.get( 0 ); +// returns + +re = realf( z ); +// returns ~1.25 + +im = imagf( z ); +// returns ~2.5 +``` + +The function has the following additional parameters: + +- **offsetCX**: starting index for `cx`. +- **offsetCY**: starting index for `cy`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to apply a plane rotation to every other element starting from the second element, + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + +var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex64( 0.0, 0.75 ); + +crot.ndarray( 2, cx, 2, 1, cy, 2, 1, 1.25, s ); + +var z = cy.get( 3 ); +// returns + +var re = realf( z ); +// returns ~-6.0 + +var im = imagf( z ); +// returns ~5.25 + +z = cx.get( 1 ); +// returns + +re = realf( z ); +// returns ~3.75 + +im = imagf( z ); +// returns ~5.0 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions leave `cx` and `cy` unchanged. +- `crot()` corresponds to the [LAPACK][lapack] routine [`crot`][crot]. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var ccopy = require( '@stdlib/blas/base/ccopy' ); +var zeros = require( '@stdlib/array/zeros' ); +var logEach = require( '@stdlib/console/log-each' ); +var crot = require( '@stdlib/lapack/base/crot' ); + +function rand() { + return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +// Generate random input arrays: +var cx = filledarrayBy( 10, 'complex64', rand ); +var cxc = ccopy( cx.length, cx, 1, zeros( cx.length, 'complex64' ), 1 ); + +var cy = filledarrayBy( 10, 'complex64', rand ); +var cyc = ccopy( cy.length, cy, 1, zeros( cy.length, 'complex64' ), 1 ); + +var s = new Complex64( 0.0, 0.75 ); + +// Apply a plane rotation: +crot( cx.length, cx, 1, cy, 1, 1.25, s ); + +// Print the results: +logEach( '(%s,%s) => (%s,%s)', cxc, cyc, cx, cy ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: http://www.netlib.org/lapack + +[crot]: https://netlib.org/lapack/explore-html/d1/d45/group__rot_ga25544801d45dcabdec7b24d863ebea9c.html#ga25544801d45dcabdec7b24d863ebea9c + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/crot/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/crot/benchmark/benchmark.js new file mode 100644 index 000000000000..e502a0377f71 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var pkg = require( './../package.json' ).name; +var crot = require( './../lib/crot.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var cx; + var cy; + var s; + + cx = new Complex64Array( uniform( len*2, -100.0, 100.0, options ) ); + cy = new Complex64Array( uniform( len*2, -100.0, 100.0, options ) ); + s = new Complex64( 0.6, 0.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var viewX; + var i; + + viewX = reinterpret( cx, 0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + crot( cx.length, cx, 1, cy, 1, 0.8, s ); + if ( isnanf( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/crot/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/crot/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..e28837bec023 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/benchmark/benchmark.ndarray.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var pkg = require( './../package.json' ).name; +var crot = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var cx; + var cy; + var s; + + cx = new Complex64Array( uniform( len*2, -100.0, 100.0, options ) ); + cy = new Complex64Array( uniform( len*2, -100.0, 100.0, options ) ); + s = new Complex64( 0.6, 0.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var viewX; + var i; + + viewX = reinterpret( cx, 0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + crot( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + if ( isnanf( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':ndarray:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/crot/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/crot/docs/repl.txt new file mode 100644 index 000000000000..e484df2fc8ef --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/docs/repl.txt @@ -0,0 +1,172 @@ + +{{alias}}( N, cx, strideCX, cy, strideCY, c, s ) + Applies a plane rotation with real cosine and complex sine. + + The `N` and stride parameters determine how values in the strided arrays are + accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N` is less than or equal to `0`, the vectors are unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + cx: Complex64Array + First input array. + + strideCX: integer + Index increment for `cx`. + + cy: Complex64Array + Second input array. + + strideCY: integer + Index increment for `cy`. + + c: number + Cosine of the angle of rotation. + + s: Complex64 + Sine of the angle of rotation. + + Returns + ------- + cy: Complex64Array + Input array `cy`. + + Examples + -------- + // Standard usage: + > var cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var cy = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float32/ctor}}( 0.3, 0.4 ); + > {{alias}}( cx.length, cx, 1, cy, 1, 0.8, s ); + > var z = cy.get( 0 ); + > var re = {{alias:@stdlib/complex/float32/real}}( z ) + ~-1.1 + > var im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~-0.2 + > z = cx.get( 0 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~0.8 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~1.6 + + // Advanced indexing: + > cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + > cy = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float32/ctor}}( 0.3, 0.4 ); + > {{alias}}( 2, cx, -2, cy, 1, 0.8, s ); + > z = cy.get( 0 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~-3.9 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~0.2 + > z = cx.get( 2 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~4.0 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~4.8 + + // Using typed array views: + > var cx0 = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var cy0 = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var cx1 = new {{alias:@stdlib/array/complex64}}( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); + > var cy1 = new {{alias:@stdlib/array/complex64}}( cy0.buffer, cy0.BYTES_PER_ELEMENT*2 ); + > var s = new {{alias:@stdlib/complex/float32/ctor}}( 0.3, 0.4 ); + > {{alias}}( 1, cx1, 1, cy1, 1, 0.8, s ); + > z = cy0.get( 2 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~-2.5 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~0.0 + > z = cx0.get( 1 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~2.4 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~3.2 + + +{{alias}}.ndarray( N, cx, strideCX, offsetCX, cy, strideCY, offsetCY, c, s ) + Applies a plane rotation with real cosine and complex sine using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + cx: Complex64Array + First input array. + + strideCX: integer + Index increment for `cx`. + + offsetCX: integer + Starting index for `cx`. + + cy: Complex64Array + Second input array. + + strideCY: integer + Index increment for `cy`. + + offsetCY: integer + Starting index for `cy`. + + c: number + Cosine of the angle of rotation. + + s: Complex64 + Sine of the angle of rotation. + + Returns + ------- + cy: Complex64Array + Input array `cy`. + + Examples + -------- + // Standard usage: + > var cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var cy = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float32/ctor}}( 0.3, 0.4 ); + > {{alias}}.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + > var z = cy.get( 0 ); + > var re = {{alias:@stdlib/complex/float32/real}}( z ) + ~-1.1 + > var im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~-0.2 + > z = cx.get( 0 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~0.8 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~1.6 + + // Advanced indexing: + > cx = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > cy = new {{alias:@stdlib/array/complex64}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float32/ctor}}( 0.3, 0.4 ); + > {{alias}}.ndarray( 1, cx, 2, 1, cy, 2, 1, 0.8, s ); + > z = cy.get( 1 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~-2.5 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~0.0 + > z = cx.get( 1 ); + > re = {{alias:@stdlib/complex/float32/real}}( z ) + ~2.4 + > im = {{alias:@stdlib/complex/float32/imag}}( z ) + ~3.2 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/lapack/base/crot/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/crot/docs/types/index.d.ts new file mode 100644 index 000000000000..6cb20023ff10 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/docs/types/index.d.ts @@ -0,0 +1,198 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex64Array } from '@stdlib/types/array'; +import { Complex64 } from '@stdlib/types/complex'; + +/** +* Interface describing `crot`. +*/ +interface Routine { + /** + * Applies a plane rotation with real cosine and complex sine. + * + * @param N - number of indexed elements + * @param cx - first input array + * @param strideCX - `cx` stride length + * @param cy - second input array + * @param strideCY - `cy` stride length + * @param c - cosine of the angle of rotation + * @param s - sine of the angle of rotation + * @returns `cy` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32' ); + * var realf = require( '@stdlib/complex/float32/real' ); + * var imagf = require( '@stdlib/complex/float32/imag' ); + * + * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * var s = new Complex64( 0.3, 0.4 ); + * + * crot( cx.length, cx, 1, cy, 1, 0.8, s ); + * + * var z = cy.get( 0 ); + * // returns + * + * var re = realf( z ); + * // returns ~-1.1 + * + * var im = imagf( z ); + * // returns ~-0.2 + * + * z = cx.get( 0 ); + * // returns + * + * re = realf( z ); + * // returns ~0.8 + * + * im = imagf( z ); + * // returns ~1.6 + */ + ( N: number, cx: Complex64Array, strideCX: number, cy: Complex64Array, strideCY: number, c: number, s: Complex64 ): Complex64Array; + + /** + * Applies a plane rotation with real cosine and complex sine using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param cx - first input array + * @param strideCX - `cx` stride length + * @param offsetCX - starting index for `cx` + * @param cy - second input array + * @param strideCY - `cy` stride length + * @param offsetCY - starting index for `cy` + * @param c - cosine of the angle of rotation + * @param s - sine of the angle of rotation + * @returns `cy` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32' ); + * var realf = require( '@stdlib/complex/float32/real' ); + * var imagf = require( '@stdlib/complex/float32/imag' ); + * + * var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * var s = new Complex64( 0.3, 0.4 ); + * + * crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + * + * var z = cy.get( 0 ); + * // returns + * + * var re = realf( z ); + * // returns ~-1.1 + * + * var im = imagf( z ); + * // returns ~-0.2 + * + * z = cx.get( 0 ); + * // returns + * + * re = realf( z ); + * // returns ~0.8 + * + * im = imagf( z ); + * // returns ~1.6 + */ + ndarray( N: number, cx: Complex64Array, strideCX: number, offsetCX: number, cy: Complex64Array, strideCY: number, offsetCY: number, c: number, s: Complex64 ): Complex64Array; +} + +/** +* Applies a plane rotation with real cosine and complex sine. +* +* @param N - number of indexed elements +* @param cx - first input array +* @param strideCX - `cx` stride length +* @param cy - second input array +* @param strideCY - `cy` stride length +* @param c - cosine of the angle of rotation +* @param s - sine of the angle of rotation +* @returns `cy` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex64( 0.3, 0.4 ); +* +* crot( 2, cx, 2, cy, 1, 0.8, s ); +* +* var z = cy.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns ~-1.1 +* +* var im = imagf( z ); +* // returns ~-0.2 +* +* z = cx.get( 0 ); +* // returns +* +* re = realf( z ); +* // returns ~0.8 +* +* im = imagf( z ); +* // returns ~1.6 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex64( 0.3, 0.4 ); +* +* crot.ndarray( 2, cx, 2, 0, cy, 1, 0, 0.8, s ); +* +* var z = cy.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns ~-1.1 +* +* var im = imagf( z ); +* // returns ~-0.2 +* +* z = cx.get( 0 ); +* // returns +* +* re = realf( z ); +* // returns ~0.8 +* +* im = imagf( z ); +* // returns ~1.6 +*/ +declare var crot: Routine; + + +// EXPORTS // + +export = crot; diff --git a/lib/node_modules/@stdlib/lapack/base/crot/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/crot/docs/types/test.ts new file mode 100644 index 000000000000..501d43df13a9 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/docs/types/test.ts @@ -0,0 +1,333 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import Complex64 = require( '@stdlib/complex/float32/ctor' ); +import crot = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( cx.length, cx, 1, cy, 1, 0.8, s ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( '10', cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( true, cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( false, cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( null, cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( undefined, cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( [], cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( {}, cx, 1, cy, 1, 0.8, s ); // $ExpectError + crot( ( cx: number ): number => cx, cx, 1, cy, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( cx.length, 10, 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, '10', 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, true, 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, false, 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, null, 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, undefined, 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, [ '1' ], 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, {}, 1, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, ( cx: number ): number => cx, 1, cy, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( cx.length, cx, '10', cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, true, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, false, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, null, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, undefined, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, [], cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, {}, cy, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, ( cx: number ): number => cx, cy, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( cx.length, cx, 1, 10, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, '10', 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, true, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, false, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, null, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, undefined, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, [ '1' ], 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, {}, 1, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, ( cx: number ): number => cx, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( cx.length, cx, 1, cy, '10', 0.8, 0.6 ); // $ExpectError + crot( cx.length, cx, 1, cy, true, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, cy, false, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, cy, null, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, cy, undefined, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, cy, [], 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, cy, {}, 0.8, s ); // $ExpectError + crot( cx.length, cx, 1, cy, ( cx: number ): number => cx, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot( cx.length, cx, 1, cy, 1, '10', s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, true, s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, false, s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, null, s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, undefined, s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, [], s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, {}, s ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, ( cx: number ): number => cx, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a complex number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + + crot( cx.length, cx, 1, cy, 1, 0.8, 0.6 ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, '10' ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, true ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, false ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, null ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, undefined ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, [] ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, {} ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, ( cx: number ): number => cx ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot(); // $ExpectError + crot( cx.length ); // $ExpectError + crot( cx.length, cx ); // $ExpectError + crot( cx.length, cx, 1 ); // $ExpectError + crot( cx.length, cx, 1, cy ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8 ); // $ExpectError + crot( cx.length, cx, 1, cy, 1, 0.8, s, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( '10', cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( true, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( false, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( null, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( undefined, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( [], cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( {}, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( ( cx: number ): number => cx, cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, 10, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, '10', 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, true, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, false, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, null, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, undefined, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, [ '1' ], 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, {}, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, ( cx: number ): number => cx, 1, 0, cy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, '10', 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, true, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, false, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, null, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, undefined, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, [], 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, {}, 0, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, ( cx: number ): number => cx, 0, cy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, 1, '10', cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, true, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, false, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, null, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, undefined, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, [], cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, {}, cy, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, ( cx: number ): number => cx, cy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Complex64Array... +{ + const cx = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, 1, 0, 10, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, '10', 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, true, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, false, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, null, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, undefined, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, [ '1' ], 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, {}, 1, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, ( cx: number ): number => cx, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, 1, 0, cy, '10', 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, true, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, false, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, null, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, undefined, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, [], 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, {}, 0, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, ( cx: number ): number => cx, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, 1, 0, cy, 1, '10', 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, true, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, false, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, null, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, undefined, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, [], 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, {}, 0.8, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, ( cx: number ): number => cx, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, '10', s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, true, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, false, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, null, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, undefined, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, [], s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, {}, s ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, ( cx: number ): number => cx, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a complex number... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, 0.6 ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, '10' ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, true ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, false ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, null ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, undefined ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, [] ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, {} ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, ( cx: number ): number => cx ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const cx = new Complex64Array( 10 ); + const cy = new Complex64Array( 10 ); + const s = new Complex64( 0.3, 0.4 ); + + crot.ndarray(); // $ExpectError + crot.ndarray( cx.length ); // $ExpectError + crot.ndarray( cx.length, cx ); // $ExpectError + crot.ndarray( cx.length, cx, 1 ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0 ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1 ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0 ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8 ); // $ExpectError + crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/crot/examples/index.js b/lib/node_modules/@stdlib/lapack/base/crot/examples/index.js new file mode 100644 index 000000000000..f21d84e72099 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/examples/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var ccopy = require( '@stdlib/blas/base/ccopy' ); +var zeros = require( '@stdlib/array/zeros' ); +var logEach = require( '@stdlib/console/log-each' ); +var crot = require( './../lib' ); + +function rand() { + return new Complex64( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +// Generate random input arrays: +var cx = filledarrayBy( 10, 'complex64', rand ); +var cxc = ccopy( cx.length, cx, 1, zeros( cx.length, 'complex64' ), 1 ); + +var cy = filledarrayBy( 10, 'complex64', rand ); +var cyc = ccopy( cy.length, cy, 1, zeros( cy.length, 'complex64' ), 1 ); + +var s = new Complex64( 0.0, 0.75 ); + +// Apply a plane rotation: +crot( cx.length, cx, 1, cy, 1, 1.25, s ); + +// Print the results: +logEach( '(%s,%s) => (%s,%s)', cxc, cyc, cx, cy ); diff --git a/lib/node_modules/@stdlib/lapack/base/crot/lib/crot.js b/lib/node_modules/@stdlib/lapack/base/crot/lib/crot.js new file mode 100644 index 000000000000..ab662a695686 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/lib/crot.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Applies a plane rotation with real cosine and complex sine. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} cx - first input array +* @param {integer} strideCX - `cx` stride length +* @param {Complex64Array} cy - second input array +* @param {integer} strideCY - `cy` stride length +* @param {number} c - cosine of the angle of rotation +* @param {Complex64} s - sine of the angle of rotation +* @returns {Complex64Array} `cy` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex64( 0.3, 0.4 ); +* +* crot( cx.length, cx, 1, cy, 1, 0.8, s ); +* +* var z = cy.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns ~-1.1 +* +* var im = imagf( z ); +* // returns ~-0.2 +* +* z = cx.get( 0 ); +* // returns +* +* re = realf( z ); +* // returns ~0.8 +* +* im = imagf( z ); +* // returns ~1.6 +*/ +function crot( N, cx, strideCX, cy, strideCY, c, s ) { + var ix = stride2offset( N, strideCX ); + var iy = stride2offset( N, strideCY ); + return ndarray( N, cx, strideCX, ix, cy, strideCY, iy, c, s ); +} + + +// EXPORTS // + +module.exports = crot; diff --git a/lib/node_modules/@stdlib/lapack/base/crot/lib/index.js b/lib/node_modules/@stdlib/lapack/base/crot/lib/index.js new file mode 100644 index 000000000000..7ad7a13da5a4 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/lib/index.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK auxiliary routine to apply a plane rotation with real cosine and complex sine. +* +* @module @stdlib/lapack/base/crot +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var crot = require( '@stdlib/lapack/base/crot' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex64( 0.6, 0 ); +* +* crot( cx.length, cx, 1, cy, 1, 0.8, s ); +* +* var z = cy.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns ~-0.6 +* +* var im = imagf( z ); +* // returns ~-1.2 +* +* z = cx.get( 0 ); +* // returns +* +* re = realf( z ); +* // returns ~0.8 +* +* im = imagf( z ); +* // returns ~1.6 +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* var crot = require( '@stdlib/lapack/base/crot' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex64( 0.6, 0 ); +* +* crot.ndarray( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); +* +* var z = cy.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns ~-0.6 +* +* var im = imagf( z ); +* // returns ~-1.2 +* +* z = cx.get( 0 ); +* // returns +* +* re = realf( z ); +* // returns ~0.8 +* +* im = imagf( z ); +* // returns ~1.6 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var crot; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + crot = main; +} else { + crot = tmp; +} + + +// EXPORTS // + +module.exports = crot; + +// exports: { "ndarray": "crot.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/crot/lib/main.js b/lib/node_modules/@stdlib/lapack/base/crot/lib/main.js new file mode 100644 index 000000000000..9bb50265786d --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var crot = require( './crot.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( crot, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = crot; diff --git a/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js new file mode 100644 index 000000000000..dbbec565eb8b --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js @@ -0,0 +1,128 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); + + +// MAIN // + +/** +* Applies a plane rotation with real cosine and complex sine. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} cx - first input array +* @param {integer} strideCX - `cx` stride length +* @param {NonNegativeInteger} offsetCX - starting `cx` index +* @param {Complex64Array} cy - second input array +* @param {integer} strideCY - `cy` stride length +* @param {NonNegativeInteger} offsetCY - starting `cy` index +* @param {number} c - cosine of the angle of rotation +* @param {Complex64} s - sine of the angle of rotation +* @returns {Complex64Array} `cy` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* var cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex64( 0.3, 0.4 ); +* +* crot( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); +* +* var z = cy.get( 0 ); +* // returns +* +* var re = realf( z ); +* // returns ~-1.1 +* +* var im = imagf( z ); +* // returns ~-0.2 +* +* z = cx.get( 0 ); +* // returns +* +* re = realf( z ); +* // returns ~0.8 +* +* im = imagf( z ); +* // returns ~1.6 +*/ +function crot( N, cx, strideCX, offsetCX, cy, strideCY, offsetCY, c, s ) { + var viewX; + var viewY; + var sr; + var si; + var sx; + var sy; + var ix; + var iy; + var yr; + var yi; + var xr; + var xi; + var i; + + if ( N <= 0 ) { + return cy; + } + viewX = reinterpret( cx, 0 ); + viewY = reinterpret( cy, 0 ); + + ix = offsetCX * 2; + iy = offsetCY * 2; + + sx = strideCX * 2; + sy = strideCY * 2; + + sr = realf( s ); + si = imagf( s ); + + for ( i = 0; i < N; i++ ) { + yr = viewY[ iy ]; + yi = viewY[ iy+1 ]; + xr = viewX[ ix ]; + xi = viewX[ ix+1 ]; + + // Compute tmp = c * cx[ ix ] + s * cy[ iy ] + viewX[ ix ] = f32( f32( c*xr ) + f32( f32( sr*yr ) - f32( si*yi ) ) ); + viewX[ ix+1 ] = f32( f32( c*xi ) + f32( f32( sr*yi ) + f32( si*yr ) ) ); + + // Compute cy[ iy ] = c * cy[ iy ] - conj(s) * cx[ ix ] + viewY[ iy ] = f32( f32( c*yr ) - f32( f32( sr*xr ) + f32( si*xi ) ) ); + viewY[ iy+1 ] = f32( f32( c*yi ) - f32( f32( sr*xi ) - f32( si*xr ) ) ); + + ix += sx; + iy += sy; + } + return cy; +} + + +// EXPORTS // + +module.exports = crot; diff --git a/lib/node_modules/@stdlib/lapack/base/crot/package.json b/lib/node_modules/@stdlib/lapack/base/crot/package.json new file mode 100644 index 000000000000..84ae96e38495 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/lapack/base/crot", + "version": "0.0.0", + "description": "LAPACK auxiliary routine to apply a plane rotation with real cosine and complex sine.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "blas", + "linear", + "algebra", + "subroutines", + "crot", + "rotation", + "vector", + "typed", + "array", + "ndarray", + "complex", + "complex64", + "float", + "float32", + "float32array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/lapack/base/crot/test/test.crot.js b/lib/node_modules/@stdlib/lapack/base/crot/test/test.crot.js new file mode 100644 index 000000000000..3fb14fdf4626 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/test/test.crot.js @@ -0,0 +1,636 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var absf = require( '@stdlib/math/base/special/absf' ); +var crot = require( './../lib/crot.js' ); + + +// FUNCTIONS // + +/** +* Tests for element-wise approximate equality. +* +* @private +* @param {Object} t - test object +* @param {Collection} actual - actual values +* @param {Collection} expected - expected values +* @param {number} rtol - relative tolerance +*/ +function isApprox( t, actual, expected, rtol ) { + var delta; + var tol; + var i; + + t.strictEqual( actual.length, expected.length, 'returns expected value' ); + for ( i = 0; i < expected.length; i++ ) { + if ( actual[ i ] === expected[ i ] ) { + t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' ); + } else { + delta = absf( actual[ i ] - expected[ i ] ); + tol = rtol * EPS * absf( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' ); + } + } +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof crot, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( crot.length, 7, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + // Verify in octave with [0.8 0.6; -0.6 0.8] * [1+2i, 3+4i, 5+6i, 7+8i; 0 0 0 0] + + s = new Complex64( 0.6, 0.0 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 4.0, // 3 + 4.8, // 3 + 5.6, // 4 + 6.4 // 4 + ]); + cye = new Float32Array([ + -0.6, // 1 + -1.2, // 1 + -1.8, // 2 + -2.4, // 2 + -3.0, // 3 + -3.6, // 3 + -4.2, // 4 + -4.8 // 4 + ]); + + out = crot( cx.length, cx, 1, cy, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + // Verify in octave with [1.25 0.75i; .75i 1.25] * [1+2i, 3+4i, 5+6i, 7+8i; 0 0 0 0] + + s = new Complex64( 0.0, 0.75 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 1.25, // 1 + 2.5, // 1 + 3.75, // 2 + 5.0, // 2 + 6.25, // 3 + 7.5, // 3 + 8.75, // 4 + 10.0 // 4 + ]); + cye = new Float32Array([ + -1.5, // 1 + 0.75, // 1 + -3.0, // 2 + 2.25, // 2 + -4.5, // 3 + 3.75, // 3 + -6.0, // 4 + 5.25 // 4 + ]); + + out = crot( cx.length, cx, 1, cy, 1, 1.25, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + // Verify in octave with [1.25 0.3+0.4i; -0.3+0.4i 1.25] * [1+2i, 3+4i, 5+6i, 7+8i; 0 0 0 0] + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 1.25, // 1 + 2.5, // 1 + 3.75, // 2 + 5.0, // 2 + 6.25, // 3 + 7.5, // 3 + 8.75, // 4 + 10.0 // 4 + ]); + cye = new Float32Array([ + -1.1, // 1 + -0.2, // 1 + -2.5, // 2 + 0.0, // 2 + -3.9, // 3 + 0.2, // 3 + -5.3, // 4 + 0.4 // 4 + ]); + + out = crot( cx.length, cx, 1, cy, 1, 1.25, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -1.1, // 1 + -0.2, // 1 + -3.9, // 2 + 0.2, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = crot( 2, cx, 2, cy, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + -2.5, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + out = crot( 2, cx, 1, cy, 2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the second array', function test( t ) { + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = crot( cx.length, cx, 1, cy, 1, 0.8, s ); + + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns both vectors unchanged', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cye = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + crot( -1, cx, 1, cy, 1, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + crot( 0, cx, 1, cy, 1, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 3.0, // 1 + 4.0, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 2 + 1.6, // 2 + 2.4, // 1 + 3.2, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -1.1, // 2 + -0.2, // 2 + 0.0, + 0.0, + -2.5, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + out = crot( 2, cx, -1, cy, -2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -3.9, // 2 + 0.2, // 2 + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = crot( 2, cx, 2, cy, -1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var viewX; + var viewY; + var cx0; + var cy0; + var cx1; + var cy1; + var cxe; + var cye; + var out; + var s; + + s = new Complex64( 0.3, 0.4 ); + + // Initial arrays... + cx0 = new Complex64Array([ + 1.0, + 2.0, + 3.0, // 2 + 4.0, // 2 + 5.0, + 6.0, + 7.0, // 1 + 8.0 // 1 + ]); + cy0 = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + // Create offset views... + cx1 = new Complex64Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // begin at the 2nd element + cy1 = new Complex64Array( cy0.buffer, cy0.BYTES_PER_ELEMENT*2 ); // begin at the 3rd element + + viewX = new Float32Array( cx0.buffer ); + viewY = new Float32Array( cy0.buffer ); + + cxe = new Float32Array([ + 1.0, + 2.0, + 2.4, // 2 + 3.2, // 2 + 5.0, + 6.0, + 5.6, // 1 + 6.4 // 1 + ]); + cye = new Float32Array([ + 0.0, + 0.0, + 0.0, + 0.0, + -5.3, // 1 + 0.4, // 1 + -2.5, // 2 + 0.0 // 2 + ]); + + out = crot( 2, cx1, -2, cy1, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/crot/test/test.js b/lib/node_modules/@stdlib/lapack/base/crot/test/test.js new file mode 100644 index 000000000000..180ef280fcba --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var isBrowser = require( '@stdlib/assert/is-browser' ); +var crot = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': isBrowser +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof crot, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof crot.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var crot = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( crot, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var crot; + var main; + + main = require( './../lib/crot.js' ); + + crot = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( crot, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/crot/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/crot/test/test.ndarray.js new file mode 100644 index 000000000000..35b67bd85266 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/crot/test/test.ndarray.js @@ -0,0 +1,560 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var absf = require( '@stdlib/math/base/special/absf' ); +var crot = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Tests for element-wise approximate equality. +* +* @private +* @param {Object} t - test object +* @param {Collection} actual - actual values +* @param {Collection} expected - expected values +* @param {number} rtol - relative tolerance +*/ +function isApprox( t, actual, expected, rtol ) { + var delta; + var tol; + var i; + + t.strictEqual( actual.length, expected.length, 'returns expected value' ); + for ( i = 0; i < expected.length; i++ ) { + if ( actual[ i ] === expected[ i ] ) { + t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' ); + } else { + delta = absf( actual[ i ] - expected[ i ] ); + tol = rtol * EPS * absf( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' ); + } + } +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof crot, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 9', function test( t ) { + t.strictEqual( crot.length, 9, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.6, 0.0 ); + + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 4.0, // 3 + 4.8, // 3 + 5.6, // 4 + 6.4 // 4 + ]); + cye = new Float32Array([ + -0.6, // 1 + -1.2, // 1 + -1.8, // 2 + -2.4, // 2 + -3.0, // 3 + -3.6, // 3 + -4.2, // 4 + -4.8 // 4 + ]); + + out = crot( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.0, 0.6 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -1.2, // 1 + 0.6, // 1 + -3.6, // 2 + 3.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = crot( 2, cx, 2, 0, cy, 1, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, + 2.0, + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0, // 2 + 7.0, // 3 + 8.0 // 3 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 1.0, + 2.0, + 2.4, // 1 + 3.2, // 1 + 4.0, // 2 + 4.8, // 2 + 5.6, // 3 + 6.4 // 3 + ]); + cye = new Float32Array([ + -2.5, // 1 + 0.0, // 1 + -3.9, // 2 + 0.2, // 2 + -5.3, // 3 + 0.4, // 3 + 0.0, + 0.0 + ]); + + out = crot( 3, cx, 1, 1, cy, 1, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + -2.5, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + out = crot( 2, cx, 1, 0, cy, 2, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -3.9, // 2 + 0.2, // 2 + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = crot( 2, cx, 2, 0, cy, -1, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the second array', function test( t ) { + var out; + var cx; + var cy; + var s; + + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + s = new Complex64( 0.3, 0.4 ); + + out = crot( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns both vectors unchanged', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var cx; + var cy; + var s; + + cx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + s = new Complex64( 0.3, 0.4 ); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cye = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + crot( -1, cx, 1, 0, cy, 1, 0, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + crot( 0, cx, 1, 0, cy, 1, 0, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 3.0, // 1 + 4.0, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 0.8, // 2 + 1.6, // 2 + 2.4, // 1 + 3.2, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float32Array([ + -1.1, // 2 + -0.2, // 2 + 0.0, + 0.0, + -2.5, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + out = crot( 2, cx, -1, 1, cy, -2, 2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex64( 0.3, 0.4 ); + cx = new Complex64Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex64Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float32Array( cx.buffer ); + viewY = new Float32Array( cy.buffer ); + + cxe = new Float32Array([ + 1.0, + 2.0, + 2.4, // 1 + 3.2, // 1 + 5.0, + 6.0, + 5.6, // 2 + 6.4 // 2 + ]); + cye = new Float32Array([ + 0.0, + 0.0, + 0.0, + 0.0, + -2.5, // 1 + 0.0, // 1 + -5.3, // 2 + 0.4 // 2 + ]); + + out = crot( 2, cx, 2, 1, cy, 1, 2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/dge-trans/README.md b/lib/node_modules/@stdlib/lapack/base/dge-trans/README.md index d60b174f9731..233dc7eeb41d 100644 --- a/lib/node_modules/@stdlib/lapack/base/dge-trans/README.md +++ b/lib/node_modules/@stdlib/lapack/base/dge-trans/README.md @@ -63,14 +63,14 @@ var Float64Array = require( '@stdlib/array/float64' ); // Initial arrays... var A0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -var Out0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); +var out0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); // Create offset views... var A1 = new Float64Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var Out1 = new Float64Array( Out0.buffer, Out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -dgetrans( 'row-major', 2, 2, A1, 2, Out1, 2 ); -// Out0 => [ 0.0, 1.0, 3.0, 2.0, 4.0 ] +dgetrans( 'row-major', 2, 2, A1, 2, out1, 2 ); +// out0 => [ 0.0, 1.0, 3.0, 2.0, 4.0 ] ``` #### dgetrans.ndarray( M, N, A, sa1, sa2, oa, out, so1, so2, oo ) diff --git a/lib/node_modules/@stdlib/lapack/base/dlacpy/README.md b/lib/node_modules/@stdlib/lapack/base/dlacpy/README.md index 7459e8145024..33e43898d079 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlacpy/README.md +++ b/lib/node_modules/@stdlib/lapack/base/dlacpy/README.md @@ -107,11 +107,11 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -// B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +// B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] ```
diff --git a/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/repl.txt index ffe2f6a41b06..b63b9e5fa8d0 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/repl.txt +++ b/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/repl.txt @@ -42,10 +42,10 @@ Examples -------- - > var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 3.0, 0.0, 4.0 ] ); - > var B = new {{alias:@stdlib/array/float64}}( [ 5.0, 7.0, 0.0, 8.0 ] ); + > var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var B = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > {{alias}}( 'row-major', 'all', 2, 2, A, 2, B, 2 ) - [ 1.0, 3.0, 0.0, 4.0 ] + [ 1.0, 2.0, 3.0, 4.0 ] {{alias}}.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob ) @@ -99,10 +99,10 @@ Examples -------- - > var A = new {{alias:@stdlib/array/float64}}( [ 0.0, 1.0, 3.0, 0.0, 4.0 ] ); - > var B = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 5.0, 7.0, 0.0, 8.0 ] ); + > var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + > var B = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); > {{alias}}.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ) - [ 0.0, 0.0, 1.0, 3.0, 0.0, 4.0 ] + [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/types/index.d.ts index dd5364250506..b94c87b4adb0 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/lapack/base/dlacpy/docs/types/index.d.ts @@ -69,11 +69,11 @@ interface Routine { * @example * var Float64Array = require( '@stdlib/array/float64' ); * - * var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); - * var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); + * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var B = new Float64Array( 6 ); * * dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); - * // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] + * // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ ndarray( uplo: string, M: number, N: number, A: Float64Array, strideA1: number, strideA2: number, offsetA: number, B: Float64Array, strideB1: number, strideB2: number, offsetB: number ): Float64Array; } @@ -103,11 +103,11 @@ interface Routine { * @example * var Float64Array = require( '@stdlib/array/float64' ); * -* var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float64Array( 6 ); * * dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ declare var dlacpy: Routine; diff --git a/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/index.js b/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/index.js index ad79ad3e2df7..1a97231cf4ff 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/index.js +++ b/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/index.js @@ -37,11 +37,11 @@ * var Float64Array = require( '@stdlib/array/float64' ); * var dlacpy = require( '@stdlib/lapack/base/dlacpy' ); * -* var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float64Array( 6 ); * * dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/ndarray.js index 66b722fcd1db..baec1e500137 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dlacpy/lib/ndarray.js @@ -44,29 +44,29 @@ var base = require( './base.js' ); * @example * var Float64Array = require( '@stdlib/array/float64' ); * -* var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float64Array( 6 ); * * dlacpy( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] * * @example * var Float64Array = require( '@stdlib/array/float64' ); * -* var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float64Array( 6 ); * * dlacpy( 'upper', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 53.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 0.0, 5.0 ] * * @example * var Float64Array = require( '@stdlib/array/float64' ); * -* var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float64Array( 6 ); * * dlacpy( 'lower', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 312.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 0.0, 4.0, 5.0 ] */ function dlacpy( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { // eslint-disable-line max-len, max-params return base( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/lapack/base/dlacpy/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlacpy/test/test.ndarray.js index 84e231ec9242..a06f19c76ae7 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlacpy/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dlacpy/test/test.ndarray.js @@ -46,25 +46,25 @@ tape( 'the function copies all of a matrix `A` to another matrix `B` (row-major) var A; var B; - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = dlacpy( 'all', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0 ] ); out = dlacpy( 'all', 2, 3, A, -3, -1, 6, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = dlacpy( 'all', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -79,25 +79,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major var A; var B; - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 0.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 0.0, 15.0, 16.0 ] ); out = dlacpy( 'upper', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 3.0, 2.0, 1.0, 0.0, 5.0, 4.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 13.0, 12.0, 11.0, 0.0, 15.0, 14.0 ] ); out = dlacpy( 'upper', 2, 3, A, 3, -1, 3, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 4.0, 0.0, 0.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 0.0, 14.0, 0.0, 0.0 ] ); out = dlacpy( 'upper', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -112,25 +112,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major var A; var B; - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 4.0, 5.0, 0.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 0.0, 14.0, 15.0, 0.0 ] ); out = dlacpy( 'lower', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 4.0, 0.0, 0.0, 1.0, 2.0, 0.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 14.0, 0.0, 0.0, 11.0, 12.0, 0.0 ] ); out = dlacpy( 'lower', 2, 3, A, -3, 1, 4, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 13.0, 14.0, 15.0, 16.0 ] ); out = dlacpy( 'lower', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -145,25 +145,25 @@ tape( 'the function copies all of a matrix `A` to another matrix `B` (column-maj var A; var B; - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = dlacpy( 'all', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0 ] ); out = dlacpy( 'all', 2, 3, A, 1, 2, 1, B, -1, -2, 8 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = dlacpy( 'all', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -178,25 +178,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (column-ma var A; var B; - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 13.0, 14.0, 15.0, 16.0 ] ); out = dlacpy( 'upper', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 1.0, 4.0, 3.0, 6.0, 5.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 11.0, 14.0, 13.0, 16.0, 15.0 ] ); out = dlacpy( 'upper', 2, 3, A, 1, 2, 1, B, -1, 2, 4 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 4.0, 5.0, 0.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 0.0, 14.0, 15.0, 0.0 ] ); out = dlacpy( 'upper', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -211,25 +211,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (column-ma var A; var B; - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 4.0, 0.0, 0.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 0.0, 14.0, 0.0, 0.0 ] ); out = dlacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.0, 1.0, 2.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 14.0, 11.0, 12.0 ] ); out = dlacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, -2, 7 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float64Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float64Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 0.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 0.0, 15.0, 16.0 ] ); out = dlacpy( 'lower', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); t.strictEqual( out, B, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/lapack/base/dlassq/README.md b/lib/node_modules/@stdlib/lapack/base/dlassq/README.md index 39de9f0e3ab3..61f9d535024d 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlassq/README.md +++ b/lib/node_modules/@stdlib/lapack/base/dlassq/README.md @@ -107,7 +107,7 @@ dlassq.ndarray( 4, X, 1, 0, 1.0, 0.0, out, 1, 0 ); The function has the following additional parameters: - **ox**: starting index for `X`. -- **out**: output [`Float64Array`][mdn-float64array] +- **out**: output [`Float64Array`][mdn-float64array]. - **so**: stride length for `out`. - **oo**: starting index for `out`. diff --git a/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts index 78ba02be4ecd..e9b598da6965 100644 --- a/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/lapack/base/docs/types/index.d.ts @@ -56,11 +56,11 @@ interface Namespace { * @example * var Float64Array = require( '@stdlib/array/float64' ); * - * var A = new Float64Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); - * var B = new Float64Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); + * var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var B = new Float64Array( 6 ); * * ns.dlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); - * // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] + * // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ dlacpy: typeof dlacpy; @@ -183,11 +183,11 @@ interface Namespace { * @example * var Float32Array = require( '@stdlib/array/float32' ); * - * var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); - * var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); + * var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var B = new Float32Array( 6 ); * * ns.slacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); - * // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] + * // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ slacpy: typeof slacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/lib/index.js b/lib/node_modules/@stdlib/lapack/base/lib/index.js index c92e921d81e9..672062483405 100644 --- a/lib/node_modules/@stdlib/lapack/base/lib/index.js +++ b/lib/node_modules/@stdlib/lapack/base/lib/index.js @@ -36,6 +36,51 @@ var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); */ var ns = {}; +/** +* @name clacgv +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/clacgv} +*/ +setReadOnly( ns, 'clacgv', require( '@stdlib/lapack/base/clacgv' ) ); + +/** +* @name clacpy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/clacpy} +*/ +setReadOnly( ns, 'clacpy', require( '@stdlib/lapack/base/clacpy' ) ); + +/** +* @name claset +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/claset} +*/ +setReadOnly( ns, 'claset', require( '@stdlib/lapack/base/claset' ) ); + +/** +* @name crot +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/crot} +*/ +setReadOnly( ns, 'crot', require( '@stdlib/lapack/base/crot' ) ); + +/** +* @name dgetrans +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/dge-trans} +*/ +setReadOnly( ns, 'dgetrans', require( '@stdlib/lapack/base/dge-trans' ) ); + /** * @name dlacpy * @memberof ns @@ -45,6 +90,15 @@ var ns = {}; */ setReadOnly( ns, 'dlacpy', require( '@stdlib/lapack/base/dlacpy' ) ); +/** +* @name dlamch +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/dlamch} +*/ +setReadOnly( ns, 'dlamch', require( '@stdlib/lapack/base/dlamch' ) ); + /** * @name dlassq * @memberof ns @@ -72,6 +126,15 @@ setReadOnly( ns, 'dlaswp', require( '@stdlib/lapack/base/dlaswp' ) ); */ setReadOnly( ns, 'dpttrf', require( '@stdlib/lapack/base/dpttrf' ) ); +/** +* @name sgetrans +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/sge-trans} +*/ +setReadOnly( ns, 'sgetrans', require( '@stdlib/lapack/base/sge-trans' ) ); + /** * @name slacpy * @memberof ns @@ -81,6 +144,15 @@ setReadOnly( ns, 'dpttrf', require( '@stdlib/lapack/base/dpttrf' ) ); */ setReadOnly( ns, 'slacpy', require( '@stdlib/lapack/base/slacpy' ) ); +/** +* @name slaswp +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/slaswp} +*/ +setReadOnly( ns, 'slaswp', require( '@stdlib/lapack/base/slaswp' ) ); + /** * @name spttrf * @memberof ns @@ -90,6 +162,42 @@ setReadOnly( ns, 'slacpy', require( '@stdlib/lapack/base/slacpy' ) ); */ setReadOnly( ns, 'spttrf', require( '@stdlib/lapack/base/spttrf' ) ); +/** +* @name zlacgv +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/zlacgv} +*/ +setReadOnly( ns, 'zlacgv', require( '@stdlib/lapack/base/zlacgv' ) ); + +/** +* @name zlacpy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/zlacpy} +*/ +setReadOnly( ns, 'zlacpy', require( '@stdlib/lapack/base/zlacpy' ) ); + +/** +* @name zlaset +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/zlaset} +*/ +setReadOnly( ns, 'zlaset', require( '@stdlib/lapack/base/zlaset' ) ); + +/** +* @name zrot +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/lapack/base/zrot} +*/ +setReadOnly( ns, 'zrot', require( '@stdlib/lapack/base/zrot' ) ); + // EXPORTS // diff --git a/lib/node_modules/@stdlib/lapack/base/sge-trans/README.md b/lib/node_modules/@stdlib/lapack/base/sge-trans/README.md index e0be1568b98f..c87b00bf419a 100644 --- a/lib/node_modules/@stdlib/lapack/base/sge-trans/README.md +++ b/lib/node_modules/@stdlib/lapack/base/sge-trans/README.md @@ -63,14 +63,14 @@ var Float32Array = require( '@stdlib/array/float32' ); // Initial arrays... var A0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -var Out0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); +var out0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); // Create offset views... var A1 = new Float32Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var Out1 = new Float32Array( Out0.buffer, Out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float32Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -sgetrans( 'row-major', 2, 2, A1, 2, Out1, 2 ); -// Out0 => [ 0.0, 1.0, 3.0, 2.0, 4.0 ] +sgetrans( 'row-major', 2, 2, A1, 2, out1, 2 ); +// out0 => [ 0.0, 1.0, 3.0, 2.0, 4.0 ] ``` #### sgetrans.ndarray( M, N, A, sa1, sa2, oa, out, so1, so2, oo ) diff --git a/lib/node_modules/@stdlib/lapack/base/slacpy/README.md b/lib/node_modules/@stdlib/lapack/base/slacpy/README.md index 714c75e7a87e..dda9b3925671 100644 --- a/lib/node_modules/@stdlib/lapack/base/slacpy/README.md +++ b/lib/node_modules/@stdlib/lapack/base/slacpy/README.md @@ -107,11 +107,11 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); slacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -// B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +// B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] ``` diff --git a/lib/node_modules/@stdlib/lapack/base/slacpy/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/slacpy/docs/repl.txt index 837293c812db..763087aae804 100644 --- a/lib/node_modules/@stdlib/lapack/base/slacpy/docs/repl.txt +++ b/lib/node_modules/@stdlib/lapack/base/slacpy/docs/repl.txt @@ -42,10 +42,10 @@ Examples -------- - > var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 3.0, 0.0, 4.0 ] ); - > var B = new {{alias:@stdlib/array/float32}}( [ 5.0, 7.0, 0.0, 8.0 ] ); + > var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var B = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 0.0, 0.0 ] ); > {{alias}}( 'row-major', 'all', 2, 2, A, 2, B, 2 ) - [ 1.0, 3.0, 0.0, 4.0 ] + [ 1.0, 2.0, 3.0, 4.0 ] {{alias}}.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob ) @@ -99,10 +99,10 @@ Examples -------- - > var A = new {{alias:@stdlib/array/float32}}( [ 0.0, 1.0, 3.0, 0.0, 4.0 ] ); - > var B = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 5.0, 7.0, 0.0, 8.0 ] ); + > var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + > var B = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); > {{alias}}.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ) - [ 0.0, 0.0, 1.0, 3.0, 0.0, 4.0 ] + [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] See Also -------- diff --git a/lib/node_modules/@stdlib/lapack/base/slacpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/slacpy/docs/types/index.d.ts index 8a09fe303f0e..f58c1bc1cb18 100644 --- a/lib/node_modules/@stdlib/lapack/base/slacpy/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/lapack/base/slacpy/docs/types/index.d.ts @@ -69,11 +69,11 @@ interface Routine { * @example * var Float32Array = require( '@stdlib/array/float32' ); * - * var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); - * var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); + * var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var B = new Float32Array( 6 ); * * slacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); - * // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] + * // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ ndarray( uplo: string, M: number, N: number, A: Float32Array, strideA1: number, strideA2: number, offsetA: number, B: Float32Array, strideB1: number, strideB2: number, offsetB: number ): Float32Array; } @@ -103,11 +103,11 @@ interface Routine { * @example * var Float32Array = require( '@stdlib/array/float32' ); * -* var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float32Array( 6 ); * * slacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ declare var slacpy: Routine; diff --git a/lib/node_modules/@stdlib/lapack/base/slacpy/lib/index.js b/lib/node_modules/@stdlib/lapack/base/slacpy/lib/index.js index d1dcba5d0610..8b6e7252c019 100644 --- a/lib/node_modules/@stdlib/lapack/base/slacpy/lib/index.js +++ b/lib/node_modules/@stdlib/lapack/base/slacpy/lib/index.js @@ -37,11 +37,11 @@ * var Float32Array = require( '@stdlib/array/float32' ); * var slacpy = require( '@stdlib/lapack/base/slacpy' ); * -* var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float32Array( 6 ); * * slacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/lapack/base/slacpy/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/slacpy/lib/ndarray.js index 94a4bc87324b..fea2150ebcc1 100644 --- a/lib/node_modules/@stdlib/lapack/base/slacpy/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/slacpy/lib/ndarray.js @@ -44,29 +44,29 @@ var base = require( './base.js' ); * @example * var Float32Array = require( '@stdlib/array/float32' ); * -* var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float32Array( 6 ); * * slacpy( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 4.0, 5.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); * -* var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float32Array( 6 ); * * slacpy( 'upper', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 2.0, 53.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 3.0, 0.0, 5.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); * -* var A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); -* var B = new Float32Array( [ 0.0, 0.0, 11.0, 312.0, 53.0, 412.0 ] ); +* var A = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var B = new Float32Array( 6 ); * * slacpy( 'lower', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); -* // B => [ 0.0, 0.0, 1.0, 312.0, 3.0, 4.0 ] +* // B => [ 0.0, 0.0, 2.0, 0.0, 4.0, 5.0 ] */ function slacpy( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { // eslint-disable-line max-len, max-params return base( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/lapack/base/slacpy/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/slacpy/test/test.ndarray.js index b14e8085ae4a..f9271c8eadb9 100644 --- a/lib/node_modules/@stdlib/lapack/base/slacpy/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/slacpy/test/test.ndarray.js @@ -46,25 +46,25 @@ tape( 'the function copies all of a matrix `A` to another matrix `B` (row-major) var A; var B; - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = slacpy( 'all', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0 ] ); out = slacpy( 'all', 2, 3, A, -3, -1, 6, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = slacpy( 'all', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -79,25 +79,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major var A; var B; - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 0.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 0.0, 15.0, 16.0 ] ); out = slacpy( 'upper', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 3.0, 2.0, 1.0, 0.0, 5.0, 4.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 13.0, 12.0, 11.0, 0.0, 15.0, 14.0 ] ); out = slacpy( 'upper', 2, 3, A, 3, -1, 3, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 4.0, 0.0, 0.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 0.0, 14.0, 0.0, 0.0 ] ); out = slacpy( 'upper', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -112,25 +112,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major var A; var B; - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 4.0, 5.0, 0.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 0.0, 14.0, 15.0, 0.0 ] ); out = slacpy( 'lower', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 4.0, 0.0, 0.0, 1.0, 2.0, 0.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 14.0, 0.0, 0.0, 11.0, 12.0, 0.0 ] ); out = slacpy( 'lower', 2, 3, A, -3, 1, 4, B, 3, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 13.0, 14.0, 15.0, 16.0 ] ); out = slacpy( 'lower', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -145,25 +145,25 @@ tape( 'the function copies all of a matrix `A` to another matrix `B` (column-maj var A; var B; - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = slacpy( 'all', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 16.0, 15.0, 14.0, 13.0, 12.0, 11.0 ] ); out = slacpy( 'all', 2, 3, A, 1, 2, 1, B, -1, -2, 8 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); out = slacpy( 'all', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -178,25 +178,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (column-ma var A; var B; - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 13.0, 14.0, 15.0, 16.0 ] ); out = slacpy( 'upper', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 1.0, 4.0, 3.0, 6.0, 5.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 11.0, 14.0, 13.0, 16.0, 15.0 ] ); out = slacpy( 'upper', 2, 3, A, 1, 2, 1, B, -1, 2, 4 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 4.0, 5.0, 0.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 0.0, 0.0, 14.0, 15.0, 0.0 ] ); out = slacpy( 'upper', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); t.strictEqual( out, B, 'returns expected value' ); @@ -211,25 +211,25 @@ tape( 'the function copies part of a matrix `A` to another matrix `B` (column-ma var A; var B; - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 4.0, 0.0, 0.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 0.0, 14.0, 0.0, 0.0 ] ); out = slacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.0, 1.0, 2.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 14.0, 11.0, 12.0 ] ); out = slacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, -2, 7 ); t.strictEqual( out, B, 'returns expected value' ); t.deepEqual( out, expected, 'returns expected value' ); - A = new Float32Array( [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = new Float32Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); B = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - expected = new Float32Array( [ 0.0, 0.0, 0.0, 1.0, 2.0, 3.0, 0.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 11.0, 12.0, 13.0, 0.0, 15.0, 16.0 ] ); out = slacpy( 'lower', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); t.strictEqual( out, B, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/README.md b/lib/node_modules/@stdlib/lapack/base/zlacgv/README.md new file mode 100644 index 000000000000..52e8cad0b2df --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/README.md @@ -0,0 +1,225 @@ + + +# zlacgv + +> Conjugate each element in a double-precision complex floating-point vector. + +
+ +## Usage + +```javascript +var zlacgv = require( '@stdlib/lapack/base/zlacgv' ); +``` + +#### zlacgv( N, zx, strideZX ) + +Conjugates each element in a double-precision complex floating-point vector. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + +zlacgv( 2, zx, 1 ); + +var z = zx.get( 0 ); +// returns + +var re = real( z ); +// returns 1.0 + +var im = imag( z ); +// returns -2.0 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **zx**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideZX**: stride length for `zx`. + +The `N` and stride parameters determine which elements in `zx` are conjugated. For example, to conjugate every other element in `zx`, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +zlacgv( 2, zx, 2 ); + +var z = zx.get( 0 ); +// returns + +var re = real( z ); +// returns 1.0 + +var im = imag( z ); +// returns -2.0 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +// Initial array: +var zx0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +// Create an offset view: +var zx1 = new Complex128Array( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Conjugate every element in `zx1`: +zlacgv( 3, zx1, 1 ); + +var z = zx0.get( 1 ); +// returns + +var re = real( z ); +// returns 3.0 + +var im = imag( z ); +// returns -4.0 +``` + +#### zlacgv.ndarray( N, zx, strideZX, offsetZX ) + +Conjugates each element in a double-precision floating-point vector using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +zlacgv.ndarray( 3, zx, 1, 0 ); + +var z = zx.get( 0 ); +// returns + +var re = real( z ); +// returns 1.0 + +var im = imag( z ); +// returns -2.0 +``` + +The function has the following additional parameters: + +- **offsetZX**: starting index for `zx`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to conjugate every other element in the input strided array starting from the second element, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + +zlacgv.ndarray( 2, zx, 2, 1 ); + +var z = zx.get( 3 ); +// returns + +var re = real( z ); +// returns 7.0 + +var im = imag( z ); +// returns -8.0 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `zx` unchanged. +- `zlacgv()` corresponds to the [LAPACK][lapack] BLAS-like level 1 routine [`zlacgv`][zlacgv]. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zlacgv = require( '@stdlib/lapack/base/zlacgv' ); + +function rand() { + return new Complex128( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +var zx = filledarrayBy( 10, 'complex128', rand ); +console.log( zx.toString() ); + +// Conjugate elements: +zlacgv( zx.length, zx, 1 ); +console.log( zx.get( zx.length-1 ).toString() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: https://www.netlib.org/lapack + +[zlacgv]: https://www.netlib.org/lapack/explore-html/d9/d50/group__lacgv_gae42087fcabd33130fcbac2aff031de8b.html#gae42087fcabd33130fcbac2aff031de8b + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/benchmark/benchmark.js new file mode 100644 index 000000000000..b60f0d1b15a5 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/benchmark/benchmark.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var pkg = require( './../package.json' ).name; +var zlacgv = require( './../lib/zlacgv.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var zxbuf; + var zx; + + zxbuf = uniform( len*2, -100.0, 100.0, options ); + zx = new Complex128Array( zxbuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zlacgv( zx.length, zx, 1 ); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..415187e72284 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/benchmark/benchmark.ndarray.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var pkg = require( './../package.json' ).name; +var zlacgv = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var zxbuf; + var zx; + + zxbuf = uniform( len*2, -100.0, 100.0, options ); + zx = new Complex128Array( zxbuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zlacgv( zx.length, zx, 1, 0 ); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( zxbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':ndarray:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/repl.txt new file mode 100644 index 000000000000..7d6dd2f01f9d --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/repl.txt @@ -0,0 +1,108 @@ + +{{alias}}( N, zx, strideZX ) + Conjugates each element in a double-precision complex floating-point vector. + + The `N` and stride parameters determine which elements in `zx` are + conjugated. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N` is less than or equal to `0`, the function returns `zx` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + zx: Complex128Array + Input array. + + strideZX: integer + Stride length for `zx`. + + Returns + ------- + zx: Complex128Array + Input array. + + Examples + -------- + // Standard usage: + > var zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > {{alias}}( 2, zx, 1 ); + > var z = zx.get( 0 ); + > var re = {{alias:@stdlib/complex/float64/real}}( z ) + 1.0 + > var im = {{alias:@stdlib/complex/float64/imag}}( z ) + -2.0 + + // Advanced indexing: + > zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > {{alias}}( 2, zx, 2 ); + > z = zx.get( 0 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + 1.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + -2.0 + + // Using typed array views: + > var zx0 = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var zx1 = new {{alias:@stdlib/array/complex128}}( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, zx1, 1 ); + > z = zx0.get( 1 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + 3.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + -4.0 + + +{{alias}}.ndarray( N, zx, strideZX, offsetZX ) + Conjugates each element in a double-precision complex floating-point vector + using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + zx: Complex128Array + Input array. + + strideZX: integer + Stride length for `zx`. + + offsetZX: integer + Starting index for `zx`. + + Returns + ------- + zx: Complex128Array + Input array. + + Examples + -------- + // Standard usage: + > var zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > {{alias}}.ndarray( 2, zx, 1, 0 ); + > var z = zx.get( 0 ); + > var re = {{alias:@stdlib/complex/float64/real}}( z ) + 1.0 + > var im = {{alias:@stdlib/complex/float64/imag}}( z ) + -2.0 + + // Advanced indexing: + > zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + > {{alias}}.ndarray( 2, zx, 1, 2 ); + > z = zx.get( 2 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + 5.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + -6.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/types/index.d.ts new file mode 100644 index 000000000000..5eb0c409bf1e --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/types/index.d.ts @@ -0,0 +1,136 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zlacgv`. +*/ +interface Routine { + /** + * Conjugates each element in a double-precision complex floating-point vector. + * + * @param N - number of indexed elements + * @param zx - input array + * @param strideZX - `zx` stride length + * @returns input array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * zlacgv( 3, zx, 1 ); + * + * var z = zx.get( 0 ); + * // returns + * + * var re = real( z ); + * // returns 1.0 + * + * var im = imag( z ); + * // returns -2.0 + */ + ( N: number, zx: Complex128Array, strideZX: number ): Complex128Array; + + /** + * Conjugates each element in a double-precision complex floating-point vector. + * + * @param N - number of indexed elements + * @param zx - input array + * @param strideZX - `zx` stride length + * @param offsetZX - starting index for `zx` + * @returns input array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * zlacgv.ndarray( 3, zx, 1, 0 ); + * + * var z = zx.get( 0 ); + * // returns + * + * var re = real( z ); + * // returns 1.0 + * + * var im = imag( z ); + * // returns -2.0 + */ + ndarray( N: number, zx: Complex128Array, strideZX: number, offsetZX: number ): Complex128Array; +} + +/** +* Conjugates each element in a double-precision complex floating-point vector. +* +* @param N - number of indexed elements +* @param zx - input array +* @param strideZX - `zx` stride length +* @returns input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zlacgv( 3, zx, 1 ); +* +* var z = zx.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns -4.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zlacgv.ndarray( 2, zx, 1, 1 ); +* +* var z = zx.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns -4.0 +*/ +declare var zlacgv: Routine; + + +// EXPORTS // + +export = zlacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/types/test.ts new file mode 100644 index 000000000000..316833499da0 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/docs/types/test.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import zlacgv = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zlacgv( zx.length, zx, 1 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zlacgv( '10', zx, 1 ); // $EzxpectError + zlacgv( true, zx, 1 ); // $ExpectError + zlacgv( false, zx, 1 ); // $ExpectError + zlacgv( null, zx, 1 ); // $ExpectError + zlacgv( undefined, zx, 1 ); // $ExpectError + zlacgv( [], zx, 1 ); // $ExpectError + zlacgv( {}, zx, 1 ); // $ExpectError + zlacgv( ( zx: number ): number => zx, zx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zlacgv( zx.length, 10, 1 ); // $ExpectError + zlacgv( zx.length, '10', 1 ); // $ExpectError + zlacgv( zx.length, true, 1 ); // $ExpectError + zlacgv( zx.length, false, 1 ); // $ExpectError + zlacgv( zx.length, null, 1 ); // $ExpectError + zlacgv( zx.length, undefined, 1 ); // $ExpectError + zlacgv( zx.length, [ '1' ], 1 ); // $ExpectError + zlacgv( zx.length, {}, 1 ); // $ExpectError + zlacgv( zx.length, ( zx: number ): number => zx, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zlacgv( zx.length, zx, '10' ); // $ExpectError + zlacgv( zx.length, zx, true ); // $ExpectError + zlacgv( zx.length, zx, false ); // $ExpectError + zlacgv( zx.length, zx, null ); // $ExpectError + zlacgv( zx.length, zx, undefined ); // $ExpectError + zlacgv( zx.length, zx, [] ); // $ExpectError + zlacgv( zx.length, zx, {} ); // $ExpectError + zlacgv( zx.length, zx, ( zx: number ): number => zx ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const zx = new Complex128Array( 10 ); + + zlacgv(); // $ExpectError + zlacgv( zx.length ); // $ExpectError + zlacgv( zx.length, zx ); // $ExpectError + zlacgv( zx.length, zx, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zlacgv.ndarray( zx.length, zx, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zlacgv.ndarray( '10', zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( true, zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( false, zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( null, zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( undefined, zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( [], zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( {}, zx, 1, 0 ); // $ExpectError + zlacgv.ndarray( ( zx: number ): number => zx, zx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + + zlacgv( zx.length, 10, 1, 0 ); // $ExpectError + zlacgv( zx.length, '10', 1, 0 ); // $ExpectError + zlacgv( zx.length, true, 1, 0 ); // $ExpectError + zlacgv( zx.length, false, 1, 0 ); // $ExpectError + zlacgv( zx.length, null, 1, 0 ); // $ExpectError + zlacgv( zx.length, undefined, 1, 0 ); // $ExpectError + zlacgv( zx.length, [ '1' ], 1, 0 ); // $ExpectError + zlacgv( zx.length, {}, 1, 0 ); // $ExpectError + zlacgv( zx.length, ( zx: number ): number => zx, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zlacgv.ndarray( zx.length, zx, '10', 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, true, 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, false, 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, null, 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, undefined, 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, [], 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, {}, 0 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, ( zx: number ): number => zx, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + + zlacgv.ndarray( zx.length, zx, 1, '10' ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, true ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, false ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, null ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, undefined ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, [] ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, {} ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, ( zx: number ): number => zx ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const zx = new Complex128Array( 10 ); + + zlacgv.ndarray(); // $ExpectError + zlacgv.ndarray( zx.length ); // $ExpectError + zlacgv.ndarray( zx.length, zx ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1 ); // $ExpectError + zlacgv.ndarray( zx.length, zx, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/examples/index.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/examples/index.js new file mode 100644 index 000000000000..400a205f9d18 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zlacgv = require( './../lib' ); + +function rand() { + return new Complex128( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +var zx = filledarrayBy( 10, 'complex128', rand ); +console.log( zx.toString() ); + +// Conjugate elements: +zlacgv( zx.length, zx, 1 ); +console.log( zx.get( zx.length-1 ).toString() ); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/index.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/index.js new file mode 100644 index 000000000000..cbe244398be4 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/index.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK BLAS-like level-1 routine to conjugate each element in a double-precision complex floating-point vector. +* +* @module @stdlib/lapack/base/zlacgv +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zlacgv = require( '@stdlib/lapack/base/zlacgv' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zlacgv( 3, zx, 1 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 1.0 +* +* var im = imag( z ); +* // returns -2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zlacgv = require( '@stdlib/lapack/base/zlacgv' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zlacgv.ndarray( 3, 1, 0 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 1.0 +* +* var im = imag( z ); +* // returns -2.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zlacgv; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zlacgv = main; +} else { + zlacgv = tmp; +} + + +// EXPORTS // + +module.exports = zlacgv; + +// exports: { "ndarray": "zlacgv.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/main.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/main.js new file mode 100644 index 000000000000..6fcede7ec60e --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zlacgv = require( './zlacgv.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zlacgv, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zlacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js new file mode 100644 index 000000000000..d4584f505972 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + + +// MAIN // + +/** +* Conjugates each element in a double-precision complex floating-point vector. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} zx - input array +* @param {integer} strideZX - `zx` stride length +* @param {NonNegativeInteger} offsetZX - starting `zx` index +* @returns {Complex128Array} input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zlacgv( 3, zx, 1, 0 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 1.0 +* +* var im = imag( z ); +* // returns -2.0 +*/ +function zlacgv( N, zx, strideZX, offsetZX ) { + var zx64; + var ix; + var sx; + var i; + + if ( N <= 0 ) { + return zx; + } + // Reinterpret the input array as a real-valued array of interleaved real and imaginary components: + zx64 = reinterpret( zx, 0 ); + + // Adjust the strides and offset: + sx = strideZX * 2; + ix = ( offsetZX * 2 ) + 1; // index of the first imaginary component + + // Conjugate each element by negating the imaginary components... + for ( i = 0; i < N; i++ ) { + zx64[ ix ] = -zx64[ ix ]; + ix += sx; + } + return zx; +} + + +// EXPORTS // + +module.exports = zlacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/zlacgv.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/zlacgv.js new file mode 100644 index 000000000000..d4ed37909628 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/zlacgv.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Conjugates each element in a double-precision complex floating-point vector. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} zx - input array +* @param {integer} strideZX - `zx` stride length +* @returns {Complex128Array} input array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* zlacgv( 3, zx, 1 ); +* +* var z = zx.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 1.0 +* +* var im = imag( z ); +* // returns -2.0 +*/ +function zlacgv( N, zx, strideZX ) { + return ndarray( N, zx, strideZX, stride2offset( N, strideZX ) ); +} + + +// EXPORTS // + +module.exports = zlacgv; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/package.json b/lib/node_modules/@stdlib/lapack/base/zlacgv/package.json new file mode 100644 index 000000000000..83f9b07e6c0f --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/lapack/base/zlacgv", + "version": "0.0.0", + "description": "Conjugate each element in a double-precision complex floating-point vector.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "blas", + "level 1", + "linear", + "algebra", + "subroutines", + "zlacgv", + "conjugate", + "vector", + "typed", + "array", + "ndarray", + "complex", + "complex128", + "double", + "float64", + "float64array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.js new file mode 100644 index 000000000000..fa0b9473898e --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var isBrowser = require( '@stdlib/assert/is-browser' ); +var zlacgv = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': isBrowser +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlacgv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zlacgv.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zlacgv = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zlacgv, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zlacgv; + var main; + + main = require( './../lib/zlacgv.js' ); + + zlacgv = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zlacgv, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.ndarray.js new file mode 100644 index 000000000000..b9b98387173a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.ndarray.js @@ -0,0 +1,283 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zlacgv = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlacgv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( zlacgv.length, 4, 'arity of 4' ); + t.end(); +}); + +tape( 'the function conjugates elements in a strided array', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.3, // 1 + 0.1, // 1 + 0.5, // 2 + 0.0, // 2 + 0.0, // 3 + 0.5, // 3 + 0.0, // 4 + 0.2, // 4 + 2.0, + 3.0, + 2.0, + 3.0 + ]); + + zlacgv( 4, zx, 1, 0 ); + + expected = new Complex128Array([ + 0.3, // 1 + -0.1, // 1 + 0.5, // 2 + -0.0, // 2 + 0.0, // 3 + -0.5, // 3 + 0.0, // 4 + -0.2, // 4 + 2.0, + 3.0, + 2.0, + 3.0 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, // 1 + 0.1, // 1 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 3 + -0.3, // 3 + 7.0, + 2.0 + ]); + + zlacgv( 3, zx, 2, 0 ); + + expected = new Complex128Array([ + 0.1, // 1 + -0.1, // 1 + 3.0, + 6.0, + -0.6, // 2 + -0.1, // 2 + 4.0, + 7.0, + 0.1, // 3 + 0.3, // 3 + 7.0, + 2.0 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a negative `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, // 3 + 0.1, // 3 + 3.0, + 6.0, + -0.6, // 2 + 0.1, // 2 + 4.0, + 7.0, + 0.1, // 1 + -0.3, // 1 + 7.0, + 2.0 + ]); + + zlacgv( 3, zx, -2, 4 ); + + expected = new Complex128Array([ + 0.1, // 3 + -0.1, // 3 + 3.0, + 6.0, + -0.6, // 2 + -0.1, // 2 + 4.0, + 7.0, + 0.1, // 1 + 0.3, // 1 + 7.0, + 2.0 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `zx` offset', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + 6.0, // 1 + 0.1, // 2 + -0.3, // 2 + 7.0, // 3 + 2.0 // 3 + ]); + + zlacgv( 3, zx, 1, 3 ); + + expected = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + -6.0, // 1 + 0.1, // 2 + 0.3, // 2 + 7.0, // 3 + -2.0 // 3 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + out = zlacgv( 4, zx, 1, 0 ); + + t.strictEqual( out, zx, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0 + ]); + + zlacgv( -1, zx, 1, 0 ); + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + zlacgv( 0, zx, 1, 0 ); + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + 6.0, // 1 + 0.1, + -0.3, + 7.0, + 2.0, + 2.0, // 2 + 3.0 // 2 + ]); + + zlacgv( 2, zx, -3, 6 ); + + expected = new Complex128Array([ + 0.1, + 0.1, + 3.0, + 6.0, + -0.6, + 0.1, + 4.0, // 1 + -6.0, // 1 + 0.1, + -0.3, + 7.0, + 2.0, + 2.0, // 2 + -3.0 // 2 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.zlacgv.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.zlacgv.js new file mode 100644 index 000000000000..e60b44ebdee8 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/test/test.zlacgv.js @@ -0,0 +1,235 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zlacgv = require( './../lib/zlacgv.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlacgv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 3', function test( t ) { + t.strictEqual( zlacgv.length, 3, 'arity of 3' ); + t.end(); +}); + +tape( 'the function conjugates elements in a strided array', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 0.3, // 1 + 0.1, // 1 + 0.5, // 2 + 0.0, // 2 + 0.0, // 3 + 0.5, // 3 + 0.0, // 4 + 0.2 // 4 + ]); + + zlacgv( 4, zx, 1 ); + + expected = new Complex128Array([ + 0.3, // 1 + -0.1, // 1 + 0.5, // 2 + -0.0, // 2 + 0.0, // 3 + -0.5, // 3 + 0.0, // 4 + -0.2 // 4 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0, + 9.0, // 3 + 10.0, // 3 + 11.0, + 12.0 + ]); + + zlacgv( 3, zx, 2 ); + + expected = new Complex128Array([ + 1.0, // 1 + -2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + -6.0, // 2 + 7.0, + 8.0, + 9.0, // 3 + -10.0, // 3 + 11.0, + 12.0 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a negative `zx` stride', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array([ + 1.0, // 3 + 2.0, // 3 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0, + 9.0, // 1 + 10.0, // 1 + 11.0, + 12.0 + ]); + + zlacgv( 3, zx, -2 ); + + expected = new Complex128Array([ + 1.0, // 3 + -2.0, // 3 + 3.0, + 4.0, + 5.0, // 2 + -6.0, // 2 + 7.0, + 8.0, + 9.0, // 1 + -10.0, // 1 + 11.0, + 12.0 + ]); + + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + out = zlacgv( 4, zx, 1 ); + + t.strictEqual( out, zx, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the input array unchanged', function test( t ) { + var expected; + var zx; + + zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0 + ]); + + zlacgv( -1, zx, 1 ); + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + zlacgv( 0, zx, 1 ); + t.ok( isSameComplex128Array( zx, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var zx0; + var zx1; + + // Initial arrays... + zx0 = new Complex128Array([ + 0.1, + -0.3, + 8.0, // 1 + 9.0, // 1 + 0.5, // 2 + -0.1, // 2 + 2.0, // 3 + 5.0, // 3 + 2.0, + 3.0 + ]); + + // Create offset views... + zx1 = new Complex128Array( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + + zlacgv( 3, zx1, 1 ); + + expected = new Complex128Array([ + 0.1, + -0.3, + 8.0, // 1 + -9.0, // 1 + 0.5, // 2 + 0.1, // 2 + 2.0, // 3 + -5.0, // 3 + 2.0, + 3.0 + ]); + + t.ok( isSameComplex128Array( zx0, expected ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/README.md b/lib/node_modules/@stdlib/lapack/base/zlacpy/README.md new file mode 100644 index 000000000000..05af4bb9c09a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/README.md @@ -0,0 +1,275 @@ + + +# zlacpy + +> Copy all or part of a matrix `A` to another matrix `B`. + +
+ +## Usage + +```javascript +var zlacpy = require( '@stdlib/lapack/base/zlacpy' ); +``` + +#### zlacpy( order, uplo, M, N, A, LDA, B, LDB ) + +Copies all or part of a matrix `A` to another matrix `B`. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + +var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var B = new Complex128Array( 4 ); + +zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); + +var viewB = reinterpret( B, 0 ); +// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] +``` + +The function has the following parameters: + +- **order**: storage layout. +- **uplo**: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **A**: input [`Complex128Array`][@stdlib/array/complex128]. +- **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`). +- **B**: output [`Complex128Array`][@stdlib/array/complex128]. +- **LDB**: stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`). + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + +// Initial arrays... +var A0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var B0 = new Complex128Array( 5 ); + +// Create offset views... +var A1 = new Complex128Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var B1 = new Complex128Array( B0.buffer, B0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +zlacpy( 'row-major', 'all', 2, 2, A1, 2, B1, 2 ); + +var viewB = reinterpret( B0, 0 ); +// returns [ 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] +``` + +#### zlacpy.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob ) + +Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + +var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var B = new Complex128Array( 4 ); + +zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); + +var viewB = reinterpret( B, 0 ); +// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] +``` + +The function has the following parameters: + +- **uplo**: specifies whether to copy the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **A**: input [`Complex128Array`][@stdlib/array/complex128]. +- **sa1**: stride of the first dimension of `A`. +- **sa2**: stride of the second dimension of `A`. +- **oa**: starting index for `A`. +- **B**: output [`Complex128Array`][@stdlib/array/complex128]. +- **sb1**: stride of the first dimension of `B`. +- **sb2**: stride of the second dimension of `B`. +- **ob**: starting index for `B`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + +var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var B = new Complex128Array( 6 ); + +zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); + +var viewB = reinterpret( B, 0 ); +// returns [ 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] +``` + +
+ + + +
+ +## Notes + +- `zlacpy()` corresponds to the [LAPACK][lapack] routine [`zlacpy`][lapack-zlacpy]. + +
+ + + +
+ +## Examples + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var uniform = require( '@stdlib/random/array/discrete-uniform' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var zlacpy = require( '@stdlib/lapack/base/zlacpy' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex128Array( uniform( 2*N, -10, 10, { + 'dtype': 'generic' +})); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var B = new Complex128Array( uniform( 2*N, -10, 10, { + 'dtype': 'generic' +})); +console.log( ndarray2array( B, shape, strides, 0, order ) ); + +zlacpy( order, 'all', shape[ 0 ], shape[ 1 ], A, strides[ 0 ], B, strides[ 0 ] ); +console.log( ndarray2array( B, shape, strides, 0, order ) ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +TODO +``` + +#### TODO + +TODO. + +```c +TODO +``` + +TODO + +```c +TODO +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +TODO +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: https://www.netlib.org/lapack/explore-html/ + +[lapack-zlacpy]: https://netlib.org/lapack/explore-html/d0/d9e/group__lacpy_ga243f0a47458b9a525136a69146c10192.html#ga243f0a47458b9a525136a69146c10192 + +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/benchmark/benchmark.js new file mode 100644 index 000000000000..ad44b061ffa6 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var zlacpy = require( './../lib/zlacpy.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var opts; + var A; + var B; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + B = new Complex128Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = zlacpy( 'column-major', 'all', N, N, A, N, B, N ); + if ( isnan( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+':order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..52cd7ae0379b --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/benchmark/benchmark.ndarray.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var zlacpy = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var opts; + var A; + var B; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + B = new Complex128Array( uniform( 2*N*N, -10.0, 10.0, opts ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = zlacpy( 'all', N, N, A, 1, N, 0, B, 1, N, 0 ); + if ( isnan( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%z.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+':ndarray:order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/repl.txt new file mode 100644 index 000000000000..131b8e15583b --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/repl.txt @@ -0,0 +1,120 @@ + +{{alias}}( order, uplo, M, N, A, LDA, B, LDB ) + Copies all or part of a matrix `A` to another matrix `B`. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + Parameters + ---------- + order: string + Row-major (C-style) or column-major (Fortran-style) order. Must be + either 'row-major' or 'column-major'. + + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + A: Complex128Array + Input matrix `A`. + + LDA: integer + Stride of the first dimension of `A` (a.k.a., leading dimension of the + matrix `A`). + + B: Complex128Array + Output matrix `B`. + + LDB: integer + Stride of the first dimension of `B` (a.k.a., leading dimension of the + matrix `B`). + + Returns + ------- + B: Complex128Array + Output matrix. + + Examples + -------- + > var abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]; + > var bbuf = [ 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ]; + > var A = new {{alias:@stdlib/array/complex128}}( abuf ); + > var B = new {{alias:@stdlib/array/complex128}}( bbuf ); + > {{alias}}( 'row-major', 'all', 2, 2, A, 2, B, 2 ); + > var z = B.get( 0 ); + > {{alias:@stdlib/complex/float64/real}}( z ) + 1.0 + > {{alias:@stdlib/complex/float64/imag}}( z ) + 2.0 + + +{{alias}}.ndarray( uplo, M, N, A, sa1, sa2, oa, B, sb1, sb2, ob ) + Copies all or part of a matrix `A` to another matrix `B` using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + A: Complex128Array + Input matrix `A`. + + sa1: integer + Stride of the first dimension of `A`. + + sa2: integer + Stride of the second dimension of `A`. + + oa: integer + Starting index for `A`. + + B: Complex128Array + Output matrix `B`. + + sb1: integer + Stride of the first dimension of `B`. + + sb2: integer + Stride of the second dimension of `B`. + + ob: integer + Starting index for `B`. + + Returns + ------- + B: Complex128Array + Output matrix. + + Examples + -------- + > var abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]; + > var bbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var A = new {{alias:@stdlib/array/complex128}}( abuf ); + > var B = new {{alias:@stdlib/array/complex128}}( bbuf ); + > {{alias}}.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); + > var z = B.get( 2 ); + > {{alias:@stdlib/complex/float64/real}}( z ) + 3.0 + > {{alias:@stdlib/complex/float64/imag}}( z ) + 4.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/types/index.d.ts new file mode 100644 index 000000000000..44091c88601d --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/types/index.d.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Layout } from '@stdlib/types/blas'; +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zlacpy`. +*/ +interface Routine { + /** + * Copies all or part of a matrix `A` to another matrix `B`. + * + * @param order - storage layout of `A` and `B` + * @param uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param A - input matrix + * @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) + * @param B - output matrix + * @param LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) + * @returns `B` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var B = new Complex128Array( 4 ); + * + * zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); + * + * var z = B.get( 0 ); + * // returns + * + * var v = real( z ); + * // returns 1.0 + * + * v = imag( z ); + * // returns 2.0 + */ + ( order: Layout, uplo: string, M: number, N: number, A: Complex128Array, LDA: number, B: Complex128Array, LDB: number ): Complex128Array; + + /** + * Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics. + * + * @param uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param A - input matrix + * @param strideA1 - stride of the first dimension of `A` + * @param strideA2 - stride of the second dimension of `A` + * @param offsetA - starting index for `A` + * @param B - output matrix + * @param strideB1 - stride of the first dimension of `B` + * @param strideB2 - stride of the second dimension of `B` + * @param offsetB - starting index for `B` + * @returns `B` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); + * var B = new Complex128Array( 12 ); + * + * zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); + * + * var z = B.get( 2 ); + * // returns + * + * var v = real( z ); + * // returns 3.0 + * + * v = imag( z ); + * // returns 4.0 + */ + ndarray( uplo: string, M: number, N: number, A: Complex128Array, strideA1: number, strideA2: number, offsetA: number, B: Complex128Array, strideB1: number, strideB2: number, offsetB: number ): Complex128Array; +} + +/** +* Copies all or part of a matrix `A` to another matrix `B`. +* +* @param order - storage layout of `A` and `B` +* @param uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param M - number of rows in matrix `A` +* @param N - number of columns in matrix `A` +* @param A - input matrix +* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @param B - output matrix +* @param LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) +* @returns `B` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex128Array( 12 ); +* +* zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +*/ +declare var zlacpy: Routine; + + +// EXPORTS // + +export = zlacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/types/test.ts new file mode 100644 index 000000000000..a18f5b3ac71a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/docs/types/test.ts @@ -0,0 +1,359 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import zlacpy = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a string... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 5, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( true, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( false, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( null, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( void 0, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( [], 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( {}, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( ( x: number ): number => x, 'all', 2, 2, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a string... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 5, 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', true, 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', false, 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', null, 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', void 0, 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', [], 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', {}, 2, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', ( x: number ): number => x, 2, 2, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 'all', '5', 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', true, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', false, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', null, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', void 0, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', [], 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', {}, 2, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', ( x: number ): number => x, 2, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 'all', 2, '5', A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, true, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, false, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, null, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, void 0, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, [], A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, {}, A, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, ( x: number ): number => x, A, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Complex128Array... +{ + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 'all', 2, 2, '5', 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, 5, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, true, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, false, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, null, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, void 0, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, [], 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, {}, 2, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, ( x: number ): number => x, 2, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 'all', 2, 2, A, '5', B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, true, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, false, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, null, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, void 0, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, [], B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, {}, B, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, ( x: number ): number => x, B, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a Complex128Array... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + zlacpy( 'row-major', 'all', 2, 2, A, 2, '5', 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, 5, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, true, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, false, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, null, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, void 0, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, [], 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, {}, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, ( x: number ): number => x, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, '5' ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, true ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, false ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, null ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, void 0 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, [] ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, {} ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy(); // $ExpectError + zlacpy( 'row-major' ); // $ExpectError + zlacpy( 'row-major', 'all' ); // $ExpectError + zlacpy( 'row-major', 'all', 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2 ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B ); // $ExpectError + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a string... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 5, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( true, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( false, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( null, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( void 0, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( [], 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( {}, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( ( x: number ): number => x, 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', '5', 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', true, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', false, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', null, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', void 0, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', [], 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', {}, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', ( x: number ): number => x, 2, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, '5', A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, true, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, false, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, null, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, void 0, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, [], A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, {}, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, ( x: number ): number => x, A, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex128Array... +{ + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, '5', 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, 5, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, true, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, false, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, null, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, void 0, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, [], 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, {}, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, ( x: number ): number => x, 2, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, '5', 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, true, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, false, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, null, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, void 0, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, [], 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, {}, 1, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, ( x: number ): number => x, 1, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, '5', 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, true, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, false, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, null, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, void 0, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, [], 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, {}, 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, ( x: number ): number => x, 0, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, '5', B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, true, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, false, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, null, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, void 0, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, [], B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, {}, B, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, ( x: number ): number => x, B, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a Complex128Array... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, '5', 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, 5, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, true, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, false, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, null, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, void 0, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, [], 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, {}, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, ( x: number ): number => x, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a ninth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, '5', 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, true, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, false, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, null, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, void 0, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, [], 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, {}, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a tenth argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, '5', 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, true, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, false, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, null, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, void 0, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, [], 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, {}, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eleventh argument which is not a number... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, '5' ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, true ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, false ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, null ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, void 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, [] ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, {} ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + const B = new Complex128Array( 4 ); + + zlacpy.ndarray(); // $ExpectError + zlacpy.ndarray( 'all' ); // $ExpectError + zlacpy.ndarray( 'all', 2 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1 ); // $ExpectError + zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/examples/index.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/examples/index.js new file mode 100644 index 000000000000..8830534f3d0f --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var uniform = require( '@stdlib/random/array/discrete-uniform' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var dlacpy = require( './../lib' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex128Array( uniform( 2*N, -10, 10, { + 'dtype': 'float64' +})); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var B = new Complex128Array( uniform( 2*N, -10, 10, { + 'dtype': 'float64' +})); +console.log( ndarray2array( B, shape, strides, 0, order ) ); + +dlacpy( order, 'all', shape[ 0 ], shape[ 1 ], A, strides[ 0 ], B, strides[ 0 ] ); +console.log( ndarray2array( B, shape, strides, 0, order ) ); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/base.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/base.js new file mode 100644 index 000000000000..d974bdeaa162 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/base.js @@ -0,0 +1,614 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len, max-params */ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); +var loopOrder = require( '@stdlib/ndarray/base/unary-loop-interchange-order' ); +var min = require( '@stdlib/math/base/special/fast/min' ); + + +// FUNCTIONS // + +/** +* Copies all of a matrix `A` to another matrix `B`. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Float64Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Float64Array} B - output matrix view +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Float64Array} `B` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, 4, 2, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, 4, -2, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 1.0, 2.0, 7.0, 8.0, 5.0, 6.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, -4, 2, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 7.0, 8.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, -4, -2, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 5.0, 6.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, 2, 4, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 5.0, 6.0, 3.0, 4.0, 7.0, 8.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, -2, 4, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 7.0, 8.0, 1.0, 2.0, 5.0, 6.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, 2, -4, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 1.0, 2.0, 7.0, 8.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyAll( 2, 2, A, -2, -4, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 3.0, 4.0, 5.0, 6.0, 1.0, 2.0 ] +*/ +function copyAll( M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var da0; + var da1; + var db0; + var db1; + var sh; + var S0; + var S1; + var sa; + var sb; + var ia; + var ib; + var i0; + var i1; + var o; + + // Resolve the loop interchange order: + o = loopOrder( [ M, N ], [ strideA1, strideA2 ], [ strideB1, strideB2 ] ); + sh = o.sh; + sa = o.sx; + sb = o.sy; + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + da0 = sa[ 0 ]; + da1 = sa[ 1 ] - ( S0*sa[0] ); + db0 = sb[ 0 ]; + db1 = sb[ 1 ] - ( S0*sb[0] ); + + // Set the pointers to the first indexed elements in the respective matrices... + ia = offsetA; + ib = offsetB; + + // Iterate over the matrix dimensions... + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + B[ ib ] = A[ ia ]; + B[ ib+1 ] = A[ ia+1 ]; + ia += da0; + ib += db0; + } + ia += da1; + ib += db1; + } + return B; +} + +/** +* Copies the upper triangular/trapezoidal part of a matrix `A` to another matrix `B`. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Float64Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Float64Array} B - output matrix view +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Float64Array} `B` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, 4, 2, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, 4, -2, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 5.0, 6.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, -4, 2, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 7.0, 8.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, -4, -2, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 5.0, 6.0, 0.0, 0.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, 2, 4, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 5.0, 6.0, 0.0, 0.0, 7.0, 8.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, -2, 4, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 7.0, 8.0, 0.0, 0.0, 5.0, 6.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, 2, -4, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyUpper( 2, 2, A, -2, -4, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 3.0, 4.0, 0.0, 0.0, 1.0, 2.0 ] +*/ +function copyUpper( M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var ia; + var ib; + var i0; + var i1; + var ja; + var jb; + + ia = offsetA; + ib = offsetB; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + ja = ia + ( i1*strideA2 ); + jb = ib + ( i1*strideB2 ); + for ( i0 = i1; i0 < N; i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA2; + jb += strideB2; + } + ia += strideA1; + ib += strideB1; + } + return B; + } + for ( i1 = 0; i1 < N; i1++ ) { + jb = ib; + ja = ia; + for ( i0 = 0; i0 <= min( i1, M-1 ); i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA1; + jb += strideB1; + } + ia += strideA2; + ib += strideB2; + } + return B; +} + +/** +* Copies the lower triangular/trapezoidal part of a matrix `A` to another matrix `B`. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Float64Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Float64Array} B - output matrix +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Float64Array} `B` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, 4, 2, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 7.0, 8.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, 4, -2, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 0.0, 0.0, 7.0, 8.0, 5.0, 6.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, -4, 2, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, -4, -2, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, 2, 4, 0, B, 4, 2, 0 ); +* // B => [ 1.0, 2.0, 0.0, 0.0, 3.0, 4.0, 7.0, 8.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, -2, 4, 2, B, 4, 2, 0 ); +* // B => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 5.0, 6.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, 2, -4, 4, B, 4, 2, 0 ); +* // B => [ 5.0, 6.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Float64Array( 8 ); +* +* copyLower( 2, 2, A, -2, -4, 6, B, 4, 2, 0 ); +* // B => [ 7.0, 8.0, 0.0, 0.0, 5.0, 6.0, 1.0, 2.0 ] +*/ +function copyLower( M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var ia; + var ib; + var i0; + var i1; + var ja; + var jb; + + ia = offsetA; + ib = offsetB; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + ja = ia; + jb = ib; + for ( i0 = 0; i0 <= min( i1, N-1 ); i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA2; + jb += strideB2; + } + ia += strideA1; + ib += strideB1; + } + return B; + } + for ( i1 = 0; i1 < N; i1++ ) { + ja = ia + ( i1*strideA1 ); + jb = ib + ( i1*strideB1 ); + for ( i0 = i1; i0 < M; i0++ ) { + B[ jb ] = A[ ja ]; + B[ jb+1 ] = A[ ja+1 ]; + ja += strideA1; + jb += strideB1; + } + ia += strideA2; + ib += strideB2; + } + return B; +} + + +// MAIN // + +/** +* Copies all or part of a matrix `A` to another matrix `B`. +* +* @private +* @param {string} uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex128Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Complex128Array} B - output matrix +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Complex128Array} `B` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'all', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +* +* z = B.get( 2 ); +* // returns +* +* v = real( z ); +* // returns 5.0 +* +* v = imag( z ); +* // returns 6.0 +* +* z = B.get( 3 ); +* // returns +* +* v = real( z ); +* // returns 7.0 +* +* v = imag( z ); +* // returns 8.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'upper', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); +* // B => +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +* +* z = B.get( 2 ); +* // returns +* +* v = real( z ); +* // returns 0.0 +* +* v = imag( z ); +* // returns 0.0 +* +* z = B.get( 3 ); +* // returns +* +* v = real( z ); +* // returns 7.0 +* +* v = imag( z ); +* // returns 8.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'lower', 2, 2, A, 2, 1, 0, B, 2, 1, 0 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = real( z ); +* // returns 0.0 +* +* v = imag( z ); +* // returns 0.0 +* +* z = B.get( 2 ); +* // returns +* +* v = real( z ); +* // returns 5.0 +* +* v = imag( z ); +* // returns 6.0 +* +* z = B.get( 3 ); +* // returns +* +* v = real( z ); +* // returns 7.0 +* +* v = imag( z ); +* // returns 8.0 +*/ +function zlacpy( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { + var viewA; + var viewB; + + // Reinterpret the input and output arrays as real-valued arrays of interleaved real and imaginary components: + viewA = reinterpret( A, 0 ); + viewB = reinterpret( B, 0 ); + + // Adjust the strides and offsets accordingly: + strideA1 *= 2; + strideA2 *= 2; + strideB1 *= 2; + strideB2 *= 2; + + offsetA *= 2; + offsetB *= 2; + + if ( uplo === 'upper' ) { + copyUpper( M, N, viewA, strideA1, strideA2, offsetA, viewB, strideB1, strideB2, offsetB ); + } else if ( uplo === 'lower' ) { + copyLower( M, N, viewA, strideA1, strideA2, offsetA, viewB, strideB1, strideB2, offsetB ); + } else { + copyAll( M, N, viewA, strideA1, strideA2, offsetA, viewB, strideB1, strideB2, offsetB ); + } + return B; +} + + +// EXPORTS // + +module.exports = zlacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/index.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/index.js new file mode 100644 index 000000000000..1b4e0a1b3328 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/index.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK routine to copy all or part of a matrix `A` to another matrix `B`. +* +* @module @stdlib/lapack/base/zlacpy +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zlacpy = require( '@stdlib/lapack/base/zlacpy' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zlacpy = require( '@stdlib/lapack/base/zlacpy' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex128Array( 12 ); +* +* zlacpy.ndarray( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zlacpy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zlacpy = main; +} else { + zlacpy = tmp; +} + + +// EXPORTS // + +module.exports = zlacpy; + +// exports: { "ndarray": "zlacpy.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/main.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/main.js new file mode 100644 index 000000000000..1a9441000e87 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zlacpy = require( './zlacpy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zlacpy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zlacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/ndarray.js new file mode 100644 index 000000000000..c0336a8f34bb --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/ndarray.js @@ -0,0 +1,126 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var base = require( './base.js' ); + + +// MAIN // + +/** +* Copies all or part of a matrix `A` to another matrix `B` using alternative indexing semantics. +* +* @param {string} uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex128Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @param {Complex128Array} B - output matrix +* @param {integer} strideB1 - stride of the first dimension of `B` +* @param {integer} strideB2 - stride of the second dimension of `B` +* @param {NonNegativeInteger} offsetB - starting index for `B` +* @returns {Complex128Array} `B` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex128Array( 12 ); +* +* zlacpy( 'all', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex128Array( 12 ); +* +* zlacpy( 'upper', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +* +* z = B.get( 4 ); +* // returns +* +* v = real( z ); +* // returns 0.0 +* +* v = imag( z ); +* // returns 0.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +* var B = new Complex128Array( 12 ); +* +* zlacpy( 'lower', 2, 2, A, 2, 1, 1, B, 2, 1, 2 ); +* +* var z = B.get( 2 ); +* // returns +* +* var v = real( z ); +* // returns 3.0 +* +* v = imag( z ); +* // returns 4.0 +* +* z = B.get( 1 ); +* // returns +* +* v = real( z ); +* // returns 0.0 +* +* v = imag( z ); +* // returns 0.0 +*/ +function zlacpy( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ) { // eslint-disable-line max-len, max-params + return base( uplo, M, N, A, strideA1, strideA2, offsetA, B, strideB1, strideB2, offsetB ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = zlacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/zlacpy.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/zlacpy.js new file mode 100644 index 000000000000..9573118e2ea2 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/lib/zlacpy.js @@ -0,0 +1,152 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); +var format = require( '@stdlib/string/format' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Copies all or part of a matrix `A` to another matrix `B`. +* +* @param {string} order - storage layout of `A` and `B` +* @param {string} uplo - specifies whether to copy the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex128Array} A - input matrix +* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @param {Complex128Array} B - output matrix +* @param {PositiveInteger} LDB - stride of the first dimension of `B` (a.k.a., leading dimension of the matrix `B`) +* @throws {TypeError} first argument must be a valid order +* @throws {RangeError} sixth argument must be greater than or equal to `N` +* @throws {RangeError} eighth argument must be greater than or equal to `N` +* @returns {Complex128Array} `B` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'row-major', 'all', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'row-major', 'upper', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* z = B.get( 2 ); +* // returns +* +* v = real( z ); +* // returns 0.0 +* +* v = imag( z ); +* // returns 0.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var B = new Complex128Array( 4 ); +* +* zlacpy( 'row-major', 'lower', 2, 2, A, 2, B, 2 ); +* +* var z = B.get( 0 ); +* // returns +* +* var v = real( z ); +* // returns 1.0 +* +* v = imag( z ); +* // returns 2.0 +* +* z = B.get( 1 ); +* // returns +* +* v = real( z ); +* // returns 0.0 +* +* v = imag( z ); +* // returns 0.0 +*/ +function zlacpy( order, uplo, M, N, A, LDA, B, LDB ) { + var sa1; + var sa2; + var sb1; + var sb2; + if ( !isLayout( order ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); + } + if ( order === 'column-major' ) { + sa1 = 1; + sa2 = LDA; + sb1 = 1; + sb2 = LDB; + } else { // order === 'row-major' + if ( LDA < N ) { + throw new RangeError( format( 'invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.', N, LDA ) ); + } + if ( LDB < N ) { + throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.', N, LDB ) ); + } + sa1 = LDA; + sa2 = 1; + sb1 = LDB; + sb2 = 1; + } + return base( uplo, M, N, A, sa1, sa2, 0, B, sb1, sb2, 0 ); +} + + +// EXPORTS // + +module.exports = zlacpy; diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/package.json b/lib/node_modules/@stdlib/lapack/base/zlacpy/package.json new file mode 100644 index 000000000000..78cd5c64976a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/lapack/base/zlacpy", + "version": "0.0.0", + "description": "Copy all or part of a matrix A to another matrix B.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "zlacpy", + "copy", + "linear", + "algebra", + "subroutines", + "array", + "ndarray", + "matrix", + "complex128", + "complex128array" + ] +} diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.js new file mode 100644 index 000000000000..5c5fb7c1ff25 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zlacpy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlacpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zlacpy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zlacpy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zlacpy, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zlacpy; + var main; + + main = require( './../lib/zlacpy.js' ); + + zlacpy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zlacpy, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.ndarray.js new file mode 100644 index 000000000000..d1d2bad06c70 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.ndarray.js @@ -0,0 +1,270 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zlacpy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlacpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 11', function test( t ) { + t.strictEqual( zlacpy.length, 11, 'returns expected value' ); + t.end(); +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (row-major)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0] ); + + out = zlacpy( 'all', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 22.0, 23.0, 20.0, 21.0, 18.0, 19.0, 16.0, 17.0, 14.0, 15.0, 12.0, 13.0 ] ); + + out = zlacpy( 'all', 2, 3, A, -3, -1, 6, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'all', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major, upper)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 0.0, 0.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'upper', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 22.0, 23.0, 20.0, 21.0, 18.0, 19.0, 0.0, 0.0, 14.0, 15.0, 12.0, 13.0 ] ); + + out = zlacpy( 'upper', 2, 3, A, -3, -1, 6, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 0.0, 0.0, 18.0, 19.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = zlacpy( 'upper', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok(isSameComplex128Array(out, expected), 'returns expected value'); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (row-major, lower)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 20.0, 21.0, 0.0, 0.0 ] ); + + out = zlacpy( 'lower', 2, 3, A, 3, 1, 1, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok(isSameComplex128Array(out, expected), 'returns expected value'); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 0.0, 0.0 ] ); + + out = zlacpy( 'lower', 2, 3, A, -3, 1, 4, B, 3, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'lower', 3, 2, A, 2, 1, 1, B, 2, 1, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + t.end(); +}); +tape( 'the function copies all of a matrix `A` to another matrix `B` (column-major)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'all', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 22.0, 23.0, 20.0, 21.0, 18.0, 19.0, 16.0, 17.0, 14.0, 15.0, 12.0, 13.0 ] ); + + out = zlacpy( 'all', 2, 3, A, 1, 2, 1, B, -1, -2, 8 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'all', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (column-major, upper)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'upper', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 18.0, 19.0, 16.0, 17.0, 22.0, 23.0, 20.0, 21.0 ] ); + + out = zlacpy( 'upper', 2, 3, A, 1, 2, 1, B, -1, 2, 4 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 20.0, 21.0, 0.0, 0.0 ] ); + + out = zlacpy( 'upper', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies part of a matrix `A` to another matrix `B` (column-major, lower)', function test( t ) { + var expected; + var out; + var A; + var B; + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 0.0, 0.0, 18.0, 19.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = zlacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, 2, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 18.0, 19.0, 12.0, 13.0, 14.0, 15.0 ] ); + + out = zlacpy( 'lower', 2, 3, A, 1, 2, 1, B, 1, -2, 7 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + A = new Complex128Array( [ 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0 ] ); + B = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 0.0, 0.0, 20.0, 21.0, 22.0, 23.0 ] ); + + out = zlacpy( 'lower', 3, 2, A, 1, 3, 1, B, 1, 3, 3 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, expected ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (column-major, lower, complex access patterns)', function test( t ) { + var out; + var A; + var B; + + /* eslint-disable array-element-newline, no-multi-spaces */ + + A = new Complex128Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 1, 2, 999, 999, 3, 4, 999, 999, 5, 6, + 999, 999, 7, 8, 999, 999, 9, 10, 999, 999, 11, 12, + 999, 999, 13, 14, 999, 999, 15, 16, 999, 999, 17, 18, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + B = new Complex128Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + + /* eslint-enable array-element-newline, no-multi-spaces */ + + out = zlacpy( 'all', 3, 3, A, 2, 6, 7, B, 2, 6, 7 ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.zlacpy.js b/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.zlacpy.js new file mode 100644 index 000000000000..e39ab1ad798d --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlacpy/test/test.zlacpy.js @@ -0,0 +1,283 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var zlacpy = require( './../lib/zlacpy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlacpy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( zlacpy.length, 8, 'returns expected value' ); + t.end(); +}); + +tape( 'the function throws an error if provided an invalid first argument', function test( t ) { + var values; + var A; + var B; + var i; + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + + A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + B = new Complex128Array( 4 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zlacpy( value, 'all', 2, 2, A, 2, B, 2 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid sixth argument (row-major)', function test( t ) { + var values; + var A; + var B; + var i; + + values = [ + 0, + 1 + ]; + + A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + B = new Complex128Array( 4 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zlacpy( 'row-major', 'all', 2, 2, A, value, B, 2 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid eighth argument (row-major)', function test( t ) { + var values; + var A; + var B; + var i; + + values = [ + 0, + 1 + ]; + + A = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + B = new Complex128Array( 4 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zlacpy( 'row-major', 'all', 2, 2, A, 2, B, value ); + }; + } +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (row-major)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex128Array( M*N ); + + out = zlacpy( 'row-major', 'all', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (row-major, upper)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex128Array( M*N ); + + out = zlacpy( 'row-major', 'lower', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + + out = zlacpy( 'row-major', 'upper', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (row-major, lower)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex128Array( M*N ); + + out = zlacpy( 'row-major', 'upper', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + + out = zlacpy( 'row-major', 'lower', M, N, A, N, B, N ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies all of a matrix `A` to another matrix `B` (column-major)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex128Array( M*N ); + + out = zlacpy( 'column-major', 'all', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (column-major, upper)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex128Array( M*N ); + + out = zlacpy( 'column-major', 'lower', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + + out = zlacpy( 'column-major', 'upper', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function copies a part of a matrix `A` to another matrix `B` (column-major, lower)', function test( t ) { + var opts; + var out; + var A; + var B; + var M; + var N; + + M = 5; + N = 8; + + opts = { + 'dtype': 'float64' + }; + + A = new Complex128Array( uniform( M*N*2, -10.0, 10.0, opts ) ); + B = new Complex128Array( M*N ); + + out = zlacpy( 'column-major', 'upper', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + + out = zlacpy( 'column-major', 'lower', M, N, A, M, B, M ); + t.strictEqual( out, B, 'returns expected value' ); + t.ok( isSameComplex128Array( out, A ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/README.md b/lib/node_modules/@stdlib/lapack/base/zlaset/README.md new file mode 100644 index 000000000000..ae4c6a94f5f7 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/README.md @@ -0,0 +1,333 @@ + + +# zlaset + +> Set the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. + +
+ +## Usage + +```javascript +var zlaset = require( '@stdlib/lapack/base/zlaset' ); +``` + +#### zlaset( order, uplo, M, N, alpha, beta, A, LDA ) + +Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var A = new Complex128Array( 4 ); + +var alpha = new Complex128( 1.0, 2.0 ); +var beta = new Complex128( 3.0, 4.0 ); + +zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); + +var z = A.get( 0 ); +// returns + +var re = real( z ); +// returns 3.0 + +var im = imag( z ); +// returns 4.0 + +z = A.get( 1 ); +// returns + +re = real( z ); +// returns 1.0 + +im = imag( z ); +// returns 2.0 +``` + +The function has the following parameters: + +- **order**: storage layout. +- **uplo**: specifies whether to set the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **alpha**: value assigned to off-diagonal elements. +- **beta**: value assigned to diagonal elements. +- **A**: input [`Complex128Array`][@stdlib/array/complex128]. +- **LDA**: stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`). + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +// Initial array: +var A0 = new Complex128Array( 5 ); + +// Create offset view: +var A1 = new Complex128Array( A0.buffer, A0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var alpha = new Complex128( 1.0, 2.0 ); +var beta = new Complex128( 3.0, 4.0 ); + +zlaset( 'row-major', 'all', 2, 2, alpha, beta, A1, 2 ); + +var z = A0.get( 1 ); +// returns + +var re = real( z ); +// returns 3.0 + +var im = imag( z ); +// returns 4.0 +``` + +#### zlaset.ndarray( uplo, M, N, alpha, beta, A, sa1, sa2, oa ) + +Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var A = new Complex128Array( 4 ); + +var alpha = new Complex128( 1.0, 2.0 ); +var beta = new Complex128( 3.0, 4.0 ); + +zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); + +var z = A.get( 0 ); +// returns + +var re = real( z ); +// returns 3.0 + +var im = imag( z ); +// returns 4.0 + +z = A.get( 1 ); +// returns + +re = real( z ); +// returns 1.0 + +im = imag( z ); +// returns 2.0 +``` + +The function has the following parameters: + +- **uplo**: specifies whether to set the upper or lower triangular/trapezoidal part of a matrix `A`. +- **M**: number of rows in `A`. +- **N**: number of columns in `A`. +- **alpha**: value assigned to off-diagonal elements. +- **beta**: value assigned to diagonal elements. +- **A**: input [`Complex128Array`][@stdlib/array/complex128]. +- **sa1**: stride of the first dimension of `A`. +- **sa2**: stride of the second dimension of `A`. +- **oa**: starting index for `A`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var A = new Complex128Array( 5 ); + +var alpha = new Complex128( 1.0, 2.0 ); +var beta = new Complex128( 3.0, 4.0 ); + +zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); + +var z = A.get( 0 ); +// returns + +var re = real( z ); +// returns 0.0 + +var im = imag( z ); +// returns 0.0 + +z = A.get( 1 ); +// returns + +re = real( z ); +// returns 3.0 + +im = imag( z ); +// returns 4.0 +``` + +
+ + + +
+ +## Notes + +- `zlaset()` corresponds to the [LAPACK][lapack] routine [`zlaset`][lapack-zlaset]. + +
+ + + +
+ +## Examples + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var zlaset = require( '@stdlib/lapack/base/zlaset' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex128Array( N ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var alpha = new Complex128( 1.0, 2.0 ); +var beta = new Complex128( 3.0, 4.0 ); + +zlaset( order, 'all', shape[ 0 ], shape[ 1 ], alpha, beta, A, strides[ 0 ] ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +TODO +``` + +#### TODO + +TODO. + +```c +TODO +``` + +TODO + +```c +TODO +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +TODO +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: https://www.netlib.org/lapack/explore-html/ + +[lapack-zlaset]: https://www.netlib.org/lapack/explore-html/d0/de5/group__laset_gaf2a0d5a8d17c28cb3cb1f36a77bb8537.html#gaf2a0d5a8d17c28cb3cb1f36a77bb8537 + +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/zlaset/benchmark/benchmark.js new file mode 100644 index 000000000000..a169f03a8394 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/benchmark/benchmark.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var zlaset = require( './../lib/zlaset.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var alpha; + var beta; + var abuf; + var A; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + abuf = new Float64Array( N*N*2 ); + A = new Complex128Array( abuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zlaset( 'column-major', 'all', N, N, alpha, beta, A, N ); + if ( isnan( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+'::equidimensional:order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlaset/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..f1c535b69f60 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/benchmark/benchmark.ndarray.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var pkg = require( './../package.json' ).name; +var zlaset = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - number of elements along each dimension +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var alpha; + var beta; + var abuf; + var A; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + abuf = new Float64Array( N*N*2 ); + A = new Complex128Array( abuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zlaset( 'all', N, N, alpha, beta, A, 1, N, 0 ); + if ( isnan( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( abuf[ i%abuf.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var N; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + N = floor( pow( pow( 10, i ), 1.0/2.0 ) ); + f = createBenchmark( N ); + bench( pkg+'::equidimensional:ndarray:order=column-major,size='+(N*N), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/zlaset/docs/repl.txt new file mode 100644 index 000000000000..3e3c1767f725 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/docs/repl.txt @@ -0,0 +1,113 @@ + +{{alias}}( order, uplo, M, N, alpha, beta, A, LDA ) + Sets the off-diagonal elements and the diagonal elements of a double- + precision complex floating-point matrix `A` to specified values. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + Parameters + ---------- + order: string + Row-major (C-style) or column-major (Fortran-style) order. Must be + either 'row-major' or 'column-major'. + + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + alpha: Complex128 + Value assigned to off-diagonal elements. + + beta: Complex128 + Value assigned to diagonal elements. + + A: Complex128Array + Input matrix `A`. + + LDA: integer + Stride of the first dimension of `A` (a.k.a., leading dimension of the + matrix `A`). + + Returns + ------- + A: Complex128Array + Input matrix. + + Examples + -------- + > var A = new {{alias:@stdlib/array/complex128}}( 4 ); + > var alpha = new {{alias:@stdlib/complex/float64/ctor}}( 1.0, 2.0 ); + > var beta = new {{alias:@stdlib/complex/float64/ctor}}( 3.0, 4.0 ); + > {{alias}}( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); + > var z = A.get( 0 ); + > {{alias:@stdlib/complex/float64/real}}( z ) + 3.0 + > {{alias:@stdlib/complex/float64/imag}}( z ) + 4.0 + + +{{alias}}.ndarray( uplo, M, N, alpha, beta, A, sa1, sa2, oa ) + Sets the off-diagonal elements and the diagonal elements of a double- + precision complex floating-point matrix `A` to specified values using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + uplo: string + Specifies whether to copy the upper or lower triangular/trapezoidal part + of a matrix `A`. + + M: integer + Number of rows in `A`. + + N: integer + Number of columns in `A`. + + alpha: Complex128 + Value assigned to off-diagonal elements. + + beta: Complex128 + Value assigned to diagonal elements. + + A: Complex128Array + Input matrix `A`. + + sa1: integer + Stride of the first dimension of `A`. + + sa2: integer + Stride of the second dimension of `A`. + + oa: integer + Starting index for `A`. + + Returns + ------- + A: Complex128Array + Input matrix. + + Examples + -------- + > var A = new {{alias:@stdlib/array/complex128}}( 5 ); + > var alpha = new {{alias:@stdlib/complex/float64/ctor}}( 1.0, 2.0 ); + > var beta = new {{alias:@stdlib/complex/float64/ctor}}( 3.0, 4.0 ); + > {{alias}}.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); + > var z = A.get( 1 ); + > {{alias:@stdlib/complex/float64/real}}( z ) + 3.0 + > {{alias:@stdlib/complex/float64/imag}}( z ) + 4.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/zlaset/docs/types/index.d.ts new file mode 100644 index 000000000000..5d067a66672b --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/docs/types/index.d.ts @@ -0,0 +1,127 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; +import { Complex128 } from '@stdlib/types/complex'; +import { Layout } from '@stdlib/types/blas'; + +/** +* Interface describing `zlaset`. +*/ +interface Routine { + /** + * Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. + * + * @param order - storage layout of `A` + * @param uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param alpha - value assigned to off-diagonal elements + * @param beta - value assigned to diagonal elements + * @param A - input matrix + * @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) + * @returns `A` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * + * var A = new Complex128Array( 4 ); + * + * var alpha = new Complex128( 1.0, 2.0 ); + * var beta = new Complex128( 3.0, 4.0 ); + * + * zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); + * // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] + */ + ( order: Layout, uplo: string, M: number, N: number, alpha: Complex128, beta: Complex128, A: Complex128Array, LDA: number ): Complex128Array; + + /** + * Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values using alternative indexing semantics. + * + * @param uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` + * @param M - number of rows in matrix `A` + * @param N - number of columns in matrix `A` + * @param alpha - value assigned to off-diagonal elements + * @param beta - value assigned to diagonal elements + * @param A - input matrix + * @param strideA1 - stride of the first dimension of `A` + * @param strideA2 - stride of the second dimension of `A` + * @param offsetA - starting index for `A` + * @returns `A` + * + * @example + * var Complex128Array = require( '@stdlib/array/float64' ); + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * + * var A = new Complex128Array( 4 ); + * + * var alpha = new Complex128( 1.0, 2.0 ); + * var beta = new Complex128( 3.0, 4.0 ); + * + * zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); + * // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] + */ + ndarray( uplo: string, M: number, N: number, alpha: Complex128, beta: Complex128, A: Complex128Array, strideA1: number, strideA2: number, offsetA: number ): Complex128Array; +} + +/** +* Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. +* +* @param order - storage layout of `A` +* @param uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param M - number of rows in matrix `A` +* @param N - number of columns in matrix `A` +* @param alpha - value assigned to off-diagonal elements +* @param beta - value assigned to diagonal elements +* @param A - input matrix +* @param LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @returns `A` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var A = new Complex128Array( 5 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset.ndarray( 'all', 2, 2, A, 2, 1, 1 ); +* // A => [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +*/ +declare var zlaset: Routine; + + +// EXPORTS // + +export = zlaset; diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/zlaset/docs/types/test.ts new file mode 100644 index 000000000000..57b1e7a37fa9 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/docs/types/test.ts @@ -0,0 +1,348 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import zlaset = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a string... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 5, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( true, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( false, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( null, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( void 0, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( [], 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( {}, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( ( x: number ): number => x, 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a string... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 5, 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', true, 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', false, 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', null, 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', void 0, 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', [], 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', {}, 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', ( x: number ): number => x, 2, 2, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 'all', '5', 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', true, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', false, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', null, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', void 0, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', [], 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', {}, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', ( x: number ): number => x, 2, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 'all', 2, '5', alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, true, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, false, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, null, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, void 0, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, [], alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, {}, alpha, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, ( x: number ): number => x, alpha, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a complex number... +{ + const A = new Complex128Array( 4 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 'all', 2, 2, '5', beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, 5, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, true, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, false, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, null, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, void 0, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, [], beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, {}, beta, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, ( x: number ): number => x, beta, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a complex number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + + zlaset( 'row-major', 'all', 2, 2, alpha, '5', A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, true, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, false, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, null, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, void 0, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, [], A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, {}, A, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, ( x: number ): number => x, A, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a Complex128Array... +{ + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 'all', 2, 2, alpha, beta, '5', 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, 5, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, true, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, false, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, null, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, void 0, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, [], 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, {}, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, ( x: number ): number => x, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an eighth argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, '5' ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, true ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, false ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, null ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, void 0 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, [] ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, {} ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset(); // $ExpectError + zlaset( 'row-major' ); // $ExpectError + zlaset( 'row-major', 'all' ); // $ExpectError + zlaset( 'row-major', 'all', 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2 ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A ); // $ExpectError + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2, 3 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a string... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 5, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( true, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( false, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( null, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( void 0, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( [], 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( {}, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( ( x: number ): number => x, 2, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', '5', 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', true, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', false, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', null, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', void 0, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', [], 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', {}, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', ( x: number ): number => x, 2, alpha, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, '5', alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, true, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, false, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, null, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, void 0, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, [], alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, {}, alpha, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, ( x: number ): number => x, alpha, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a complex number... +{ + const A = new Complex128Array( 4 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, '5', beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, 5, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, true, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, false, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, null, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, void 0, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, [], beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, {}, beta, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, ( x: number ): number => x, beta, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a complex number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, alpha, '5', A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, 5, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, true, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, false, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, null, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, void 0, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, [], A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, {}, A, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, ( x: number ): number => x, A, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Complex128Array... +{ + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, alpha, beta, '5', 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, 5, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, true, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, false, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, null, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, void 0, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, [], 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, {}, 2, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, ( x: number ): number => x, 2, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, '5', 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, true, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, false, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, null, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, void 0, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, [], 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, {}, 1, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, '5', 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, true, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, false, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, null, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, void 0, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, [], 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, {}, 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a number... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, '5' ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, true ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, false ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, null ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, void 0 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, [] ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, {} ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const A = new Complex128Array( 4 ); + const alpha = new Complex128( 1.0, 2.0 ); + const beta = new Complex128( 3.0, 4.0 ); + + zlaset.ndarray(); // $ExpectError + zlaset.ndarray( 'all' ); // $ExpectError + zlaset.ndarray( 'all', 2 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1 ); // $ExpectError + zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 0, 3 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/examples/index.js b/lib/node_modules/@stdlib/lapack/base/zlaset/examples/index.js new file mode 100644 index 000000000000..44e451212a05 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var zlaset = require( './../lib' ); + +var shape = [ 5, 8 ]; +var order = 'row-major'; +var strides = shape2strides( shape, order ); + +var N = numel( shape ); + +var A = new Complex128Array( N ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); + +var alpha = new Complex128( 1.0, 2.0 ); +var beta = new Complex128( 3.0, 4.0 ); + +zlaset( order, 'all', shape[ 0 ], shape[ 1 ], alpha, beta, A, strides[ 0 ] ); +console.log( ndarray2array( A, shape, strides, 0, order ) ); diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/base.js b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/base.js new file mode 100644 index 000000000000..ab3937650535 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/base.js @@ -0,0 +1,630 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); +var min = require( '@stdlib/math/base/special/fast/min' ); + + +// FUNCTIONS // + +/** +* Sets the diagonal of a double-precision complex floating-point matrix `A` to a specified value. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float64Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float64Array} `A` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* setDiagonal( 2, 3, 1.0, 2.0, A, 6, 2, 0 ); +* // A => [ 1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 0.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* setDiagonal( 2, 2, 1.0, 2.0, A, 4, 2, 0 ); +* // A => [ 1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* setDiagonal( 3, 2, 1.0, 2.0, A, 4, 2, 0 ); +* // A => [ 1.0, 2.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ] +*/ +function setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ) { + var sa; + var ia; + var i; + + sa = strideA1 + strideA2; + ia = offsetA; + for ( i = 0; i < min( M, N ); i++ ) { + A[ ia ] = breal; + A[ ia+1 ] = bimag; + ia += sa; + } + return A; +} + +/** +* Sets all elements of a double-precision complex floating-point matrix `A` to specified values. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} areal - real component of the value to assign to off-diagonal elements +* @param {number} aimag - imaginary component of the value to assign to off-diagonal elements +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float64Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float64Array} `A` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, 2, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, -2, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, 2, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, -2, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, 4, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, 4, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, -4, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setAll( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, -4, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 ] +*/ +function setAll( M, N, areal, aimag, breal, bimag, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len + var da0; + var da1; + var sh; + var S0; + var S1; + var sa; + var ia; + var i0; + var i1; + var o; + + // Resolve the loop interchange order: + o = loopOrder( [ M, N ], [ strideA1, strideA2 ] ); + sh = o.sh; + sa = o.sx; + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + da0 = sa[ 0 ]; + da1 = sa[ 1 ] - ( S0*sa[0] ); + + // Set the pointer to the first indexed element: + ia = offsetA; + + // Fill the array with a scalar value... + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + A[ ia ] = areal; + A[ ia+1 ] = aimag; + ia += da0; + } + ia += da1; + } + // Replace the diagonal: + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + + return A; +} + +/** +* Sets the upper triangular/trapezoidal part of a double-precision complex floating-point matrix `A` to specified values. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} areal - real component of the value to assign to off-diagonal elements +* @param {number} aimag - imaginary component of the value to assign to off-diagonal elements +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float64Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float64Array} `A` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, 2, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, -2, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, 2, 4 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, -2, 6 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, 4, 0 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, 4, 2 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, -4, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setUpper( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, -4, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +*/ +function setUpper( M, N, areal, aimag, breal, bimag, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len + var idx; + var ia; + var i0; + var i1; + + ia = offsetA; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + idx = ia + ( i1*strideA2 ); + for ( i0 = i1; i0 < N; i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA2; + } + ia += strideA1; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; + } + for ( i1 = 0; i1 < N; i1++ ) { + idx = ia; + for ( i0 = 0; i0 <= min( i1, M-1 ); i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA1; + } + ia += strideA2; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; +} + +/** +* Sets the lower triangular/trapezoidal part of a double-precision complex floating-point matrix `A` to specified values. +* +* @private +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {number} areal - real component of the value to assign to off-diagonal elements +* @param {number} aimag - imaginary component of the value to assign to off-diagonal elements +* @param {number} breal - real component of the value to assign to diagonal elements +* @param {number} bimag - imaginary component of the value to assign to diagonal elements +* @param {Float64Array} A - input matrix view +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Float64Array} `A` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, 2, 0 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 4, -2, 2 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, 2, 4 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -4, -2, 6 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, 4, 0 ); +* // A => [ 3.0, 4.0, 1.0, 2.0, 0.0, 0.0, 3.0, 4.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, 4, 2 ); +* // A => [ 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 0.0, 0.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, 2, -4, 4 ); +* // A => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var A = new Float64Array( 8 ); +* // returns [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] +* +* setLower( 2, 2, 1.0, 2.0, 3.0, 4.0, A, -2, -4, 6 ); +* // A => [ 3.0, 4.0, 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] +*/ +function setLower( M, N, areal, aimag, breal, bimag, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len + var idx; + var ia; + var i0; + var i1; + + ia = offsetA; + if ( isRowMajor( [ strideA1, strideA2 ] ) ) { + for ( i1 = 0; i1 < M; i1++ ) { + idx = ia; + for ( i0 = 0; i0 <= min( i1, N-1 ); i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA2; + } + ia += strideA1; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; + } + for ( i1 = 0; i1 < N; i1++ ) { + idx = ia + ( i1*strideA1 ); + for ( i0 = i1; i0 < M; i0++ ) { + A[ idx ] = areal; + A[ idx+1 ] = aimag; + idx += strideA1; + } + ia += strideA2; + } + setDiagonal( M, N, breal, bimag, A, strideA1, strideA2, offsetA ); + return A; +} + + +// MAIN // + +/** +* Sets elements of matrix `A` to specified values. +* +* @private +* @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex128} alpha - value assigned to off-diagonal elements +* @param {Complex128} beta - value assigned to diagonal elements +* @param {Complex128Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Complex128Array} `A` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'all', 2, 2, alpha, beta, A, 2, 1, 0 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'upper', 2, 2, alpha, beta, A, 2, 1, 0 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 0.0 +* +* im = imag( z ); +* // returns 0.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'lower', 2, 2, alpha, beta, A, 2, 1, 0 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = real( z ); +* // returns 0.0 +* +* im = imag( z ); +* // returns 0.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +*/ +function zlaset( uplo, M, N, alpha, beta, A, strideA1, strideA2, offsetA ) { + var viewA; + var ar; + var ai; + var br; + var bi; + + // Reinterpret the input array as a real-valued array of interleaved real and imaginary components: + viewA = reinterpret( A, 0 ); + + // Adjust the strides and offset accordingly: + strideA1 *= 2; + strideA2 *= 2; + + offsetA *= 2; + + // Decompose the scalars to real and imaginary components: + ar = real( alpha ); + ai = imag( alpha ); + br = real( beta ); + bi = imag( beta ); + + if ( uplo === 'upper' ) { + setUpper( M, N, ar, ai, br, bi, viewA, strideA1, strideA2, offsetA ); + } else if ( uplo === 'lower' ) { + setLower( M, N, ar, ai, br, bi, viewA, strideA1, strideA2, offsetA ); + } else { + setAll( M, N, ar, ai, br, bi, viewA, strideA1, strideA2, offsetA ); + } + return A; +} + + +// EXPORTS // + +module.exports = zlaset; diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/index.js b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/index.js new file mode 100644 index 000000000000..1321adf90b15 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/index.js @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK routine to set the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. +* +* @module @stdlib/lapack/base/zlaset +* +* @example +* var Complex128Array = require( '@stdlib/array/float64' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zlaset = require( '@stdlib/lapack/base/zlaset' ); +* +* var A = new Complex128Array( 4 ); +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ) +* // returns 4.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/float64' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zlaset = require( '@stdlib/lapack/base/zlaset' ); +* +* var A = new Complex128Array( 5 ); +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset.ndarray( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zlaset; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zlaset = main; +} else { + zlaset = tmp; +} + + +// EXPORTS // + +module.exports = zlaset; + +// exports: { "ndarray": "zlaset.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/main.js b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/main.js new file mode 100644 index 000000000000..75aecdd63b25 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zlaset = require( './zlaset.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zlaset, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zlaset; diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js new file mode 100644 index 000000000000..49a6ffe1360a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js @@ -0,0 +1,167 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var base = require( './base.js' ); + + +// MAIN // + +/** +* Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. +* +* @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex128} alpha - value assigned to off-diagonal elements +* @param {Complex128} beta - value assigned to diagonal elements +* @param {Complex128Array} A - input matrix +* @param {integer} strideA1 - stride of the first dimension of `A` +* @param {integer} strideA2 - stride of the second dimension of `A` +* @param {NonNegativeInteger} offsetA - starting index for `A` +* @returns {Complex128Array} `A` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 5 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'all', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* z = A.get( 3 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 5 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'upper', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* z = A.get( 3 ); +* // returns +* +* re = real( z ); +* // returns 0.0 +* +* im = imag( z ); +* // returns 0.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var A = new Complex128Array( 5 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'lower', 2, 2, alpha, beta, A, 2, 1, 1 ); +* +* var z = A.get( 1 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 0.0 +* +* im = imag( z ); +* // returns 0.0 +* +* z = A.get( 3 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +*/ +function zlaset( uplo, M, N, alpha, beta, A, strideA1, strideA2, offsetA ) { + return base( uplo, M, N, alpha, beta, A, strideA1, strideA2, offsetA ); +} + + +// EXPORTS // + +module.exports = zlaset; diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/zlaset.js b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/zlaset.js new file mode 100644 index 000000000000..d2a89594e7ab --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/zlaset.js @@ -0,0 +1,187 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); +var format = require( '@stdlib/string/format' ); +var base = require( './base.js' ); + + +// MAIN // + +/** +* Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. +* +* @param {string} order - storage layout of `A` +* @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` +* @param {NonNegativeInteger} M - number of rows in matrix `A` +* @param {NonNegativeInteger} N - number of columns in matrix `A` +* @param {Complex128} alpha - value assigned to off-diagonal elements +* @param {Complex128} beta - value assigned to diagonal elements +* @param {Complex128Array} A - input matrix +* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) +* @throws {TypeError} first argument must be a valid order +* @throws {RangeError} eighth argument must be greater than or equal to `N` +* @returns {Complex128Array} `A` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'row-major', 'upper', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 0.0 +* +* im = imag( z ); +* // returns 0.0 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var A = new Complex128Array( 4 ); +* +* var alpha = new Complex128( 1.0, 2.0 ); +* var beta = new Complex128( 3.0, 4.0 ); +* +* zlaset( 'row-major', 'lower', 2, 2, alpha, beta, A, 2 ); +* +* var z = A.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns 3.0 +* +* var im = imag( z ); +* // returns 4.0 +* +* z = A.get( 1 ); +* // returns +* +* re = real( z ); +* // returns 0.0 +* +* im = imag( z ); +* // returns 0.0 +* +* z = A.get( 2 ); +* // returns +* +* re = real( z ); +* // returns 1.0 +* +* im = imag( z ); +* // returns 2.0 +*/ +function zlaset( order, uplo, M, N, alpha, beta, A, LDA ) { + var sa1; + var sa2; + if ( !isLayout( order ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); + } + if ( order === 'column-major' ) { + sa1 = 1; + sa2 = LDA; + } else { // order === 'row-major' + if ( LDA < N ) { + throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.', N, LDA ) ); + } + sa1 = LDA; + sa2 = 1; + } + return base( uplo, M, N, alpha, beta, A, sa1, sa2, 0 ); +} + + +// EXPORTS // + +module.exports = zlaset; diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/package.json b/lib/node_modules/@stdlib/lapack/base/zlaset/package.json new file mode 100644 index 000000000000..632bda7f1d59 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/lapack/base/zlaset", + "version": "0.0.0", + "description": "Set the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "zlaset", + "copy", + "linear", + "algebra", + "subroutines", + "array", + "ndarray", + "matrix", + "float64", + "double", + "float64array", + "complex", + "cmplx", + "complex128array" + ] +} diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.js b/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.js new file mode 100644 index 000000000000..b0dd34a7cda6 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zlaset = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlaset, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zlaset.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zlaset = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zlaset, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zlaset; + var main; + + main = require( './../lib/zlaset.js' ); + + zlaset = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zlaset, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.ndarray.js new file mode 100644 index 000000000000..fbeb69a4ffd1 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.ndarray.js @@ -0,0 +1,466 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zlaset = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlaset, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 9', function test( t ) { + t.strictEqual( zlaset.length, 9, 'returns expected value' ); + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var M; + var N; + var A; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + M = 2; + N = 3; + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'all', 2, 3, alpha, beta, A, 3, 1, 1 ); + + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'all', 2, 3, alpha, beta, A, -3, -1, 6 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'all', 3, 2, alpha, beta, A, 2, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, upper)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var M; + var N; + var A; + + M = 3; + N = 2; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + A = new Complex128Array( ( M * N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'upper', 2, 3, alpha, beta, A, 3, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'upper', 2, 3, alpha, beta, A, 3, -1, 3 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'upper', 3, 2, alpha, beta, A, 2, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, lower)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'lower', 2, 3, alpha, beta, A, 3, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'lower', 2, 3, alpha, beta, A, -3, 1, 4 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'lower', 3, 2, alpha, beta, A, 2, 1, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'all', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'all', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'all', 3, 2, alpha, beta, A, 1, 3, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, upper)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'upper', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'upper', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'upper', 3, 2, alpha, beta, A, 1, 3, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 2; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'lower', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'lower', 2, 3, alpha, beta, A, 1, 2, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + A = new Complex128Array( ( M*N ) + 1 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 0.0, 0.0, + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'lower', 3, 2, alpha, beta, A, 1, 3, 1 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower, complex access patterns)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline, no-multi-spaces */ + + A = new Complex128Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + + expected = new Complex128Array([ + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, + 999, 999, 3, 4, 999, 999, 1, 2, 999, 999, 1, 2, + 999, 999, 1, 2, 999, 999, 3, 4, 999, 999, 1, 2, + 999, 999, 1, 2, 999, 999, 1, 2, 999, 999, 3, 4, + 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999, 999 + ]); + + /* eslint-enable array-element-newline, no-multi-spaces */ + + out = zlaset( 'all', 3, 3, alpha, beta, A, 2, 6, 7 ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.zlaset.js b/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.zlaset.js new file mode 100644 index 000000000000..bdf5290295fd --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/test/test.zlaset.js @@ -0,0 +1,489 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zlaset = require( './../lib/zlaset.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zlaset, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( zlaset.length, 8, 'returns expected value' ); + t.end(); +}); + +tape( 'the function throws an error if provided an invalid first argument', function test( t ) { + var values; + var alpha; + var beta; + var A; + var i; + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + + A = new Complex128Array( 4 ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zlaset( value, 'all', 2, 2, alpha, beta, A, 2 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid eighth argument (row-major)', function test( t ) { + var values; + var alpha; + var beta; + var A; + var i; + + values = [ + 0, + 1 + ]; + + A = new Complex128Array( 4 ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + zlaset( 'row-major', 'all', 2, 2, alpha, beta, A, value ); + }; + } +}); + +tape( 'the function assigns values to matrix `A` (row-major, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'row-major', 'all', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'row-major', 'all', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, upper, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'row-major', 'upper', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, upper, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'row-major', 'upper', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, lower, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'row-major', 'lower', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (row-major, lower, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'row-major', 'lower', M, N, alpha, beta, A, N ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'column-major', 'all', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'column-major', 'all', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, upper, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, + 1.0, 2.0, 1.0, 2.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'column-major', 'upper', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, upper, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 3.0, 4.0, 0.0, 0.0, 0.0, 0.0, + 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'column-major', 'upper', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower, wide)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 3; + N = 4; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, + 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'column-major', 'lower', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function assigns values to matrix `A` (column-major, lower, tall)', function test( t ) { + var expected; + var alpha; + var beta; + var out; + var A; + var M; + var N; + + M = 4; + N = 3; + + A = new Complex128Array( M*N ); + alpha = new Complex128( 1.0, 2.0 ); + beta = new Complex128( 3.0, 4.0 ); + + /* eslint-disable array-element-newline */ + expected = new Complex128Array([ + 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 3.0, 4.0, 1.0, 2.0, 1.0, 2.0, + 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 1.0, 2.0 + ]); + + /* eslint-enable array-element-newline */ + + out = zlaset( 'column-major', 'lower', M, N, alpha, beta, A, M ); + t.strictEqual( out, A, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/README.md b/lib/node_modules/@stdlib/lapack/base/zrot/README.md new file mode 100644 index 000000000000..78f3d49b0e14 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/README.md @@ -0,0 +1,299 @@ + + +# zrot + +> Apply a plane rotation with real cosine and complex sine to a pair of double-precision complex floating-point vectors. + +
+ +## Usage + +```javascript +var zrot = require( '@stdlib/lapack/base/zrot' ); +``` + +#### zrot( N, zx, strideX, zy, strideY, c, s ) + +Applies a plane rotation with real cosine and complex sine. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex128( 0.0, 0.75 ); + +zrot( zx.length, zx, 1, zy, 1, 1.25, s ); + +var z = zy.get( 0 ); +// returns + +var re = real( z ); +// returns ~-1.5 + +var im = imag( z ); +// returns ~0.75 + +z = zx.get( 0 ); +// returns + +re = real( z ); +// returns ~1.25 + +im = imag( z ); +// returns ~2.5 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **zx**: first input [`Complex128Array`][@stdlib/array/complex128]. +- **strideX**: index increment for `zx`. +- **zy**: second input [`Complex128Array`][@stdlib/array/complex128]. +- **strideY**: index increment for `zy`. + +The `N` and stride parameters determine how values from `zx` and `zy` are accessed at runtime. For example, to apply a plane rotation to every other element, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex128( 0.0, 0.75 ); + +zrot( 2, zx, 2, zy, 2, 1.25, s ); + +var z = zy.get( 0 ); +// returns + +var re = real( z ); +// returns ~-1.5 + +var im = imag( z ); +// returns ~0.75 + +z = zx.get( 0 ); +// returns + +re = real( z ); +// returns ~1.25 + +im = imag( z ); +// returns ~2.5 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +// Initial arrays... +var zx0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var zy0 = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var zx1 = new Complex128Array( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var zy1 = new Complex128Array( zy0.buffer, zy0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +var s = new Complex128( 0.0, 0.75 ); + +zrot( 2, zx1, -2, zy1, 1, 1.25, s ); + +var z = zy0.get( 2 ); +// returns + +var re = real( z ); +// returns ~-6 + +var im = imag( z ); +// returns ~5.25 + +z = zx0.get( 3 ); +// returns + +re = real( z ); +// returns ~8.75 + +im = imag( z ); +// returns ~10 +``` + +#### zrot.ndarray( N, zx, strideX, offsetX, zy, strideY, offsetY, c, s ) + +Applies a plane rotation with real cosine and complex sine using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex128( 0.0, 0.75 ); + +zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 1.25, s ); + +var z = zy.get( 0 ); +// returns + +var re = real( z ); +// returns ~-1.5 + +var im = imag( z ); +// returns ~0.75 + +z = zx.get( 0 ); +// returns + +re = real( z ); +// returns ~1.25 + +im = imag( z ); +// returns ~2.5 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `zx`. +- **offsetY**: starting index for `zy`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to apply a plane rotation to every other element starting from the second element, + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + +var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var s = new Complex128( 0.0, 0.75 ); + +zrot.ndarray( 2, zx, 2, 1, zy, 2, 1, 1.25, s ); + +var z = zy.get( 3 ); +// returns + +var re = real( z ); +// returns ~-6.0 + +var im = imag( z ); +// returns ~5.25 + +z = zx.get( 1 ); +// returns + +re = real( z ); +// returns ~3.75 + +im = imag( z ); +// returns ~5.0 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions leave `zx` and `zy` unchanged. +- `zrot()` corresponds to the [LAPACK][lapack] routine [`zrot`][zrot]. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zcopy = require( '@stdlib/blas/base/zcopy' ); +var zeros = require( '@stdlib/array/zeros' ); +var logEach = require( '@stdlib/console/log-each' ); +var zrot = require( '@stdlib/lapack/base/zrot' ); + +function rand() { + return new Complex128( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +// Generate random input arrays: +var zx = filledarrayBy( 10, 'complex128', rand ); +var zxc = zcopy( zx.length, zx, 1, zeros( zx.length, 'complex128' ), 1 ); + +var zy = filledarrayBy( 10, 'complex128', rand ); +var zyc = zcopy( zy.length, zy, 1, zeros( zy.length, 'complex128' ), 1 ); + +var s = new Complex128( 0.0, 0.75 ); + +// Apply a plane rotation: +zrot( zx.length, zx, 1, zy, 1, 1.25, s ); + +// Print the results: +logEach( '(%s,%s) => (%s,%s)', zxc, zyc, zx, zy ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[lapack]: http://www.netlib.org/lapack + +[zrot]: https://netlib.org/lapack/explore-html/d1/d45/group__rot_gaac9d54e7408105ad6f4c810902e75b7a.html#gaac9d54e7408105ad6f4c810902e75b7a + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +
+ + diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/benchmark/benchmark.js b/lib/node_modules/@stdlib/lapack/base/zrot/benchmark/benchmark.js new file mode 100644 index 000000000000..0bac7ae7b0f2 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var pkg = require( './../package.json' ).name; +var zrot = require( './../lib/zrot.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var zx; + var zy; + var s; + + zx = new Complex128Array( uniform( len*2, -100.0, 100.0, options ) ); + zy = new Complex128Array( uniform( len*2, -100.0, 100.0, options ) ); + s = new Complex128( 0.6, 0.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var viewX; + var i; + + viewX = reinterpret( zx, 0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zrot( zx.length, zx, 1, zy, 1, 0.8, s ); + if ( isnan( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zrot/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..1e55a28db4cc --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/benchmark/benchmark.ndarray.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var pkg = require( './../package.json' ).name; +var zrot = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var zx; + var zy; + var s; + + zx = new Complex128Array( uniform( len*2, -100.0, 100.0, options ) ); + zy = new Complex128Array( uniform( len*2, -100.0, 100.0, options ) ); + s = new Complex128( 0.6, 0.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var viewX; + var i; + + viewX = reinterpret( zx, 0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zrot( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s ); + if ( isnan( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( viewX[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':ndarray:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/docs/repl.txt b/lib/node_modules/@stdlib/lapack/base/zrot/docs/repl.txt new file mode 100644 index 000000000000..e4c4ec8d333f --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/docs/repl.txt @@ -0,0 +1,172 @@ + +{{alias}}( N, zx, strideX, zy, strideY, c, s ) + Applies a plane rotation with real cosine and complex sine. + + The `N` and stride parameters determine how values in the strided arrays are + accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N` is less than or equal to `0`, the vectors are unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + zx: Complex128Array + First input array. + + strideX: integer + Index increment for `zx`. + + zy: Complex128Array + Second input array. + + strideY: integer + Index increment for `zy`. + + c: number + Cosine of the angle of rotation. + + s: Complex128 + Sine of the angle of rotation. + + Returns + ------- + zy: Complex128Array + Input array `zy`. + + Examples + -------- + // Standard usage: + > var zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var zy = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float64/ctor}}( 0.3, 0.4 ); + > {{alias}}( zx.length, zx, 1, zy, 1, 0.8, s ); + > var z = zy.get( 0 ); + > var re = {{alias:@stdlib/complex/float64/real}}( z ) + ~-1.1 + > var im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~-0.2 + > z = zx.get( 0 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~0.8 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~1.6 + + // Advanced indexing: + > zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + > zy = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float64/ctor}}( 0.3, 0.4 ); + > {{alias}}( 2, zx, -2, zy, 1, 0.8, s ); + > z = zy.get( 0 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~-3.9 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~0.2 + > z = zx.get( 2 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~4.0 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~4.8 + + // Using typed array views: + > var zx0 = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var zy0 = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var zx1 = new {{alias:@stdlib/array/complex128}}( zx0.buffer, zx0.BYTES_PER_ELEMENT*1 ); + > var zy1 = new {{alias:@stdlib/array/complex128}}( zy0.buffer, zy0.BYTES_PER_ELEMENT*2 ); + > var s = new {{alias:@stdlib/complex/float64/ctor}}( 0.3, 0.4 ); + > {{alias}}( 1, zx1, 1, zy1, 1, 0.8, s ); + > z = zy0.get( 2 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~-2.5 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~0.0 + > z = zx0.get( 1 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~2.4 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~3.2 + + +{{alias}}.ndarray( N, zx, strideX, offsetX, zy, strideY, offsetY, c, s ) + Applies a plane rotation with real cosine and complex sine using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + zx: Complex128Array + First input array. + + strideX: integer + Index increment for `zx`. + + offsetX: integer + Starting index for `zx`. + + zy: Complex128Array + Second input array. + + strideY: integer + Index increment for `zy`. + + offsetY: integer + Starting index for `zy`. + + c: number + Cosine of the angle of rotation. + + s: Complex128 + Sine of the angle of rotation. + + Returns + ------- + zy: Complex128Array + Input array `zy`. + + Examples + -------- + // Standard usage: + > var zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var zy = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float64/ctor}}( 0.3, 0.4 ); + > {{alias}}.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s ); + > var z = zy.get( 0 ); + > var re = {{alias:@stdlib/complex/float64/real}}( z ) + ~-1.1 + > var im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~-0.2 + > z = zx.get( 0 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~0.8 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~1.6 + + // Advanced indexing: + > zx = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > zy = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var s = new {{alias:@stdlib/complex/float64/ctor}}( 0.3, 0.4 ); + > {{alias}}.ndarray( 1, zx, 2, 1, zy, 2, 1, 0.8, s ); + > z = zy.get( 1 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~-2.5 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~0.0 + > z = zx.get( 1 ); + > re = {{alias:@stdlib/complex/float64/real}}( z ) + ~2.4 + > im = {{alias:@stdlib/complex/float64/imag}}( z ) + ~3.2 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/docs/types/index.d.ts b/lib/node_modules/@stdlib/lapack/base/zrot/docs/types/index.d.ts new file mode 100644 index 000000000000..3e8b67a2c342 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/docs/types/index.d.ts @@ -0,0 +1,198 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; +import { Complex128 } from '@stdlib/types/complex'; + +/** +* Interface describing `zrot`. +*/ +interface Routine { + /** + * Applies a plane rotation with real cosine and complex sine. + * + * @param N - number of indexed elements + * @param zx - first input array + * @param strideX - `zx` stride length + * @param zy - second input array + * @param strideY - `zy` stride length + * @param c - cosine of the angle of rotation + * @param s - sine of the angle of rotation + * @returns `zy` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * var s = new Complex128( 0.3, 0.4 ); + * + * zrot( zx.length, zx, 1, zy, 1, 0.8, s ); + * + * var z = zy.get( 0 ); + * // returns + * + * var re = real( z ); + * // returns ~-1.1 + * + * var im = imag( z ); + * // returns ~-0.2 + * + * z = zx.get( 0 ); + * // returns + * + * re = real( z ); + * // returns ~0.8 + * + * im = imag( z ); + * // returns ~1.6 + */ + ( N: number, zx: Complex128Array, strideX: number, zy: Complex128Array, strideY: number, c: number, s: Complex128 ): Complex128Array; + + /** + * Applies a plane rotation with real cosine and complex sine using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param zx - first input array + * @param strideX - `zx` stride length + * @param offsetX - starting index for `zx` + * @param zy - second input array + * @param strideY - `zy` stride length + * @param offsetY - starting index for `zy` + * @param c - cosine of the angle of rotation + * @param s - sine of the angle of rotation + * @returns `zy` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64' ); + * var real = require( '@stdlib/complex/float64/real' ); + * var imag = require( '@stdlib/complex/float64/imag' ); + * + * var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * var s = new Complex128( 0.3, 0.4 ); + * + * zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s ); + * + * var z = zy.get( 0 ); + * // returns + * + * var re = real( z ); + * // returns ~-1.1 + * + * var im = imag( z ); + * // returns ~-0.2 + * + * z = zx.get( 0 ); + * // returns + * + * re = real( z ); + * // returns ~0.8 + * + * im = imag( z ); + * // returns ~1.6 + */ + ndarray( N: number, zx: Complex128Array, strideX: number, offsetX: number, zy: Complex128Array, strideY: number, offsetY: number, c: number, s: Complex128 ): Complex128Array; +} + +/** +* Applies a plane rotation with real cosine and complex sine. +* +* @param N - number of indexed elements +* @param zx - first input array +* @param strideX - `zx` stride length +* @param zy - second input array +* @param strideY - `zy` stride length +* @param c - cosine of the angle of rotation +* @param s - sine of the angle of rotation +* @returns `zy` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex128( 0.3, 0.4 ); +* +* zrot( 2, zx, 2, zy, 1, 0.8, s ); +* +* var z = zy.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns ~-1.1 +* +* var im = imag( z ); +* // returns ~-0.2 +* +* z = zx.get( 0 ); +* // returns +* +* re = real( z ); +* // returns ~0.8 +* +* im = imag( z ); +* // returns ~1.6 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex128( 0.3, 0.4 ); +* +* zrot.ndarray( 2, zx, 2, 0, zy, 1, 0, 0.8, s ); +* +* var z = zy.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns ~-1.1 +* +* var im = imag( z ); +* // returns ~-0.2 +* +* z = zx.get( 0 ); +* // returns +* +* re = real( z ); +* // returns ~0.8 +* +* im = imag( z ); +* // returns ~1.6 +*/ +declare var zrot: Routine; + + +// EXPORTS // + +export = zrot; diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/docs/types/test.ts b/lib/node_modules/@stdlib/lapack/base/zrot/docs/types/test.ts new file mode 100644 index 000000000000..9233650e4bad --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/docs/types/test.ts @@ -0,0 +1,333 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import zrot = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( zx.length, zx, 1, zy, 1, 0.8, s ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( '10', zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( true, zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( false, zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( null, zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( undefined, zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( [], zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( {}, zx, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( ( zx: number ): number => zx, zx, 1, zy, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( zx.length, 10, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, '10', 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, true, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, false, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, null, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, undefined, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, [ '1' ], 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, {}, 1, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, ( zx: number ): number => zx, 1, zy, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( zx.length, zx, '10', zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, true, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, false, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, null, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, undefined, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, [], zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, {}, zy, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, ( zx: number ): number => zx, zy, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( zx.length, zx, 1, 10, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, '10', 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, true, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, false, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, null, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, undefined, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, [ '1' ], 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, {}, 1, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, ( zx: number ): number => zx, 1, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( zx.length, zx, 1, zy, '10', 0.8, 0.6 ); // $ExpectError + zrot( zx.length, zx, 1, zy, true, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, false, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, null, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, undefined, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, [], 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, {}, 0.8, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, ( zx: number ): number => zx, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot( zx.length, zx, 1, zy, 1, '10', s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, true, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, false, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, null, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, undefined, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, [], s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, {}, s ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, ( zx: number ): number => zx, s ); // $ExpectError +} + +// The compiler throws an error if the function is provided a seventh argument which is not a complex number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + + zrot( zx.length, zx, 1, zy, 1, 0.8, 0.6 ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, '10' ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, true ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, false ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, null ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, undefined ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, [] ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, {} ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, ( zx: number ): number => zx ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot(); // $ExpectError + zrot( zx.length ); // $ExpectError + zrot( zx.length, zx ); // $ExpectError + zrot( zx.length, zx, 1 ); // $ExpectError + zrot( zx.length, zx, 1, zy ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8 ); // $ExpectError + zrot( zx.length, zx, 1, zy, 1, 0.8, s, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( '10', zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( true, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( false, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( null, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( undefined, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( [], zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( {}, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( ( zx: number ): number => zx, zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, 10, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, '10', 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, true, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, false, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, null, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, undefined, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, [ '1' ], 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, {}, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, ( zx: number ): number => zx, 1, 0, zy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, '10', 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, true, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, false, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, null, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, undefined, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, [], 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, {}, 0, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, ( zx: number ): number => zx, 0, zy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, 1, '10', zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, true, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, false, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, null, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, undefined, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, [], zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, {}, zy, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, ( zx: number ): number => zx, zy, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Complex128Array... +{ + const zx = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, 1, 0, 10, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, '10', 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, true, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, false, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, null, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, undefined, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, [ '1' ], 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, {}, 1, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, ( zx: number ): number => zx, 1, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, 1, 0, zy, '10', 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, true, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, false, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, null, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, undefined, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, [], 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, {}, 0, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, ( zx: number ): number => zx, 0, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, '10', 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, true, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, false, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, null, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, undefined, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, [], 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, {}, 0.8, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, ( zx: number ): number => zx, 0.8, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, '10', s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, true, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, false, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, null, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, undefined, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, [], s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, {}, s ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, ( zx: number ): number => zx, s ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a ninth argument which is not a complex number... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, 0.6 ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, '10' ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, true ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, false ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, null ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, undefined ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, [] ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, {} ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, ( zx: number ): number => zx ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const zx = new Complex128Array( 10 ); + const zy = new Complex128Array( 10 ); + const s = new Complex128( 0.3, 0.4 ); + + zrot.ndarray(); // $ExpectError + zrot.ndarray( zx.length ); // $ExpectError + zrot.ndarray( zx.length, zx ); // $ExpectError + zrot.ndarray( zx.length, zx, 1 ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0 ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1 ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0 ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8 ); // $ExpectError + zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/examples/index.js b/lib/node_modules/@stdlib/lapack/base/zrot/examples/index.js new file mode 100644 index 000000000000..6919a098b7eb --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/examples/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var zcopy = require( '@stdlib/blas/base/zcopy' ); +var zeros = require( '@stdlib/array/zeros' ); +var logEach = require( '@stdlib/console/log-each' ); +var zrot = require( './../lib' ); + +function rand() { + return new Complex128( discreteUniform( 0, 10 ), discreteUniform( -5, 5 ) ); +} + +// Generate random input arrays: +var zx = filledarrayBy( 10, 'complex128', rand ); +var zxc = zcopy( zx.length, zx, 1, zeros( zx.length, 'complex128' ), 1 ); + +var zy = filledarrayBy( 10, 'complex128', rand ); +var zyc = zcopy( zy.length, zy, 1, zeros( zy.length, 'complex128' ), 1 ); + +var s = new Complex128( 0.0, 0.75 ); + +// Apply a plane rotation: +zrot( zx.length, zx, 1, zy, 1, 1.25, s ); + +// Print the results: +logEach( '(%s,%s) => (%s,%s)', zxc, zyc, zx, zy ); diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/lib/index.js b/lib/node_modules/@stdlib/lapack/base/zrot/lib/index.js new file mode 100644 index 000000000000..f24890134508 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/lib/index.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* LAPACK auxiliary routine to apply a plane rotation with real cosine and complex sine. +* +* @module @stdlib/lapack/base/zrot +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zrot = require( '@stdlib/lapack/base/zrot' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex128( 0.6, 0 ); +* +* zrot( zx.length, zx, 1, zy, 1, 0.8, s ); +* +* var z = zy.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns ~-0.6 +* +* var im = imag( z ); +* // returns ~-1.2 +* +* z = zx.get( 0 ); +* // returns +* +* re = real( z ); +* // returns ~0.8 +* +* im = imag( z ); +* // returns ~1.6 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* var zrot = require( '@stdlib/lapack/base/zrot' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex128( 0.6, 0 ); +* +* zrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s ); +* +* var z = zy.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns ~-0.6 +* +* var im = imag( z ); +* // returns ~-1.2 +* +* z = zx.get( 0 ); +* // returns +* +* re = real( z ); +* // returns ~0.8 +* +* im = imag( z ); +* // returns ~1.6 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zrot; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zrot = main; +} else { + zrot = tmp; +} + + +// EXPORTS // + +module.exports = zrot; + +// exports: { "ndarray": "zrot.ndarray" } diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/lib/main.js b/lib/node_modules/@stdlib/lapack/base/zrot/lib/main.js new file mode 100644 index 000000000000..3a6c265d46a3 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zrot = require( './zrot.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zrot, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zrot; diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js new file mode 100644 index 000000000000..d6361de71951 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js @@ -0,0 +1,127 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); + + +// MAIN // + +/** +* Applies a plane rotation with real cosine and complex sine. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} zx - first input array +* @param {integer} strideX - `zx` stride length +* @param {NonNegativeInteger} offsetX - starting `zx` index +* @param {Complex128Array} zy - second input array +* @param {integer} strideY - `zy` stride length +* @param {NonNegativeInteger} offsetY - starting `zy` index +* @param {number} c - cosine of the angle of rotation +* @param {Complex128} s - sine of the angle of rotation +* @returns {Complex128Array} `zy` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex128( 0.3, 0.4 ); +* +* zrot( zx.length, zx, 1, 0, zy, 1, 0, 0.8, s ); +* +* var z = zy.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns ~-1.1 +* +* var im = imag( z ); +* // returns ~-0.2 +* +* z = zx.get( 0 ); +* // returns +* +* re = real( z ); +* // returns ~0.8 +* +* im = imag( z ); +* // returns ~1.6 +*/ +function zrot( N, zx, strideX, offsetX, zy, strideY, offsetY, c, s ) { + var viewX; + var viewY; + var sr; + var si; + var sx; + var sy; + var ix; + var iy; + var yr; + var yi; + var xr; + var xi; + var i; + + if ( N <= 0 ) { + return zy; + } + viewX = reinterpret( zx, 0 ); + viewY = reinterpret( zy, 0 ); + + ix = offsetX * 2; + iy = offsetY * 2; + + sx = strideX * 2; + sy = strideY * 2; + + sr = real( s ); + si = imag( s ); + + for ( i = 0; i < N; i++ ) { + yr = viewY[ iy ]; + yi = viewY[ iy+1 ]; + xr = viewX[ ix ]; + xi = viewX[ ix+1 ]; + + // Compute tmp = c * zx[ ix ] + s * zy[ iy ] + viewX[ ix ] = ( c*xr ) + ( ( sr*yr ) - ( si*yi ) ); + viewX[ ix+1 ] = ( c*xi ) + ( ( sr*yi ) + ( si*yr ) ); + + // Compute zy[ iy ] = c * zy[ iy ] - conj(s) * zx[ ix ] + viewY[ iy ] = ( c*yr ) - ( ( sr*xr ) + ( si*xi ) ); + viewY[ iy+1 ] = ( c*yi ) - ( ( sr*xi ) - ( si*xr ) ); + + ix += sx; + iy += sy; + } + return zy; +} + + +// EXPORTS // + +module.exports = zrot; diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/lib/zrot.js b/lib/node_modules/@stdlib/lapack/base/zrot/lib/zrot.js new file mode 100644 index 000000000000..ebaec7db55df --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/lib/zrot.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Applies a plane rotation with real cosine and complex sine. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} zx - first input array +* @param {integer} strideX - `zx` stride length +* @param {Complex128Array} zy - second input array +* @param {integer} strideY - `zy` stride length +* @param {number} c - cosine of the angle of rotation +* @param {Complex128} s - sine of the angle of rotation +* @returns {Complex128Array} `zy` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var real = require( '@stdlib/complex/float64/real' ); +* var imag = require( '@stdlib/complex/float64/imag' ); +* +* var zx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var zy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var s = new Complex128( 0.3, 0.4 ); +* +* zrot( zx.length, zx, 1, zy, 1, 0.8, s ); +* +* var z = zy.get( 0 ); +* // returns +* +* var re = real( z ); +* // returns ~-1.1 +* +* var im = imag( z ); +* // returns ~-0.2 +* +* z = zx.get( 0 ); +* // returns +* +* re = real( z ); +* // returns ~0.8 +* +* im = imag( z ); +* // returns ~1.6 +*/ +function zrot( N, zx, strideX, zy, strideY, c, s ) { + var ix = stride2offset( N, strideX ); + var iy = stride2offset( N, strideY ); + return ndarray( N, zx, strideX, ix, zy, strideY, iy, c, s ); +} + + +// EXPORTS // + +module.exports = zrot; diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/package.json b/lib/node_modules/@stdlib/lapack/base/zrot/package.json new file mode 100644 index 000000000000..214784a4f948 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/lapack/base/zrot", + "version": "0.0.0", + "description": "LAPACK auxiliary routine to apply a plane rotation with real cosine and complex sine.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "lapack", + "blas", + "linear", + "algebra", + "subroutines", + "zrot", + "rotation", + "vector", + "typed", + "array", + "ndarray", + "complex", + "complex128", + "double", + "float64", + "float64array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/test/test.js b/lib/node_modules/@stdlib/lapack/base/zrot/test/test.js new file mode 100644 index 000000000000..d5a2b3ddef8a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var isBrowser = require( '@stdlib/assert/is-browser' ); +var zrot = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': isBrowser +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zrot, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zrot.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zrot = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zrot, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zrot; + var main; + + main = require( './../lib/zrot.js' ); + + zrot = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zrot, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/zrot/test/test.ndarray.js new file mode 100644 index 000000000000..7a5aadde0630 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/test/test.ndarray.js @@ -0,0 +1,563 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var zrot = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Tests for element-wise approximate equality. +* +* @private +* @param {Object} t - test object +* @param {Collection} actual - actual values +* @param {Collection} expected - expected values +* @param {number} rtol - relative tolerance +*/ +function isApprox( t, actual, expected, rtol ) { + var delta; + var tol; + var i; + + t.strictEqual( actual.length, expected.length, 'returns expected value' ); + for ( i = 0; i < expected.length; i++ ) { + if ( actual[ i ] === expected[ i ] ) { + t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' ); + } else { + delta = abs( actual[ i ] - expected[ i ] ); + tol = rtol * EPS * abs( expected[ i ] ); + if ( tol === 0.0 ) { + tol = EPS; // absolute tolerance when `expected[i]` is `0` + } + t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' ); + } + } +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zrot, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 9', function test( t ) { + t.strictEqual( zrot.length, 9, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.6, 0.0 ); + + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 4.0, // 3 + 4.8, // 3 + 5.6, // 4 + 6.4 // 4 + ]); + cye = new Float64Array([ + -0.6, // 1 + -1.2, // 1 + -1.8, // 2 + -2.4, // 2 + -3.0, // 3 + -3.6, // 3 + -4.2, // 4 + -4.8 // 4 + ]); + + out = zrot( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.0, 0.6 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -1.2, // 1 + 0.6, // 1 + -3.6, // 2 + 3.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, 2, 0, cy, 1, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, + 2.0, + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0, // 2 + 7.0, // 3 + 8.0 // 3 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 1.0, + 2.0, + 2.4, // 1 + 3.2, // 1 + 4.0, // 2 + 4.8, // 2 + 5.6, // 3 + 6.4 // 3 + ]); + cye = new Float64Array([ + -2.5, // 1 + 0.0, // 1 + -3.9, // 2 + 0.2, // 2 + -5.3, // 3 + 0.4, // 3 + 0.0, + 0.0 + ]); + + out = zrot( 3, cx, 1, 1, cy, 1, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + -2.5, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, 1, 0, cy, 2, 0, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -3.9, // 2 + 0.2, // 2 + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, 2, 0, cy, -1, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the second array', function test( t ) { + var out; + var cx; + var cy; + var s; + + cx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + s = new Complex128( 0.3, 0.4 ); + + out = zrot( cx.length, cx, 1, 0, cy, 1, 0, 0.8, s ); + + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns both vectors unchanged', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var cx; + var cy; + var s; + + cx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + s = new Complex128( 0.3, 0.4 ); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cye = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + zrot( -1, cx, 1, 0, cy, 1, 0, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + zrot( 0, cx, 1, 0, cy, 1, 0, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 3.0, // 1 + 4.0, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 2 + 1.6, // 2 + 2.4, // 1 + 3.2, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -1.1, // 2 + -0.2, // 2 + 0.0, + 0.0, + -2.5, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, -1, 1, cy, -2, 2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 1.0, + 2.0, + 2.4, // 1 + 3.2, // 1 + 5.0, + 6.0, + 5.6, // 2 + 6.4 // 2 + ]); + cye = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + -2.5, // 1 + 0.0, // 1 + -5.3, // 2 + 0.4 // 2 + ]); + + out = zrot( 2, cx, 2, 1, cy, 1, 2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/test/test.zrot.js b/lib/node_modules/@stdlib/lapack/base/zrot/test/test.zrot.js new file mode 100644 index 000000000000..5e7f1c72e702 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/zrot/test/test.zrot.js @@ -0,0 +1,639 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var zrot = require( './../lib/zrot.js' ); + + +// FUNCTIONS // + +/** +* Tests for element-wise approximate equality. +* +* @private +* @param {Object} t - test object +* @param {Collection} actual - actual values +* @param {Collection} expected - expected values +* @param {number} rtol - relative tolerance +*/ +function isApprox( t, actual, expected, rtol ) { + var delta; + var tol; + var i; + + t.strictEqual( actual.length, expected.length, 'returns expected value' ); + for ( i = 0; i < expected.length; i++ ) { + if ( actual[ i ] === expected[ i ] ) { + t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' ); + } else { + delta = abs( actual[ i ] - expected[ i ] ); + tol = rtol * EPS * abs( expected[ i ] ); + if ( tol === 0.0 ) { + tol = EPS; // absolute tolerance when `expected[i]` is `0` + } + t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' ); + } + } +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zrot, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( zrot.length, 7, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + // Verify in octave with [0.8 0.6; -0.6 0.8] * [1+2i, 3+4i, 5+6i, 7+8i; 0 0 0 0] + + s = new Complex128( 0.6, 0.0 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 4.0, // 3 + 4.8, // 3 + 5.6, // 4 + 6.4 // 4 + ]); + cye = new Float64Array([ + -0.6, // 1 + -1.2, // 1 + -1.8, // 2 + -2.4, // 2 + -3.0, // 3 + -3.6, // 3 + -4.2, // 4 + -4.8 // 4 + ]); + + out = zrot( cx.length, cx, 1, cy, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + // Verify in octave with [1.25 0.75i; .75i 1.25] * [1+2i, 3+4i, 5+6i, 7+8i; 0 0 0 0] + + s = new Complex128( 0.0, 0.75 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 1.25, // 1 + 2.5, // 1 + 3.75, // 2 + 5.0, // 2 + 6.25, // 3 + 7.5, // 3 + 8.75, // 4 + 10.0 // 4 + ]); + cye = new Float64Array([ + -1.5, // 1 + 0.75, // 1 + -3.0, // 2 + 2.25, // 2 + -4.5, // 3 + 3.75, // 3 + -6.0, // 4 + 5.25 // 4 + ]); + + out = zrot( cx.length, cx, 1, cy, 1, 1.25, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function applies a plane rotation', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + // Verify in octave with [1.25 0.3+0.4i; -0.3+0.4i 1.25] * [1+2i, 3+4i, 5+6i, 7+8i; 0 0 0 0] + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, // 3 + 6.0, // 3 + 7.0, // 4 + 8.0 // 4 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0, // 3 + 0.0, // 4 + 0.0 // 4 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 1.25, // 1 + 2.5, // 1 + 3.75, // 2 + 5.0, // 2 + 6.25, // 3 + 7.5, // 3 + 8.75, // 4 + 10.0 // 4 + ]); + cye = new Float64Array([ + -1.1, // 1 + -0.2, // 1 + -2.5, // 2 + 0.0, // 2 + -3.9, // 3 + 0.2, // 3 + -5.3, // 4 + 0.4 // 4 + ]); + + out = zrot( cx.length, cx, 1, cy, 1, 1.25, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -1.1, // 1 + -0.2, // 1 + -3.9, // 2 + 0.2, // 2 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, 2, cy, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, // 2 + 4.0, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 2.4, // 2 + 3.2, // 2 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + -2.5, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, 1, cy, 2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the second array', function test( t ) { + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = zrot( cx.length, cx, 1, cy, 1, 0.8, s ); + + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns both vectors unchanged', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cy = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + cye = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + zrot( -1, cx, 1, cy, 1, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + zrot( 0, cx, 1, cy, 1, 0.8, s ); + t.deepEqual( viewX, cxe, 'returns expected value' ); + t.deepEqual( viewY, cye, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 3.0, // 1 + 4.0, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 2 + 1.6, // 2 + 2.4, // 1 + 3.2, // 1 + 5.0, + 6.0, + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -1.1, // 2 + -0.2, // 2 + 0.0, + 0.0, + -2.5, // 1 + 0.0, // 1 + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, -1, cy, -2, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 2.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var viewX; + var viewY; + var cxe; + var cye; + var out; + var cx; + var cy; + var s; + + s = new Complex128( 0.3, 0.4 ); + cx = new Complex128Array([ + 1.0, // 1 + 2.0, // 1 + 3.0, + 4.0, + 5.0, // 2 + 6.0, // 2 + 7.0, + 8.0 + ]); + cy = new Complex128Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + viewX = new Float64Array( cx.buffer ); + viewY = new Float64Array( cy.buffer ); + + cxe = new Float64Array([ + 0.8, // 1 + 1.6, // 1 + 3.0, + 4.0, + 4.0, // 2 + 4.8, // 2 + 7.0, + 8.0 + ]); + cye = new Float64Array([ + -3.9, // 2 + 0.2, // 2 + -1.1, // 1 + -0.2, // 1 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + out = zrot( 2, cx, 2, cy, -1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var viewX; + var viewY; + var cx0; + var cy0; + var cx1; + var cy1; + var cxe; + var cye; + var out; + var s; + + s = new Complex128( 0.3, 0.4 ); + + // Initial arrays... + cx0 = new Complex128Array([ + 1.0, + 2.0, + 3.0, // 2 + 4.0, // 2 + 5.0, + 6.0, + 7.0, // 1 + 8.0 // 1 + ]); + cy0 = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + // Create offset views... + cx1 = new Complex128Array( cx0.buffer, cx0.BYTES_PER_ELEMENT*1 ); // begin at the 2nd element + cy1 = new Complex128Array( cy0.buffer, cy0.BYTES_PER_ELEMENT*2 ); // begin at the 3rd element + + viewX = new Float64Array( cx0.buffer ); + viewY = new Float64Array( cy0.buffer ); + + cxe = new Float64Array([ + 1.0, + 2.0, + 2.4, // 2 + 3.2, // 2 + 5.0, + 6.0, + 5.6, // 1 + 6.4 // 1 + ]); + cye = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + -5.3, // 1 + 0.4, // 1 + -2.5, // 2 + 0.0 // 2 + ]); + + out = zrot( 2, cx1, -2, cy1, 1, 0.8, s ); + isApprox( t, viewX, cxe, 2.0 ); + isApprox( t, viewY, cye, 4.0 ); + t.strictEqual( out, cy1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js index 5c2a4932dffa..0ea52481252f 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pkg = require( './../package.json' ).name; var isEven = require( './../lib' ); @@ -31,14 +30,17 @@ var isEven = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var x; var y; var i; + len = 100; + x = discreteUniform( len, 0, 1000 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = round( (randu()*1.0e7) - 5.0e6 ); - y = isEven( x ); + y = isEven( x[ i % len ] ); if ( typeof y !== 'boolean' ) { b.fail( 'should return a boolean' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js index da205aada595..b95bed88186f 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,14 +39,17 @@ var opts = { // MAIN // bench( pkg+'::native', opts, function benchmark( b ) { + var len; var x; var y; var i; + len = 100; + x = discreteUniform( len, 0, 1000 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = round( (randu()*1.0e7) - 5.0e6 ); - y = isEven( x ); + y = isEven( x[ i % len ] ); if ( typeof y !== 'boolean' ) { b.fail( 'should return a boolean' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c index 5605d32ba184..7e0075a0d8a8 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c @@ -92,15 +92,18 @@ static double rand_double( void ) { */ static double benchmark( void ) { double elapsed; - double x; + double x[ 100 ]; double t; bool b; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = round( (rand_double()*200.0) - 100.0 ); + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( rand_double() * 200.0 ) - 100.0; - b = stdlib_base_is_even( x ); + b = stdlib_base_is_even( x[ i%100 ] ); if ( b != true && b != false ) { printf( "should return either true or false\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json index 33756e256dcf..accca2c07be0 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json @@ -1,5 +1,7 @@ { - "options": {}, + "options": { + "task": "build" + }, "fields": [ { "field": "src", @@ -24,6 +26,43 @@ ], "confs": [ { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-integer", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/create-int32" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-integer" + ] + }, + { + "task": "examples", "src": [ "./src/main.c" ], diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c index 85642e403244..b496a218e026 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c @@ -17,9 +17,12 @@ */ #include "stdlib/math/base/assert/is_even.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" #include #include -#include /** * Receives JavaScript callback invocation data. @@ -29,60 +32,11 @@ * @return Node-API value */ static napi_value addon( napi_env env, napi_callback_info info ) { - napi_status status; - - // Get callback arguments: - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); - assert( status == napi_ok ); - - // Check whether we were provided the correct number of arguments: - if ( argc < 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); - assert( status == napi_ok ); - return NULL; - } - if ( argc > 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); - assert( status == napi_ok ); - return NULL; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); - assert( status == napi_ok ); - return NULL; - } - - double x; - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - bool result = stdlib_base_is_even( x ); - - napi_value v; - status = napi_create_int32( env, (int32_t)result, &v ); - assert( status == napi_ok ); - - return v; + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_even( x ), out ); + return out; } -/** -* Initializes a Node-API module. -* -* @param env environment under which the function is invoked -* @param exports exports object -* @return main export -*/ -static napi_value init( napi_env env, napi_value exports ) { - napi_value fcn; - napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; -} +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) -NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-finite/include.gypi b/lib/node_modules/@stdlib/math/base/assert/is-finite/include.gypi index ffd7702dc420..de5f9994b817 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-finite/include.gypi +++ b/lib/node_modules/@stdlib/math/base/assert/is-finite/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_finite( x ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) + diff --git a/lib/node_modules/@stdlib/math/base/assert/is-finite/src/addon.cpp b/lib/node_modules/@stdlib/math/base/assert/is-finite/src/addon.cpp deleted file mode 100644 index 76b46f4ad6ea..000000000000 --- a/lib/node_modules/@stdlib/math/base/assert/is-finite/src/addon.cpp +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/assert/is_finite.h" -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_math_base_assert_is_finite { - - /** - * Tests if a double-precision floating-point numeric value is finite. - * - * ## Notes - * - * - When called from JavaScript, the function expects one argument: - * - * - `x`: a number - */ - napi_value node_is_finite( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 1 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide a number." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - - napi_value v; - double x; - if ( vtype0 == napi_number ) { - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - status = napi_create_int32( env, (int32_t)stdlib_base_is_finite( x ), &v ); - assert( status == napi_ok ); - } else { - status = napi_create_int32( env, 0, &v ); - assert( status == napi_ok ); - } - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_is_finite, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_math_base_assert_is_finite diff --git a/lib/node_modules/@stdlib/math/base/assert/is-finite/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-finite/test/test.native.js index d42e1f02d8f0..23d2fe6b7226 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-finite/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-finite/test/test.native.js @@ -74,24 +74,3 @@ tape( 'the function returns `false` if provided `-infinity`', opts, function tes t.equal( isfinite( NINF ), false, 'returns false' ); t.end(); }); - -tape( 'the function returns `false` if not provided a finite number', opts, function test( t ) { - var values; - var i; - - values = [ - '5', - NaN, - true, - null, - void 0, - [], - {}, - function noop() {} - ]; - - for ( i = 0; i < values.length; i++ ) { - t.equal( isfinite( values[i] ), false, 'returns false' ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-finitef/include.gypi b/lib/node_modules/@stdlib/math/base/assert/is-finitef/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-finitef/include.gypi +++ b/lib/node_modules/@stdlib/math/base/assert/is-finitef/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_finitef( x ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) + diff --git a/lib/node_modules/@stdlib/math/base/assert/is-finitef/src/addon.cpp b/lib/node_modules/@stdlib/math/base/assert/is-finitef/src/addon.cpp deleted file mode 100644 index b63d5f0ecb21..000000000000 --- a/lib/node_modules/@stdlib/math/base/assert/is-finitef/src/addon.cpp +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/assert/is_finitef.h" -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_math_base_assert_is_finitef { - - /** - * Tests if a single-precision floating-point numeric value is finite. - * - * ## Notes - * - * - When called from JavaScript, the function expects one argument: - * - * - `x`: a number - */ - napi_value node_is_finitef( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 1 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide a number." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - - napi_value v; - double x; - if ( vtype0 == napi_number ) { - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - status = napi_create_int32( env, (int32_t)stdlib_base_is_finitef( (float)x ), &v ); - assert( status == napi_ok ); - } else { - status = napi_create_int32( env, 0, &v ); - assert( status == napi_ok ); - } - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_is_finitef, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_math_base_assert_is_finitef diff --git a/lib/node_modules/@stdlib/math/base/assert/is-finitef/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-finitef/test/test.native.js index 5f57644d5253..691c1973b714 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-finitef/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-finitef/test/test.native.js @@ -74,24 +74,3 @@ tape( 'the function returns `false` if provided `-infinity`', opts, function tes t.equal( isfinitef( NINF ), false, 'returns false' ); t.end(); }); - -tape( 'the function returns `false` if not provided a finite number', opts, function test( t ) { - var values; - var i; - - values = [ - '5', - NaN, - true, - null, - void 0, - [], - {}, - function noop() {} - ]; - - for ( i = 0; i < values.length; i++ ) { - t.equal( isfinitef( values[i] ), false, 'returns false' ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-infinitef/include.gypi b/lib/node_modules/@stdlib/math/base/assert/is-infinitef/include.gypi index ffd7702dc420..de5f9994b817 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-infinitef/include.gypi +++ b/lib/node_modules/@stdlib/math/base/assert/is-infinitef/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_infinitef( x ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-infinitef/src/addon.cpp b/lib/node_modules/@stdlib/math/base/assert/is-infinitef/src/addon.cpp deleted file mode 100644 index 241aff36eae5..000000000000 --- a/lib/node_modules/@stdlib/math/base/assert/is-infinitef/src/addon.cpp +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/assert/is_infinitef.h" -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_math_base_assert_is_infinitef { - - /** - * Tests if a single-precision floating-point numeric value is infinite. - * - * ## Notes - * - * - When called from JavaScript, the function expects one argument: - * - * - `x`: a number - */ - napi_value node_is_infinitef( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 1 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide a number." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - - napi_value v; - double x; - if ( vtype0 == napi_number ) { - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - status = napi_create_int32( env, (int32_t)stdlib_base_is_infinitef( (float)x ), &v ); - assert( status == napi_ok ); - } else { - status = napi_create_int32( env, 0, &v ); - assert( status == napi_ok ); - } - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_is_infinitef, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_math_base_assert_is_infinitef diff --git a/lib/node_modules/@stdlib/math/base/assert/is-infinitef/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-infinitef/test/test.native.js index 5c910def3616..10956148a015 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-infinitef/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-infinitef/test/test.native.js @@ -52,27 +52,3 @@ tape( 'the function returns `true` if provided `-infinity`', opts, function test t.equal( isInfinitef( NINF ), true, 'returns true' ); t.end(); }); - -tape( 'the function returns `false` if not provided an infinite number', opts, function test( t ) { - var values; - var i; - - values = [ - '5', - 5.0, - -1.0e38, - 4.0e-38, - NaN, - true, - null, - void 0, - [], - {}, - function noop() {} - ]; - - for ( i = 0; i < values.length; i++ ) { - t.equal( isInfinitef( values[i] ), false, 'returns false' ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/c/native/benchmark.c index 8a2243155aee..c92c5e025ba5 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-integer/benchmark/c/native/benchmark.c @@ -92,15 +92,18 @@ static double rand_double( void ) { */ static double benchmark( void ) { double elapsed; - double x; + double x[ 100 ]; double t; bool b; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = ( rand_double() * 1000.0 ) - 500.0; + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( rand_double() * 1000.0 ) - 500.0; - b = stdlib_base_is_integer( x ); + b = stdlib_base_is_integer( x[ i%100 ] ); if ( b != true && b != false ) { printf( "should return either true or false\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integer/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-integer/manifest.json index e13af23df8ce..e921a32c7c2c 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integer/manifest.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-integer/manifest.json @@ -1,5 +1,7 @@ { - "options": {}, + "options": { + "task": "build" + }, "fields": [ { "field": "src", @@ -24,6 +26,43 @@ ], "confs": [ { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/floor", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/create-int32" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/floor" + ] + }, + { + "task": "examples", "src": [ "./src/main.c" ], diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integer/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-integer/src/addon.c index 27a1d2174513..d69edb3c3d39 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integer/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-integer/src/addon.c @@ -17,9 +17,12 @@ */ #include "stdlib/math/base/assert/is_integer.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" #include #include -#include /** * Receives JavaScript callback invocation data. @@ -29,60 +32,10 @@ * @return Node-API value */ static napi_value addon( napi_env env, napi_callback_info info ) { - napi_status status; - - // Get callback arguments: - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); - assert( status == napi_ok ); - - // Check whether we were provided the correct number of arguments: - if ( argc < 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); - assert( status == napi_ok ); - return NULL; - } - if ( argc > 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); - assert( status == napi_ok ); - return NULL; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); - assert( status == napi_ok ); - return NULL; - } - - double x; - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - bool result = stdlib_base_is_integer( x ); - - napi_value v; - status = napi_create_int32( env, (int32_t)result, &v ); - assert( status == napi_ok ); - - return v; -} - -/** -* Initializes a Node-API module. -* -* @param env environment under which the function is invoked -* @param exports exports object -* @return main export -*/ -static napi_value init( napi_env env, napi_value exports ) { - napi_value fcn; - napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_integer( x ), out ); + return out; } -NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/c/native/benchmark.c index c2441a3aa0e8..ef50a010127d 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-integerf/benchmark/c/native/benchmark.c @@ -93,14 +93,17 @@ static float rand_float( void ) { static double benchmark( void ) { double elapsed; double t; - float x; + float x[ 100 ]; bool b; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = ( rand_float() * 1000.0f ) - 500.0f; + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( rand_float() * 1000.0f ) - 500.0f; - b = stdlib_base_is_integerf( x ); + b = stdlib_base_is_integerf( x[ i%100 ] ); if ( b != true && b != false ) { printf( "should return either true or false\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integerf/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-integerf/manifest.json index 565c69f22a08..78b58b903d46 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integerf/manifest.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-integerf/manifest.json @@ -1,5 +1,7 @@ { - "options": {}, + "options": { + "task": "build" + }, "fields": [ { "field": "src", @@ -24,6 +26,43 @@ ], "confs": [ { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/floorf", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-float", + "@stdlib/napi/create-int32" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/floorf" + ] + }, + { + "task": "examples", "src": [ "./src/main.c" ], diff --git a/lib/node_modules/@stdlib/math/base/assert/is-integerf/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-integerf/src/addon.c index a065e0b495a2..cfded10953bc 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-integerf/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-integerf/src/addon.c @@ -17,9 +17,12 @@ */ #include "stdlib/math/base/assert/is_integerf.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" #include #include -#include /** * Receives JavaScript callback invocation data. @@ -29,60 +32,10 @@ * @return Node-API value */ static napi_value addon( napi_env env, napi_callback_info info ) { - napi_status status; - - // Get callback arguments: - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); - assert( status == napi_ok ); - - // Check whether we were provided the correct number of arguments: - if ( argc < 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); - assert( status == napi_ok ); - return NULL; - } - if ( argc > 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); - assert( status == napi_ok ); - return NULL; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); - assert( status == napi_ok ); - return NULL; - } - - double x; - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - bool result = stdlib_base_is_integerf( (float)x ); - - napi_value v; - status = napi_create_int32( env, (int32_t)result, &v ); - assert( status == napi_ok ); - - return v; -} - -/** -* Initializes a Node-API module. -* -* @param env environment under which the function is invoked -* @param exports exports object -* @return main export -*/ -static napi_value init( napi_env env, napi_value exports ) { - napi_value fcn; - napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_integerf( x ), out ); + return out; } -NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-nanf/include.gypi b/lib/node_modules/@stdlib/math/base/assert/is-nanf/include.gypi index ffd7702dc420..de5f9994b817 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-nanf/include.gypi +++ b/lib/node_modules/@stdlib/math/base/assert/is-nanf/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_nanf( x ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-nanf/src/addon.cpp b/lib/node_modules/@stdlib/math/base/assert/is-nanf/src/addon.cpp deleted file mode 100644 index 999433f4ab74..000000000000 --- a/lib/node_modules/@stdlib/math/base/assert/is-nanf/src/addon.cpp +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/assert/is_nanf.h" -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_math_base_assert_is_nanf { - - /** - * Tests if a single-precision floating-point numeric value is `NaN`. - * - * ## Notes - * - * - When called from JavaScript, the function expects one argument: - * - * - `x`: a number - */ - napi_value node_is_nanf( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 1 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide a number." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - - napi_value v; - double x; - if ( vtype0 == napi_number ) { - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - status = napi_create_int32( env, (int32_t)stdlib_base_is_nanf( (float)x ), &v ); - assert( status == napi_ok ); - } else { - status = napi_create_int32( env, 0, &v ); - assert( status == napi_ok ); - } - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_is_nanf, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_math_base_assert_is_nanf diff --git a/lib/node_modules/@stdlib/math/base/assert/is-nanf/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-nanf/test/test.native.js index a25d99596730..1bf16cadd144 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-nanf/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-nanf/test/test.native.js @@ -23,7 +23,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var Number = require( '@stdlib/number/ctor' ); // VARIABLES // @@ -46,26 +45,3 @@ tape( 'the function returns `true` if provided `NaN`', opts, function test( t ) t.equal( isnanf( NaN ), true, 'returns true' ); t.end(); }); - -tape( 'the function returns `false` if not provided `NaN`', opts, function test( t ) { - var values; - var i; - - values = [ - '5', - 5.0, - true, - false, - null, - void 0, - [], - {}, - function noop() {}, - new Number( NaN ) // eslint-disable-line no-new-wrappers - ]; - - for ( i = 0; i < values.length; i++ ) { - t.equal( isnanf( values[i] ), false, 'returns false when provided ' + values[ i ] ); - } - t.end(); -}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/README.md b/lib/node_modules/@stdlib/math/base/assert/is-odd/README.md index ed74decb478c..a1080a7a5030 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/README.md +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/README.md @@ -85,18 +85,14 @@ bool = isOdd( NaN ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isOdd = require( '@stdlib/math/base/assert/is-odd' ); -var bool; -var x; -var i; +var x = discreteUniform( 100, 0, 1000 ); -for ( i = 0; i < 100; i++ ) { - x = round( randu()*100.0 ); - bool = isOdd( x ); - console.log( '%d is %s', x, ( bool ) ? 'odd' : 'not odd' ); +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( '%d is %s', x[ i ], ( isOdd( x[ i ] ) ) ? 'odd' : 'not odd' ); } ``` diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.js index c72cd6cd8821..9cff6819f9c2 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.js @@ -21,8 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pkg = require( './../package.json' ).name; var isOdd = require( './../lib' ); @@ -31,14 +30,17 @@ var isOdd = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var x; var y; var i; + len = 100; + x = discreteUniform( len, 5.0e6, -5.0e6 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = round( (randu()*1.0e7) - 5.0e6 ); - y = isOdd( x ); + y = isOdd( x[ i % len ] ); if ( typeof y !== 'boolean' ) { b.fail( 'should return a boolean' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.native.js index 7ac46f6d952c..e9cc5ac85dac 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/benchmark.native.js @@ -22,8 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,14 +39,17 @@ var opts = { // MAIN // bench( pkg+'::native', opts, function benchmark( b ) { + var len; var x; var y; var i; + len = 100; + x = discreteUniform( len, 5.0e6, -5.0e6 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = round( (randu()*1.0e7) - 5.0e6 ); - y = isOdd( x ); + y = isOdd( x[ i % len ] ); if ( typeof y !== 'boolean' ) { b.fail( 'should return a boolean' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/c/native/benchmark.c index d3769a09cc19..d22a64120151 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/benchmark/c/native/benchmark.c @@ -92,15 +92,18 @@ static double rand_double( void ) { */ static double benchmark( void ) { double elapsed; - double x; + double x[ 100 ]; double t; bool b; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = round( (rand_double()*200.0) - 100.0 ); + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( rand_double() * 200.0 ) - 100.0; - b = stdlib_base_is_odd( x ); + b = stdlib_base_is_odd( x[ i % 100 ] ); if ( b != true && b != false ) { printf( "should return either true or false\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/examples/index.js b/lib/node_modules/@stdlib/math/base/assert/is-odd/examples/index.js index 3b012ed376fc..ce3ea2aee78d 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/examples/index.js @@ -18,16 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var isOdd = require( './../lib' ); -var bool; -var x; -var i; +var x = discreteUniform( 100, 0, 1000 ); -for ( i = 0; i < 100; i++ ) { - x = round( randu()*100.0 ); - bool = isOdd( x ); - console.log( '%d is %s', x, ( bool ) ? 'odd' : 'not odd' ); +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( '%d is %s', x[ i ], ( isOdd( x[ i ] ) ) ? 'odd' : 'not odd' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-odd/manifest.json index 1df892ba4163..f70657b50ed3 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/manifest.json @@ -1,5 +1,7 @@ { - "options": {}, + "options": { + "task": "build" + }, "fields": [ { "field": "src", @@ -24,6 +26,43 @@ ], "confs": [ { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-even", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/create-int32" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-even" + ] + }, + { + "task": "examples", "src": [ "./src/main.c" ], diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-odd/src/addon.c index d6411f8f69ae..4873e3dec7f9 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/src/addon.c @@ -17,9 +17,12 @@ */ #include "stdlib/math/base/assert/is_odd.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" #include #include -#include /** * Receives JavaScript callback invocation data. @@ -29,60 +32,10 @@ * @return Node-API value */ static napi_value addon( napi_env env, napi_callback_info info ) { - napi_status status; - - // Get callback arguments: - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); - assert( status == napi_ok ); - - // Check whether we were provided the correct number of arguments: - if ( argc < 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); - assert( status == napi_ok ); - return NULL; - } - if ( argc > 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); - assert( status == napi_ok ); - return NULL; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); - assert( status == napi_ok ); - return NULL; - } - - double x; - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - bool result = stdlib_base_is_odd( x ); - - napi_value v; - status = napi_create_int32( env, (int32_t)result, &v ); - assert( status == napi_ok ); - - return v; -} - -/** -* Initializes a Node-API module. -* -* @param env environment under which the function is invoked -* @param exports exports object -* @return main export -*/ -static napi_value init( napi_env env, napi_value exports ) { - napi_value fcn; - napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_odd( x ), out ); + return out; } -NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.js b/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.js index 6e7ef4c43068..92d1e0c7798d 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.js @@ -44,7 +44,7 @@ tape( 'the function returns `false` if provided an even number', function test( x = round( randu()*1.0e6 ) - 5.0e5; x *= 2; // always even bool = isOdd( x ); - t.equal( bool, false, 'returns false when provided '+x ); + t.equal( bool, false, 'returns expected value when provided '+x ); } t.end(); }); @@ -59,29 +59,29 @@ tape( 'the function returns `true` if provided an odd number', function test( t x += 1; } bool = isOdd( x ); - t.equal( bool, true, 'returns true when provided '+x ); + t.equal( bool, true, 'returns expected value when provided '+x ); } t.end(); }); tape( 'the function returns `false` if provided `+-0`', function test( t ) { - t.equal( isOdd( +0.0 ), false, 'returns false' ); - t.equal( isOdd( -0.0 ), false, 'returns false' ); + t.equal( isOdd( +0.0 ), false, 'returns expected value' ); + t.equal( isOdd( -0.0 ), false, 'returns expected value' ); t.end(); }); tape( 'WARNING: the function returns `true` if provided `+infinity`', function test( t ) { - t.equal( isOdd( PINF ), true, 'returns true' ); + t.equal( isOdd( PINF ), true, 'returns expected value' ); t.end(); }); tape( 'WARNING: the function returns `true` if provided `-infinity`', function test( t ) { - t.equal( isOdd( NINF ), true, 'returns true' ); + t.equal( isOdd( NINF ), true, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `NaN`', function test( t ) { - t.equal( isOdd( NaN ), false, 'returns false' ); - t.equal( isOdd( 0.0/0.0 ), false, 'returns false' ); + t.equal( isOdd( NaN ), false, 'returns expected value' ); + t.equal( isOdd( 0.0/0.0 ), false, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.native.js index 969908c36320..ccd195cf2a4e 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-odd/test/test.native.js @@ -53,7 +53,7 @@ tape( 'the function returns `false` if provided an even number', opts, function x = round( randu()*1.0e6 ) - 5.0e5; x *= 2; // always even bool = isOdd( x ); - t.equal( bool, false, 'returns false when provided '+x ); + t.equal( bool, false, 'returns expected value when provided '+x ); } t.end(); }); @@ -68,29 +68,29 @@ tape( 'the function returns `true` if provided an odd number', opts, function te x += 1; } bool = isOdd( x ); - t.equal( bool, true, 'returns true when provided '+x ); + t.equal( bool, true, 'returns expected value when provided '+x ); } t.end(); }); tape( 'the function returns `false` if provided `+-0`', opts, function test( t ) { - t.equal( isOdd( +0.0 ), false, 'returns false' ); - t.equal( isOdd( -0.0 ), false, 'returns false' ); + t.equal( isOdd( +0.0 ), false, 'returns expected value' ); + t.equal( isOdd( -0.0 ), false, 'returns expected value' ); t.end(); }); tape( 'WARNING: the function returns `true` if provided `+infinity`', opts, function test( t ) { - t.equal( isOdd( PINF ), true, 'returns true' ); + t.equal( isOdd( PINF ), true, 'returns expected value' ); t.end(); }); tape( 'WARNING: the function returns `true` if provided `-infinity`', opts, function test( t ) { - t.equal( isOdd( NINF ), true, 'returns true' ); + t.equal( isOdd( NINF ), true, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `NaN`', opts, function test( t ) { - t.equal( isOdd( NaN ), false, 'returns false' ); - t.equal( isOdd( 0.0/0.0 ), false, 'returns false' ); + t.equal( isOdd( NaN ), false, 'returns expected value' ); + t.equal( isOdd( 0.0/0.0 ), false, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-prime/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-prime/manifest.json index d4c3183b9dd3..efa59860bb5e 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-prime/manifest.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-prime/manifest.json @@ -39,7 +39,11 @@ "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/floor", "@stdlib/constants/float64/max-safe-integer", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/create-int32" ] }, { diff --git a/lib/node_modules/@stdlib/math/base/assert/is-prime/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-prime/src/addon.c index 1f1ba57715e0..69a3abfafdbe 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-prime/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-prime/src/addon.c @@ -17,10 +17,12 @@ */ #include "stdlib/math/base/assert/is_prime.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" #include #include -#include -#include /** * Receives JavaScript callback invocation data. @@ -30,60 +32,11 @@ * @return Node-API value */ static napi_value addon( napi_env env, napi_callback_info info ) { - napi_status status; - - // Get callback arguments: - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); - assert( status == napi_ok ); - - // Check whether we were provided the correct number of arguments: - if ( argc < 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); - assert( status == napi_ok ); - return NULL; - } - if ( argc > 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); - assert( status == napi_ok ); - return NULL; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); - assert( status == napi_ok ); - return NULL; - } - - double x; - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - bool result = stdlib_base_is_prime( x ); - - napi_value v; - status = napi_create_int32( env, (int32_t)result, &v ); - assert( status == napi_ok ); - - return v; + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_prime( x ), out ); + return out; } -/** -* Initializes a Node-API module. -* -* @param env environment under which the function is invoked -* @param exports exports object -* @return main export -*/ -static napi_value init( napi_env env, napi_value exports ) { - napi_value fcn; - napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; -} +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) -NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.js b/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.js index bda7e7894812..cfdb16533ca8 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.js @@ -49,14 +49,14 @@ tape( 'the function returns `true` if provided a prime number', function test( t M = 2e4; for ( i = 0; i < M; i++ ) { v = PRIMES[ i ]; - t.equal( isPrime( v ), true, 'returns true when provided '+v ); + t.equal( isPrime( v ), true, 'returns expected value when provided '+v ); } // Randomly test prime numbers chosen from the remainder of the list of known prime numbers... N = PRIMES.length - 1; for ( i = 0; i < 1e3; i++ ) { j = discreteUniform( M, N ); v = PRIMES[ j ]; - t.equal( isPrime( v ), true, 'returns true when provided '+v ); + t.equal( isPrime( v ), true, 'returns expected value when provided '+v ); } t.end(); }); @@ -72,7 +72,7 @@ tape( 'the function returns `false` if provided a composite number', function te N = PRIMES.length; hash = {}; for ( i = 0; i < N; i++ ) { - hash[ PRIMES[i] ] = true; + hash[ PRIMES[ i ] ] = true; } // Only test odd integers, as even integers are trivially composite... M = 2e5; @@ -80,14 +80,14 @@ tape( 'the function returns `false` if provided a composite number', function te if ( hash[ i ] ) { continue; } - t.equal( isPrime( i ), false, 'returns false when provided '+i ); + t.equal( isPrime( i ), false, 'returns expected value when provided '+i ); } // Generate random composite integers... MAX = PRIMES[ N-1 ]; for ( i = 0; i < 1e3; i++ ) { // Generate an odd integer... - j = discreteUniform( trunc( M/2 ), trunc( MAX/2 ) ); - j = (2*j) + 1; + j = discreteUniform( trunc( M / 2 ), trunc( MAX / 2 ) ); + j = ( 2 * j ) + 1; // Check if the generated integer is a known prime number... if ( hash[ j ] ) { @@ -95,7 +95,7 @@ tape( 'the function returns `false` if provided a composite number', function te i -= 1; continue; } - t.equal( isPrime( j ), false, 'returns false when provided '+j ); + t.equal( isPrime( j ), false, 'returns expected value when provided '+j ); } t.end(); }); @@ -104,9 +104,9 @@ tape( 'the function returns `false` if not provided a positive integer', functio var v; var i; for ( i = 0; i < 100; i++ ) { - v = ( randu()*100.0 ) - 50.0; + v = ( randu() * 100.0 ) - 50.0; if ( trunc(v) !== v ) { - t.equal( isPrime( v ), false, 'returns false when provided '+v ); + t.equal( isPrime( v ), false, 'returns expected value when provided '+v ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.native.js index 07ac725e76c7..62f1bb118eef 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-prime/test/test.native.js @@ -58,14 +58,14 @@ tape( 'the function returns `true` if provided a prime number', opts, function t M = 2e4; for ( i = 0; i < M; i++ ) { v = PRIMES[ i ]; - t.equal( isPrime( v ), true, 'returns true when provided '+v ); + t.equal( isPrime( v ), true, 'returns expected value when provided '+v ); } // Randomly test prime numbers chosen from the remainder of the list of known prime numbers... N = PRIMES.length - 1; for ( i = 0; i < 1e3; i++ ) { j = discreteUniform( M, N ); v = PRIMES[ j ]; - t.equal( isPrime( v ), true, 'returns true when provided '+v ); + t.equal( isPrime( v ), true, 'returns expected value when provided '+v ); } t.end(); }); @@ -81,7 +81,7 @@ tape( 'the function returns `false` if provided a composite number', opts, funct N = PRIMES.length; hash = {}; for ( i = 0; i < N; i++ ) { - hash[ PRIMES[i] ] = true; + hash[ PRIMES[ i ] ] = true; } // Only test odd integers, as even integers are trivially composite... M = 2e5; @@ -89,14 +89,14 @@ tape( 'the function returns `false` if provided a composite number', opts, funct if ( hash[ i ] ) { continue; } - t.equal( isPrime( i ), false, 'returns false when provided '+i ); + t.equal( isPrime( i ), false, 'returns expected value when provided '+i ); } // Generate random composite integers... MAX = PRIMES[ N-1 ]; for ( i = 0; i < 1e3; i++ ) { // Generate an odd integer... - j = discreteUniform( trunc( M/2 ), trunc( MAX/2 ) ); - j = (2*j) + 1; + j = discreteUniform( trunc( M / 2 ), trunc( MAX / 2 ) ); + j = ( 2 * j ) + 1; // Check if the generated integer is a known prime number... if ( hash[ j ] ) { @@ -104,7 +104,7 @@ tape( 'the function returns `false` if provided a composite number', opts, funct i -= 1; continue; } - t.equal( isPrime( j ), false, 'returns false when provided '+j ); + t.equal( isPrime( j ), false, 'returns expected value when provided '+j ); } t.end(); }); @@ -113,9 +113,9 @@ tape( 'the function returns `false` if not provided a positive integer', opts, f var v; var i; for ( i = 0; i < 100; i++ ) { - v = ( randu()*100.0 ) - 50.0; + v = ( randu() * 100.0 ) - 50.0; if ( trunc(v) !== v ) { - t.equal( isPrime( v ), false, 'returns false when provided '+v ); + t.equal( isPrime( v ), false, 'returns expected value when provided '+v ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/README.md b/lib/node_modules/@stdlib/math/base/assert/is-probability/README.md index d909224a03e6..9124f6d37dd2 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/README.md +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/README.md @@ -56,17 +56,14 @@ bool = isProbability( NaN ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isProbability = require( '@stdlib/math/base/assert/is-probability' ); -var bool; -var x; -var i; +var x = uniform( 100, -1.0, 1.0 ); -for ( i = 0; i < 100; i++ ) { - x = ( randu()*2.0 ) - 1.0; - bool = isProbability( x ); - console.log( '%d is %s', x, ( bool ) ? 'a probability' : 'not a probability' ); +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( '%d is %s', x[ i ], ( isProbability( x[ i ] ) ) ? 'a probability' : 'not a probability' ); } ``` @@ -105,6 +102,8 @@ for ( i = 0; i < 100; i++ ) { Tests if a double-precision floating-point number is a probability. ```c +#include + bool out = stdlib_base_is_probability( 0.5 ); // returns true diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.js index eba9ad9aca6e..d8aa7b920c5f 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pkg = require( './../package.json' ).name; var isProbability = require( './../lib' ); @@ -30,14 +30,17 @@ var isProbability = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var x; var y; var i; + len = 100; + x = uniform( len, 1.0, -1.0 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) - 0.0; - y = isProbability( x ); + y = isProbability( x[ i % len ] ); if ( typeof y !== 'boolean' ) { b.fail( 'should return a boolean' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.native.js index 04cef48026c3..f839abf3e90f 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -39,14 +39,17 @@ var opts = { // MAIN // bench( pkg+'::native', opts, function benchmark( b ) { + var len; var x; var y; var i; + len = 100; + x = uniform( len, -1.0, 1.0 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) - 0.0; - y = isProbability( x ); + y = isProbability( x[ i % len ] ); if ( typeof y !== 'boolean' ) { b.fail( 'should return a boolean' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/c/native/benchmark.c index 05b22e77a77b..0fd4ee800ee2 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/benchmark/c/native/benchmark.c @@ -92,15 +92,18 @@ static double rand_double( void ) { */ static double benchmark( void ) { double elapsed; - double x; + double x[ 100 ]; double t; bool b; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = ( rand_double() * 2.0 ) - 1.0;; + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( rand_double() * 2.0 ) - 0.0; - b = stdlib_base_is_probability( x ); + b = stdlib_base_is_probability( x[ i % 100 ] ); if ( b != true && b != false ) { printf( "should return either true or false\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/examples/index.js b/lib/node_modules/@stdlib/math/base/assert/is-probability/examples/index.js index 4b2fc5c08395..72bb6ef34a21 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/examples/index.js @@ -18,15 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isProbability = require( './../lib' ); -var bool; -var x; -var i; +var x = uniform( 100, -1.0, 1.0 ); -for ( i = 0; i < 100; i++ ) { - x = ( randu()*2.0 ) - 1.0; - bool = isProbability( x ); - console.log( '%d is %s', x, ( bool ) ? 'a probability' : 'not a probability' ); +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( '%d is %s', x[ i ], ( isProbability( x[ i ] ) ) ? 'a probability' : 'not a probability' ); } diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-probability/manifest.json index 04e61e361caa..9d74cf717f8c 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/manifest.json +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/manifest.json @@ -1,5 +1,7 @@ { - "options": {}, + "options": { + "task": "build" + }, "fields": [ { "field": "src", @@ -24,6 +26,36 @@ ], "confs": [ { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/create-int32", + "@stdlib/napi/export" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [] + }, + { + "task": "examples", "src": [ "./src/main.c" ], diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-probability/src/addon.c index 230719980644..c60b755fd9a9 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/src/addon.c +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/src/addon.c @@ -17,9 +17,12 @@ */ #include "stdlib/math/base/assert/is_probability.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" #include #include -#include /** * Receives JavaScript callback invocation data. @@ -29,60 +32,10 @@ * @return Node-API value */ static napi_value addon( napi_env env, napi_callback_info info ) { - napi_status status; - - // Get callback arguments: - size_t argc = 1; - napi_value argv[ 1 ]; - status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); - assert( status == napi_ok ); - - // Check whether we were provided the correct number of arguments: - if ( argc < 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); - assert( status == napi_ok ); - return NULL; - } - if ( argc > 1 ) { - status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); - assert( status == napi_ok ); - return NULL; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); - assert( status == napi_ok ); - return NULL; - } - - double x; - status = napi_get_value_double( env, argv[ 0 ], &x ); - assert( status == napi_ok ); - - bool result = stdlib_base_is_probability( x ); - - napi_value v; - status = napi_create_int32( env, (int32_t)result, &v ); - assert( status == napi_ok ); - - return v; -} - -/** -* Initializes a Node-API module. -* -* @param env environment under which the function is invoked -* @param exports exports object -* @return main export -*/ -static napi_value init( napi_env env, napi_value exports ) { - napi_value fcn; - napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_probability( x ), out ); + return out; } -NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.js b/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.js index 3e8a7e51d869..7a5ef76b57e0 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.js @@ -40,9 +40,9 @@ tape( 'the function returns `false` if provided a number less than `0.0`', funct var x; var i; for ( i = 0; i < 1000; i++ ) { - x = -1.0 - ( randu()*1000.0 ); + x = -1.0 - ( randu() * 1000.0 ); bool = isProbability( x ); - t.equal( bool, false, 'returns false when provided '+x ); + t.equal( bool, false, 'returns expected value when provided '+x ); } t.end(); }); @@ -52,9 +52,9 @@ tape( 'the function returns `false` if provided a number greater than `1.0`', fu var x; var i; for ( i = 0; i < 1000; i++ ) { - x = ( randu()*1000.0 ) + 2.0; + x = ( randu() * 1000.0 ) + 2.0; bool = isProbability( x ); - t.equal( bool, false, 'returns false when provided '+x ); + t.equal( bool, false, 'returns expected value when provided '+x ); } t.end(); }); @@ -66,34 +66,34 @@ tape( 'the function returns `true` if provided a probability', function test( t for ( i = 0; i < 1000; i++ ) { x = randu(); bool = isProbability( x ); - t.equal( bool, true, 'returns true when provided '+x ); + t.equal( bool, true, 'returns expected value when provided '+x ); } t.end(); }); tape( 'the function returns `true` if provided `+-0`', function test( t ) { - t.equal( isProbability( 0.0 ), true, 'returns true' ); - t.equal( isProbability( -0.0 ), true, 'returns true' ); + t.equal( isProbability( 0.0 ), true, 'returns expected value' ); + t.equal( isProbability( -0.0 ), true, 'returns expected value' ); t.end(); }); tape( 'the function returns `true` if provided `1`', function test( t ) { - t.equal( isProbability( 1.0 ), true, 'returns true' ); + t.equal( isProbability( 1.0 ), true, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `+infinity`', function test( t ) { - t.equal( isProbability( PINF ), false, 'returns false' ); + t.equal( isProbability( PINF ), false, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `-infinity`', function test( t ) { - t.equal( isProbability( NINF ), false, 'returns false' ); + t.equal( isProbability( NINF ), false, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `NaN`', function test( t ) { - t.equal( isProbability( NaN ), false, 'returns false' ); - t.equal( isProbability( 0.0/0.0 ), false, 'returns false' ); + t.equal( isProbability( NaN ), false, 'returns expected value' ); + t.equal( isProbability( 0.0 / 0.0 ), false, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.native.js index a8d18fbcd613..a8022bf23cb3 100644 --- a/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/assert/is-probability/test/test.native.js @@ -49,9 +49,9 @@ tape( 'the function returns `false` if provided a number less than `0.0`', opts, var x; var i; for ( i = 0; i < 1000; i++ ) { - x = -1.0 - ( randu()*1000.0 ); + x = -1.0 - ( randu() * 1000.0 ); bool = isProbability( x ); - t.equal( bool, false, 'returns false when provided '+x ); + t.equal( bool, false, 'returns expected value when provided '+x ); } t.end(); }); @@ -61,9 +61,9 @@ tape( 'the function returns `false` if provided a number greater than `1.0`', op var x; var i; for ( i = 0; i < 1000; i++ ) { - x = ( randu()*1000.0 ) + 2.0; + x = ( randu() * 1000.0 ) + 2.0; bool = isProbability( x ); - t.equal( bool, false, 'returns false when provided '+x ); + t.equal( bool, false, 'returns expected value when provided '+x ); } t.end(); }); @@ -75,34 +75,34 @@ tape( 'the function returns `true` if provided a probability', opts, function te for ( i = 0; i < 1000; i++ ) { x = randu(); bool = isProbability( x ); - t.equal( bool, true, 'returns true when provided '+x ); + t.equal( bool, true, 'returns expected value when provided '+x ); } t.end(); }); tape( 'the function returns `true` if provided `+-0`', opts, function test( t ) { - t.equal( isProbability( 0.0 ), true, 'returns true' ); - t.equal( isProbability( -0.0 ), true, 'returns true' ); + t.equal( isProbability( 0.0 ), true, 'returns expected value' ); + t.equal( isProbability( -0.0 ), true, 'returns expected value' ); t.end(); }); tape( 'the function returns `true` if provided `1`', opts, function test( t ) { - t.equal( isProbability( 1.0 ), true, 'returns true' ); + t.equal( isProbability( 1.0 ), true, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `+infinity`', opts, function test( t ) { - t.equal( isProbability( PINF ), false, 'returns false' ); + t.equal( isProbability( PINF ), false, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `-infinity`', opts, function test( t ) { - t.equal( isProbability( NINF ), false, 'returns false' ); + t.equal( isProbability( NINF ), false, 'returns expected value' ); t.end(); }); tape( 'the function returns `false` if provided `NaN`', opts, function test( t ) { - t.equal( isProbability( NaN ), false, 'returns false' ); - t.equal( isProbability( 0.0/0.0 ), false, 'returns false' ); + t.equal( isProbability( NaN ), false, 'returns expected value' ); + t.equal( isProbability( 0.0 / 0.0 ), false, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/README.md b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/README.md new file mode 100644 index 000000000000..880a4446ed9a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/README.md @@ -0,0 +1,183 @@ + + +# isProbabilityf + +> Test if a single-precision floating-point number is a probability. + +
+ +## Usage + +```javascript +var isProbabilityf = require( '@stdlib/math/base/assert/is-probabilityf' ); +``` + +#### isProbabilityf( x ) + +Tests if a single-precision floating-point number is a probability. + +```javascript +var bool = isProbabilityf( 0.5 ); +// returns true + +bool = isProbabilityf( 3.14 ); +// returns false + +bool = isProbabilityf( NaN ); +// returns false +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var isProbabilityf = require( '@stdlib/math/base/assert/is-probabilityf' ); + +var x = uniform( 100, -1.0, 1.0, { + 'dtype': 'float32' +}); + +var i; +for ( i = 0; i < 100; i++ ) { + console.log( '%d is %s', x[ i ], ( isProbabilityf( x[ i ] ) ) ? 'a probability' : 'not a probability' ); +} +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/assert/is_probabilityf.h" +``` + +#### stdlib_base_is_probabilityf( x ) + +Tests if a single-precision floating-point number is a probability. + +```c +#include + +bool out = stdlib_base_is_probabilityf( 0.5f ); +// returns true + +out = stdlib_base_is_probabilityf( 3.14f ); +// returns false +``` + +The function accepts the following arguments: + +- **x**: `[in] float` input value. + +```c +bool stdlib_base_is_probabilityf( const float x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/math/base/assert/is_probabilityf.h" +#include +#include +#include + +int main( void ) { + float x; + bool v; + int i; + + for ( i = 0; i < 100; i++ ) { + x = ( ( (float)rand() / (float)RAND_MAX ) * 2.0f ) - 1.0f; + v = stdlib_base_is_probabilityf( x ); + printf( "%f is %sa probability\n", x, ( v ) ? "" : "not " ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/benchmark.js new file mode 100644 index 000000000000..24c4d5306918 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var isProbabilityf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var opts; + var len; + var x; + var y; + var i; + + len = 100; + opts = { + 'dtype': 'float32' + }; + x = uniform( len, -1.0, 1.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = isProbabilityf( x[ i % len ] ); + if ( typeof y !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( y ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..626c38263586 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var isProbabilityf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( isProbabilityf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var opts; + var len; + var x; + var y; + var i; + + len = 100; + opts = { + 'dtype': 'float32' + }; + x = uniform( len, -1.0, 1.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = isProbabilityf( x[ i % len ] ); + if ( typeof y !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( y ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/c/native/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..29bf784e9e60 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/benchmark/c/native/benchmark.c @@ -0,0 +1,137 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/assert/is_probabilityf.h" +#include +#include +#include +#include +#include +#include + +#define NAME "is-probabilityf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + float x[ 100 ]; + double t; + bool b; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = ( rand_float() * 2.0f ) - 0.0f; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + b = stdlib_base_is_probabilityf( x[ i % 100 ] ); + if ( b != true && b != false ) { + printf( "should return either true or false\n" ); + break; + } + } + elapsed = tic() - t; + if ( b != true && b != false ) { + printf( "should return either true or false\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/binding.gyp b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/repl.txt b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/repl.txt new file mode 100644 index 000000000000..c6bd13674f69 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( x ) + Tests if a single-precision floating-point number value is a probability. + + A probability is defined as a number on the closed interval [0,1]. + + Parameters + ---------- + x: number + Value to test. + + Returns + ------- + bool: boolean + Boolean indicating whether the value is a probability. + + Examples + -------- + > var bool = {{alias}}( 0.5 ) + true + > bool = {{alias}}( 3.14 ) + false + > bool = {{alias}}( NaN ) + false + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/types/index.d.ts new file mode 100644 index 000000000000..87a8f3aaa773 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/types/index.d.ts @@ -0,0 +1,48 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Tests if a single-precision floating-point number is a probability. +* +* ## Notes +* +* - A probability is defined as a number on the closed interval `[0,1]`. +* +* @param x - value to test +* @returns boolean indicating whether the value is a probability +* +* @example +* var bool = isProbabilityf( 0.5 ); +* // returns true +* +* @example +* var bool = isProbabilityf( 3.14 ); +* // returns false +* +* @example +* var bool = isProbabilityf( NaN ); +* // returns false +*/ +declare function isProbabilityf( x: number ): boolean; + + +// EXPORTS // + +export = isProbabilityf; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/types/test.ts new file mode 100644 index 000000000000..d7ed9fe74b51 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/docs/types/test.ts @@ -0,0 +1,46 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isProbabilityf = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isProbabilityf( 0.3 ); // $ExpectType boolean + isProbabilityf( 2 ); // $ExpectType boolean + isProbabilityf( 3.12 ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + isProbabilityf( true ); // $ExpectError + isProbabilityf( false ); // $ExpectError + isProbabilityf( null ); // $ExpectError + isProbabilityf( undefined ); // $ExpectError + isProbabilityf( [] ); // $ExpectError + isProbabilityf( {} ); // $ExpectError + isProbabilityf( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isProbabilityf(); // $ExpectError + isProbabilityf( undefined, 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/c/example.c b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/c/example.c new file mode 100644 index 000000000000..41fd9c64ebfb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/c/example.c @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/assert/is_probabilityf.h" +#include +#include +#include + +int main( void ) { + float x; + bool v; + int i; + + for ( i = 0; i < 100; i++ ) { + x = ( ( (float)rand() / (float)RAND_MAX ) * 2.0f ) - 1.0f; + v = stdlib_base_is_probabilityf( x ); + printf( "%f is %sa probability\n", x, ( v ) ? "" : "not " ); + } +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/index.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/index.js new file mode 100644 index 000000000000..f2d14cfb1fec --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var isProbabilityf = require( './../lib' ); + +var x = uniform( 100, -1.0, 1.0, { + 'dtype': 'float32' +}); + +var i; +for ( i = 0; i < 100; i++ ) { + console.log( '%d is %s', x[ i ], ( isProbabilityf( x[ i ] ) ) ? 'a probability' : 'not a probability' ); +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/include.gypi b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Tests if a single-precision floating-point number is a probability. +*/ +bool stdlib_base_is_probabilityf( const float x ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_MATH_BASE_ASSERT_IS_PROBABILITYF_H diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/index.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/index.js new file mode 100644 index 000000000000..94fd0fa67120 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test if a single-precision floating-point number is a probability. +* +* @module @stdlib/math/base/assert/is-probabilityf +* +* @example +* var isProbabilityf = require( '@stdlib/math/base/assert/is-probabilityf' ); +* +* var bool = isProbabilityf( 0.5 ); +* // returns true +* +* bool = isProbabilityf( 3.14 ); +* // returns false +* +* bool = isProbabilityf( NaN ); +* // returns false +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/main.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/main.js new file mode 100644 index 000000000000..062691f239d2 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/main.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Tests if a single-precision floating-point number is a probability. +* +* @param {number} x - value to test +* @returns {boolean} boolean indicating whether the value is a probability +* +* @example +* var bool = isProbabilityf( 0.5 ); +* // returns true +* +* @example +* var bool = isProbabilityf( 3.14 ); +* // returns false +* +* @example +* var bool = isProbabilityf( NaN ); +* // returns false +*/ +function isProbabilityf( x ) { + return ( x >= 0.0 && x <= 1.0 ); +} + + +// EXPORTS // + +module.exports = isProbabilityf; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/native.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/native.js new file mode 100644 index 000000000000..1b3de3e2f556 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var Boolean = require( '@stdlib/boolean/ctor' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Tests if a single-precision floating-point number is a probability. +* +* @private +* @param {number} x - value to test +* @returns {boolean} boolean indicating whether the value is a probability +* +* @example +* var bool = isProbabilityf( 0.5 ); +* // returns true +* +* @example +* var bool = isProbabilityf( 3.14 ); +* // returns false +* +* @example +* var bool = isProbabilityf( NaN ); +* // returns false +*/ +function isProbabilityf( x ) { + return Boolean( addon( x ) ); +} + + +// EXPORTS // + +module.exports = isProbabilityf; diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/manifest.json new file mode 100644 index 000000000000..96b478e49058 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/manifest.json @@ -0,0 +1,70 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/argv", + "@stdlib/napi/argv-float", + "@stdlib/napi/create-int32", + "@stdlib/napi/export" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [] + } + ] +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/package.json b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/package.json new file mode 100644 index 000000000000..a611860147db --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/package.json @@ -0,0 +1,79 @@ +{ + "name": "@stdlib/math/base/assert/is-probabilityf", + "version": "0.0.0", + "description": "Test if a single-precision floating-point number is a probability.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "assertion", + "assert", + "utilities", + "utility", + "utils", + "util", + "math", + "mathematics", + "float", + "number", + "numeric", + "probability", + "prob", + "is", + "isprobabilityf", + "isprob", + "type", + "check", + "valid", + "validate", + "test" + ] +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/Makefile b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/addon.c new file mode 100644 index 000000000000..bb68a57eb8bf --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/addon.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/assert/is_probabilityf.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, x, argv, 0 ); + STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_probabilityf( x ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/main.c b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/main.c new file mode 100644 index 000000000000..89b43b358418 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/src/main.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/assert/is_probabilityf.h" +#include + +/** +* Tests if a single-precision floating-point number is a probability. +* +* @param x input value +* @return output value +* +* @example +* #include +* +* bool out = stdlib_base_is_probabilityf( 0.5f ); +* // returns true +* +* out = stdlib_base_is_probabilityf( 1.5f ); +* // returns false +*/ +bool stdlib_base_is_probabilityf( const float x ) { + return ( x >= 0.0f && x <= 1.0f ); +} diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/test/test.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/test/test.js new file mode 100644 index 000000000000..0160e5f6efa9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/test/test.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var PINF = require( '@stdlib/constants/float32/pinf' ); +var NINF = require( '@stdlib/constants/float32/ninf' ); +var randu = require( '@stdlib/random/base/randu' ); +var isProbabilityf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof isProbabilityf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `false` if provided a number less than `0.0`', function test( t ) { + var bool; + var x; + var i; + for ( i = 0; i < 1000; i++ ) { + x = -1.0 - ( randu() * 1000.0 ); + bool = isProbabilityf( x ); + t.equal( bool, false, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `false` if provided a number greater than `1.0`', function test( t ) { + var bool; + var x; + var i; + for ( i = 0; i < 1000; i++ ) { + x = ( randu() * 1000.0 ) + 2.0; + bool = isProbabilityf( x ); + t.equal( bool, false, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `true` if provided a probability', function test( t ) { + var bool; + var x; + var i; + for ( i = 0; i < 1000; i++ ) { + x = randu(); + bool = isProbabilityf( x ); + t.equal( bool, true, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `true` if provided `+-0`', function test( t ) { + t.equal( isProbabilityf( 0.0 ), true, 'returns expected value' ); + t.equal( isProbabilityf( -0.0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `true` if provided `1`', function test( t ) { + t.equal( isProbabilityf( 1.0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if provided `+infinity`', function test( t ) { + t.equal( isProbabilityf( PINF ), false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if provided `-infinity`', function test( t ) { + t.equal( isProbabilityf( NINF ), false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if provided `NaN`', function test( t ) { + t.equal( isProbabilityf( NaN ), false, 'returns expected value' ); + t.equal( isProbabilityf( 0.0 / 0.0 ), false, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/test/test.native.js b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/test/test.native.js new file mode 100644 index 000000000000..5cd7db10e954 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/assert/is-probabilityf/test/test.native.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var PINF = require( '@stdlib/constants/float32/pinf' ); +var NINF = require( '@stdlib/constants/float32/ninf' ); +var randu = require( '@stdlib/random/base/randu' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var isProbabilityf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( isProbabilityf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof isProbabilityf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `false` if provided a number less than `0.0`', opts, function test( t ) { + var bool; + var x; + var i; + for ( i = 0; i < 1000; i++ ) { + x = -1.0 - ( randu() * 1000.0 ); + bool = isProbabilityf( x ); + t.equal( bool, false, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `false` if provided a number greater than `1.0`', opts, function test( t ) { + var bool; + var x; + var i; + for ( i = 0; i < 1000; i++ ) { + x = ( randu() * 1000.0 ) + 2.0; + bool = isProbabilityf( x ); + t.equal( bool, false, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `true` if provided a probability', opts, function test( t ) { + var bool; + var x; + var i; + for ( i = 0; i < 1000; i++ ) { + x = randu(); + bool = isProbabilityf( x ); + t.equal( bool, true, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `true` if provided `+-0`', opts, function test( t ) { + t.equal( isProbabilityf( 0.0 ), true, 'returns expected value' ); + t.equal( isProbabilityf( -0.0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `true` if provided `1`', opts, function test( t ) { + t.equal( isProbabilityf( 1.0 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if provided `+infinity`', opts, function test( t ) { + t.equal( isProbabilityf( PINF ), false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if provided `-infinity`', opts, function test( t ) { + t.equal( isProbabilityf( NINF ), false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if provided `NaN`', opts, function test( t ) { + t.equal( isProbabilityf( NaN ), false, 'returns expected value' ); + t.equal( isProbabilityf( 0.0 / 0.0 ), false, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/napi/binary/README.md b/lib/node_modules/@stdlib/math/base/napi/binary/README.md index e1ff3cd3af7a..f92b10cb0563 100644 --- a/lib/node_modules/@stdlib/math/base/napi/binary/README.md +++ b/lib/node_modules/@stdlib/math/base/napi/binary/README.md @@ -331,6 +331,46 @@ The function accepts the following arguments: void stdlib_math_base_napi_di_d( napi_env env, napi_callback_info info, double (*fcn)( double, int32_t ) ); ``` +#### stdlib_math_base_napi_id_d( env, info, fcn ) + +Invokes a binary function accepting a signed 32-bit integer and a double-precision floating-point number and returning a double-precision floating-point number. + +```c +#include +#include + +// ... + +static double mul( const int32_t x, const double y ) { + return x * y; +} + +// ... + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +napi_value addon( napi_env env, napi_callback_info info ) { + return stdlib_math_base_napi_id_d( env, info, mul ); +} + +// ... +``` + +The function accepts the following arguments: + +- **env**: `[in] napi_env` environment under which the function is invoked. +- **info**: `[in] napi_callback_info` callback data. +- **fcn**: `[in] double (*fcn)( int32_t, double )` binary function. + +```c +void stdlib_math_base_napi_id_d( napi_env env, napi_callback_info info, double (*fcn)( int32_t, double ) ); +``` + #### stdlib_math_base_napi_ii_i( env, info, fcn ) Invokes a binary function accepting and returning signed 32-bit integers. @@ -820,6 +860,29 @@ The macro expects the following arguments: When used, this macro should be used **instead of** `NAPI_MODULE`. The macro includes `NAPI_MODULE`, thus ensuring Node-API module registration. +#### STDLIB_MATH_BASE_NAPI_MODULE_ID_D( fcn ) + +Macro for registering a Node-API module exporting an interface invoking a binary function accepting a signed 32-bit integer and a double-precision floating-point number and returning a double-precision floating-point number. + +```c +#include + +static double mul( const int32_t x, const double y ) { + return x * y; +} + +// ... + +// Register a Node-API module: +STDLIB_MATH_BASE_NAPI_MODULE_ID_D( mul ); +``` + +The macro expects the following arguments: + +- **fcn**: `double (*fcn)( int32_t, double )` binary function. + +When used, this macro should be used **instead of** `NAPI_MODULE`. The macro includes `NAPI_MODULE`, thus ensuring Node-API module registration. + #### STDLIB_MATH_BASE_NAPI_MODULE_FI_F( fcn ) Macro for registering a Node-API module exporting an interface invoking a binary function accepting a single-precision floating-point number and a signed 32-bit integer and returning a single-precision floating-point number. diff --git a/lib/node_modules/@stdlib/math/base/napi/binary/include/stdlib/math/base/napi/binary.h b/lib/node_modules/@stdlib/math/base/napi/binary/include/stdlib/math/base/napi/binary.h index 4315f1072eac..13328645083a 100644 --- a/lib/node_modules/@stdlib/math/base/napi/binary/include/stdlib/math/base/napi/binary.h +++ b/lib/node_modules/@stdlib/math/base/napi/binary/include/stdlib/math/base/napi/binary.h @@ -342,6 +342,48 @@ }; \ NAPI_MODULE( NODE_GYP_MODULE_NAME, stdlib_math_base_napi_di_d_init ) +/** +* Macro for registering a Node-API module exporting an interface invoking a binary function accepting a signed 32-bit integer and a double-precision floating-point number and returning a double-precision floating-point number. +* +* @param fcn binary function +* +* @example +* #include +* +* static double mul( const int32_t n, const double x ) { +* return x * n; +* } +* +* // ... +* +* // Register a Node-API module: +* STDLIB_MATH_BASE_NAPI_MODULE_ID_D( mul ); +*/ +#define STDLIB_MATH_BASE_NAPI_MODULE_ID_D( fcn ) \ + static napi_value stdlib_math_base_napi_id_d_wrapper( \ + napi_env env, \ + napi_callback_info info \ + ) { \ + return stdlib_math_base_napi_id_d( env, info, fcn ); \ + }; \ + static napi_value stdlib_math_base_napi_id_d_init( \ + napi_env env, \ + napi_value exports \ + ) { \ + napi_value fcn; \ + napi_status status = napi_create_function( \ + env, \ + "exports", \ + NAPI_AUTO_LENGTH, \ + stdlib_math_base_napi_id_d_wrapper, \ + NULL, \ + &fcn \ + ); \ + assert( status == napi_ok ); \ + return fcn; \ + }; \ + NAPI_MODULE( NODE_GYP_MODULE_NAME, stdlib_math_base_napi_id_d_init ) + /** * Macro for registering a Node-API module exporting an interface invoking a binary function accepting a single-precision floating-point number and a signed 32-bit integer and returning a single-precision floating-point number. * @@ -690,6 +732,11 @@ napi_value stdlib_math_base_napi_cc_c( napi_env env, napi_callback_info info, st */ napi_value stdlib_math_base_napi_di_d( napi_env env, napi_callback_info info, double (*fcn)( double, int32_t ) ); +/** +* Invokes a binary function accepting a signed 32-bit integer and a double-precision floating-point number and returning a double-precision floating-point number. +*/ +napi_value stdlib_math_base_napi_id_d( napi_env env, napi_callback_info info, double (*fcn)( int32_t, double ) ); + /** * Invokes a binary function accepting signed 32-bit integers and returning a double-precision floating-point number. */ diff --git a/lib/node_modules/@stdlib/math/base/napi/binary/src/main.c b/lib/node_modules/@stdlib/math/base/napi/binary/src/main.c index 07d3b89c5f6e..b6de9eb38b48 100644 --- a/lib/node_modules/@stdlib/math/base/napi/binary/src/main.c +++ b/lib/node_modules/@stdlib/math/base/napi/binary/src/main.c @@ -524,6 +524,68 @@ napi_value stdlib_math_base_napi_di_d( napi_env env, napi_callback_info info, do return v; } +/** +* Invokes a binary function accepting a signed 32-bit integer and a double-precision floating-point number and returning a double-precision floating-point number. +* +* ## Notes +* +* - This function expects that the callback `info` argument provides access to the following JavaScript arguments: +* +* - `x`: input value. +* - `y`: input value. +* +* @param env environment under which the function is invoked +* @param info callback data +* @param fcn binary function +* @return function return value as a Node-API double-precision floating-point number +*/ +napi_value stdlib_math_base_napi_id_d( napi_env env, napi_callback_info info, double (*fcn)( int32_t, double ) ) { + napi_status status; + + size_t argc = 2; + napi_value argv[ 2 ]; + status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); + assert( status == napi_ok ); + + if ( argc < 2 ) { + status = napi_throw_error( env, NULL, "invalid invocation. Must provide two numbers." ); + assert( status == napi_ok ); + return NULL; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); + assert( status == napi_ok ); + return NULL; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + status = napi_throw_type_error( env, NULL, "invalid argument. Second argument must be a number." ); + assert( status == napi_ok ); + return NULL; + } + + int32_t x; + status = napi_get_value_int32( env, argv[ 0 ], &x ); + assert( status == napi_ok ); + + double y; + status = napi_get_value_double( env, argv[ 1 ], &y ); + assert( status == napi_ok ); + + napi_value v; + status = napi_create_double( env, fcn( x, y ), &v ); + assert( status == napi_ok ); + + return v; +} + /** * Invokes a binary function accepting signed 32-bit integers and returning a double-precision floating-point number. * diff --git a/lib/node_modules/@stdlib/math/base/napi/ternary/README.md b/lib/node_modules/@stdlib/math/base/napi/ternary/README.md index 4dca5fb065f2..889c4a4160d5 100644 --- a/lib/node_modules/@stdlib/math/base/napi/ternary/README.md +++ b/lib/node_modules/@stdlib/math/base/napi/ternary/README.md @@ -222,6 +222,46 @@ The function accepts the following arguments: void stdlib_math_base_napi_dii_d( napi_env env, napi_callback_info info, double (*fcn)( double, int32_t, int32_t ) ); ``` +#### stdlib_math_base_napi_iid_d( env, info, fcn ) + +Invokes a ternary function accepting two signed 32-bit integers and a double-precision floating-point number and returning a double-precision floating-point number. + +```c +#include +#include + +// ... + +static double fcn( const int32_t x, const int32_t y, const double z ) { + // ... +} + +// ... + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +napi_value addon( napi_env env, napi_callback_info info ) { + return stdlib_math_base_napi_iid_d( env, info, fcn ); +} + +// ... +``` + +The function accepts the following arguments: + +- **env**: `[in] napi_env` environment under which the function is invoked. +- **info**: `[in] napi_callback_info` callback data. +- **fcn**: `[in] double (*fcn)( int32_t, int32_t, double )` ternary function. + +```c +void stdlib_math_base_napi_iid_d( napi_env env, napi_callback_info info, double (*fcn)( int32_t, int32_t, double ) ); +``` + #### STDLIB_MATH_BASE_NAPI_MODULE_DDD_D( fcn ) Macro for registering a Node-API module exporting an interface for invoking a ternary function accepting and returning double-precision floating-point numbers. @@ -287,6 +327,29 @@ The macro expects the following arguments: When used, this macro should be used **instead of** `NAPI_MODULE`. The macro includes `NAPI_MODULE`, thus ensuring Node-API module registration. +#### STDLIB_MATH_BASE_NAPI_MODULE_IID_D( fcn ) + +Macro for registering a Node-API module exporting an interface for invoking a ternary function accepting two signed 32-bit integers and a double-precision floating-point number and returning a double-precision floating-point number. + +```c +#include + +static double fcn( const int32_t x, const int32_t y, const double z ) { + // ... +} + +// ... + +// Register a Node-API module: +STDLIB_MATH_BASE_NAPI_MODULE_IID_D( fcn ); +``` + +The macro expects the following arguments: + +- **fcn**: `double (*fcn)( int32_t, int32_t, double )` ternary function. + +When used, this macro should be used **instead of** `NAPI_MODULE`. The macro includes `NAPI_MODULE`, thus ensuring Node-API module registration. + diff --git a/lib/node_modules/@stdlib/math/base/napi/ternary/include/stdlib/math/base/napi/ternary.h b/lib/node_modules/@stdlib/math/base/napi/ternary/include/stdlib/math/base/napi/ternary.h index 514b72add029..68a1ff9a0351 100644 --- a/lib/node_modules/@stdlib/math/base/napi/ternary/include/stdlib/math/base/napi/ternary.h +++ b/lib/node_modules/@stdlib/math/base/napi/ternary/include/stdlib/math/base/napi/ternary.h @@ -144,6 +144,48 @@ }; \ NAPI_MODULE( NODE_GYP_MODULE_NAME, stdlib_math_base_napi_dii_d_init ) +/** +* Macro for registering a Node-API module exporting an interface invoking a ternary function accepting two signed 32-bit integers and a double-precision floating-point number and returning a double-precision floating-point number. +* +* @param fcn ternary function +* +* @example +* #include +* +* static double fcn( const int_32 x, const int_32 y, const double z ) { +* // ... +* } +* +* // ... +* +* // Register a Node-API module: +* STDLIB_MATH_BASE_NAPI_MODULE_IID_D( fcn ); +*/ +#define STDLIB_MATH_BASE_NAPI_MODULE_IID_D( fcn ) \ + static napi_value stdlib_math_base_napi_iid_d_wrapper( \ + napi_env env, \ + napi_callback_info info \ + ) { \ + return stdlib_math_base_napi_iid_d( env, info, fcn ); \ + }; \ + static napi_value stdlib_math_base_napi_iid_d_init( \ + napi_env env, \ + napi_value exports \ + ) { \ + napi_value fcn; \ + napi_status status = napi_create_function( \ + env, \ + "exports", \ + NAPI_AUTO_LENGTH, \ + stdlib_math_base_napi_iid_d_wrapper, \ + NULL, \ + &fcn \ + ); \ + assert( status == napi_ok ); \ + return fcn; \ + }; \ + NAPI_MODULE( NODE_GYP_MODULE_NAME, stdlib_math_base_napi_iid_d_init ) + /* * If C++, prevent name mangling so that the compiler emits a ternary file having undecorated names, thus mirroring the behavior of a C compiler. */ @@ -166,6 +208,11 @@ napi_value stdlib_math_base_napi_fff_f( napi_env env, napi_callback_info info, f */ napi_value stdlib_math_base_napi_dii_d( napi_env env, napi_callback_info info, double (*fcn)( double, int32_t, int32_t ) ); +/** +* Invokes a ternary function accepting two signed 32-bit integers and a double-precision floating-point number and returning a double-precision floating-point number. +*/ +napi_value stdlib_math_base_napi_iid_d( napi_env env, napi_callback_info info, double (*fcn)( int32_t, int32_t, double ) ); + #ifdef __cplusplus } #endif diff --git a/lib/node_modules/@stdlib/math/base/napi/ternary/src/main.c b/lib/node_modules/@stdlib/math/base/napi/ternary/src/main.c index 92b89ca0999e..e780fdb2679d 100644 --- a/lib/node_modules/@stdlib/math/base/napi/ternary/src/main.c +++ b/lib/node_modules/@stdlib/math/base/napi/ternary/src/main.c @@ -248,3 +248,79 @@ napi_value stdlib_math_base_napi_dii_d( napi_env env, napi_callback_info info, d return v; } + +/** +* Invokes a ternary function accepting two signed 32-bit integers and a double-precision floating-point number and returning a double-precision floating-point number. +* +* ## Notes +* +* - This function expects that the callback `info` argument provides access to the following JavaScript arguments: +* +* - `x`: input value. +* - `y`: input value. +* - `z`: input value. +* +* @param env environment under which the function is invoked +* @param info callback data +* @param fcn ternary function +* @return function return value as a Node-API double-precision floating-point number +*/ +napi_value stdlib_math_base_napi_iid_d( napi_env env, napi_callback_info info, double (*fcn)( int32_t, int32_t, double ) ) { + napi_status status; + + size_t argc = 3; + napi_value argv[ 3 ]; + status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); + assert( status == napi_ok ); + + if ( argc < 3 ) { + status = napi_throw_error( env, NULL, "invalid invocation. Must provide three numbers." ); + assert( status == napi_ok ); + return NULL; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); + assert( status == napi_ok ); + return NULL; + } + + napi_valuetype vtype1; + status = napi_typeof( env, argv[ 1 ], &vtype1 ); + assert( status == napi_ok ); + if ( vtype1 != napi_number ) { + status = napi_throw_type_error( env, NULL, "invalid argument. Second argument must be a number." ); + assert( status == napi_ok ); + return NULL; + } + + napi_valuetype vtype2; + status = napi_typeof( env, argv[ 2 ], &vtype2 ); + assert( status == napi_ok ); + if ( vtype2 != napi_number ) { + status = napi_throw_type_error( env, NULL, "invalid argument. Third argument must be a number." ); + assert( status == napi_ok ); + return NULL; + } + + int32_t x; + status = napi_get_value_int32( env, argv[ 1 ], &x ); + assert( status == napi_ok ); + + int32_t y; + status = napi_get_value_int32( env, argv[ 2 ], &y ); + assert( status == napi_ok ); + + double z; + status = napi_get_value_double( env, argv[ 0 ], &z ); + assert( status == napi_ok ); + + napi_value v; + status = napi_create_double( env, fcn( x, y, z ), &v ); + assert( status == napi_ok ); + + return v; +} diff --git a/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts index 7cb29ee23301..dc947fe0f75f 100644 --- a/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/ops/docs/types/index.d.ts @@ -156,6 +156,25 @@ interface Namespace { * * var im = imag( out ); * // returns -1.0 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var out = new Float64Array( 2 ); + * var v = ns.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 ); + * // returns [ -13.0, -1.0 ] + * + * var bool = ( out === v ); + * // returns true + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var z1 = new Float64Array( [ 5.0, 3.0 ] ); + * var z2 = new Float64Array( [ -2.0, 1.0 ] ); + * + * var out = ns.cmul.strided( z1, 1, 0, z2, 1, 0, new Float64Array( 2 ), 1, 0 ); + * // returns [ -13.0, -1.0 ] */ cmul: typeof cmul; diff --git a/lib/node_modules/@stdlib/math/base/special/asecdf/README.md b/lib/node_modules/@stdlib/math/base/special/asecdf/README.md index 4aaf60672a32..6a43565fa20b 100644 --- a/lib/node_modules/@stdlib/math/base/special/asecdf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/asecdf/README.md @@ -184,6 +184,13 @@ int main( void ) {
+* * * + +## See Also + +- [`@stdlib/math/base/special/asec`][@stdlib/math/base/special/asec]: compute the inverse (arc) secant of a number. +- [`@stdlib/math/base/special/asech`][@stdlib/math/base/special/asech]: compute the hyperbolic arcsecant of a number. +
@@ -196,6 +203,10 @@ int main( void ) { +[@stdlib/math/base/special/asec]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/asec + +[@stdlib/math/base/special/asech]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/asech + diff --git a/lib/node_modules/@stdlib/math/base/special/asindf/README.md b/lib/node_modules/@stdlib/math/base/special/asindf/README.md index 355f0ccb6457..18a2f8b08668 100644 --- a/lib/node_modules/@stdlib/math/base/special/asindf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/asindf/README.md @@ -178,6 +178,13 @@ int main( void ) {
+* * * + +## See Also + +- [`@stdlib/math/base/special/asinf`][@stdlib/math/base/special/asinf]: compute the arcsine of a single-precision floating-point number. +- [`@stdlib/math/base/special/asind`][@stdlib/math/base/special/asind]: compute the arcsine (in degrees) of a double-precision floating-point number. +
@@ -190,6 +197,10 @@ int main( void ) { +[@stdlib/math/base/special/asinf]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/asinf + +[@stdlib/math/base/special/asind]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/asind + diff --git a/lib/node_modules/@stdlib/math/base/special/atan2/README.md b/lib/node_modules/@stdlib/math/base/special/atan2/README.md index 8fbe8f342903..7d29251abe08 100755 --- a/lib/node_modules/@stdlib/math/base/special/atan2/README.md +++ b/lib/node_modules/@stdlib/math/base/special/atan2/README.md @@ -117,7 +117,7 @@ for ( i = 0; i < 100; i++ ) { Computes the angle in the plane (in radians) between the positive x-axis and the ray from `(0,0)` to the point `(x,y)`. ```c -double out = stdlib_base_atan2( 2.0, 2.0 ); +double out = stdlib_base_atan2( 2.0, 2.0 ); // returns ~0.785 out = stdlib_base_atan2( 6.0, 2.0 ); @@ -126,8 +126,8 @@ out = stdlib_base_atan2( 6.0, 2.0 ); The function accepts the following arguments: -- **y**: `[in] double` - `y` coordinate -- **x**: `[in] double` - `x` coordinate +- **y**: `[in] double` - `y` coordinate. +- **x**: `[in] double` - `x` coordinate. ```c double stdlib_base_atan2( const double y, const double x ); diff --git a/lib/node_modules/@stdlib/math/base/special/cceilf/README.md b/lib/node_modules/@stdlib/math/base/special/cceilf/README.md index a7c08ee41be0..99b848325ca5 100644 --- a/lib/node_modules/@stdlib/math/base/special/cceilf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cceilf/README.md @@ -176,7 +176,7 @@ int main( void ) { ## See Also -- [`@stdlib/math/base/special/cceil`][@stdlib/math/base/special/cceil]: round a double-precision complex floating-point number toward positive infinity. +- [`@stdlib/math/base/special/cceil`][@stdlib/math/base/special/cceil]: round each component of a double-precision complex floating-point number toward positive infinity. diff --git a/lib/node_modules/@stdlib/math/base/special/cosd/README.md b/lib/node_modules/@stdlib/math/base/special/cosd/README.md index 806287504ec9..d2663660456f 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosd/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosd/README.md @@ -170,6 +170,12 @@ int main( void ) {
+* * * + +## See Also + +- [`@stdlib/math/base/special/tand`][@stdlib/math/base/special/tand]: compute the tangent of an angle measured in degrees. +
@@ -182,6 +188,8 @@ int main( void ) { +[@stdlib/math/base/special/tand]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/tand + diff --git a/lib/node_modules/@stdlib/math/base/special/coth/src/main.c b/lib/node_modules/@stdlib/math/base/special/coth/src/main.c index 87c0e821e78f..a9ef72d521c0 100644 --- a/lib/node_modules/@stdlib/math/base/special/coth/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/coth/src/main.c @@ -62,7 +62,7 @@ * * @example * double out = stdlib_base_coth( 0.0 ); -* // returns INFINITY +* // returns +Infinity */ double stdlib_base_coth( const double x ) { diff --git a/lib/node_modules/@stdlib/math/base/special/cround/README.md b/lib/node_modules/@stdlib/math/base/special/cround/README.md index 64a8f3f122a6..911092aadfe7 100644 --- a/lib/node_modules/@stdlib/math/base/special/cround/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cround/README.md @@ -224,7 +224,7 @@ int main( void ) { ## See Also -- [`@stdlib/math/base/special/cceil`][@stdlib/math/base/special/cceil]: round a double-precision complex floating-point number toward positive infinity. +- [`@stdlib/math/base/special/cceil`][@stdlib/math/base/special/cceil]: round each component of a double-precision complex floating-point number toward positive infinity. - [`@stdlib/math/base/special/cfloor`][@stdlib/math/base/special/cfloor]: round a double-precision complex floating-point number toward negative infinity. - [`@stdlib/math/base/special/croundn`][@stdlib/math/base/special/croundn]: round each component of a double-precision complex floating-point number to the nearest multiple of 10^n. diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/README.md b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/README.md new file mode 100644 index 000000000000..84e96cae0cc4 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/README.md @@ -0,0 +1,221 @@ + + +# Dirac Delta + +> Evaluate the [Dirac delta function][dirac-delta-function] for a single-precision floating-point number. + +
+ +The [Dirac delta function][dirac-delta-function] may be loosely defined as + + + +```math +\delta = \begin{cases} \infty & \textrm{if}\ x = 0 \\ 0 & \textrm{if}\ x \neq 0\end{cases} +``` + + + + + +and is constrained to satisfy the identity + + + +```math +\int^{+\infty}_{-\infty} \delta(x)\ dx = 1 +``` + + + + + +Note that the [Dirac delta function][dirac-delta-function] is **not** a function in the traditional sense, as any real-valued function which is zero everywhere except at a single point, must have an integral equal to `0`. + +
+ + + +
+ +## Usage + +```javascript +var diracDeltaf = require( '@stdlib/math/base/special/dirac-deltaf' ); +``` + +#### diracDeltaf( x ) + +Evaluates the [Dirac delta function][dirac-delta-function] for a single-precision floating-point number. + +```javascript +var v = diracDeltaf( 0.0 ); +// returns Infinity + +v = diracDeltaf( 3.14 ); +// returns 0.0 + +v = diracDeltaf( NaN ); +// returns NaN +``` + +
+ + + +
+ +## Examples + + + +```javascript +var linspace = require( '@stdlib/array/base/linspace' ); +var diracDeltaf = require( '@stdlib/math/base/special/dirac-deltaf' ); + +var x = linspace( -1.0, 1.0, 101 ); + +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( 'dirac(%d) = %d', x[ i ], diracDeltaf( x[ i ] ) ); +} +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/special/dirac_deltaf.h" +``` + +#### stdlib_base_dirac_deltaf( x ) + +Evaluates the [Dirac delta function][dirac-delta-function] for a single-precision floating-point number. + +```c +float x = stdlib_base_dirac_deltaf( 0.0f ); +// returns Infinity + +x = stdlib_base_dirac_deltaf( 3.14f ); +// returns 0.0f +``` + +The function accepts the following arguments: + +- **x**: `[in] float` input value. + +```c +float stdlib_base_dirac_delta( const float x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/math/base/special/dirac_deltaf.h" +#include +#include + +int main( void ) { + const float x[] = { -1.0f, -0.5f, 0.0f, 0.5f, 1.0f, 3.14f, 2.0f }; + + float v; + int i; + for ( i = 0; i < 7; i++ ) { + v = stdlib_base_dirac_deltaf( x[ i ] ); + printf( "dirac(%f) = %f\n", x[ i ], v ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[dirac-delta-function]: https://en.wikipedia.org/wiki/Dirac_delta_function + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/benchmark.js new file mode 100644 index 000000000000..e78e64b4e07b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/array/discrete-uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pkg = require( './../package.json' ).name; +var diracDeltaf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var x; + var y; + var i; + + x = randu( 100, -50, 50 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = diracDeltaf( x[ i % x.length ] ); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..eb56ae4837a9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/benchmark.native.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/array/discrete-uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var diracDeltaf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( diracDeltaf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var x; + var y; + var i; + + x = randu( 100, -50, 50 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = diracDeltaf( x[ i % x.length ] ); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/Makefile b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/Makefile new file mode 100644 index 000000000000..d564e8b2d6f9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/Makefile @@ -0,0 +1,127 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles C source files. +# +# @param {string} [C_COMPILER] - C compiler +# @param {string} [CFLAGS] - C compiler flags +# @param {(string|void)} [fPIC] - compiler flag indicating whether to generate position independent code +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler +# @param {string} CFLAGS - C compiler flags +# @param {(string|void)} fPIC - compiler flag indicating whether to generate position independent code +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) -o $@ $< -lm + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..13fd840a4104 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/benchmark.c @@ -0,0 +1,145 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include +#include +#include +#include +#include + +#define NAME "dirac-deltaf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Computes the Dirac delta function in single-precision floating-point format. +* +* @param x input value +* @return function result +*/ +static float dirac_deltaf( float x ) { + if ( x == 0.0f ) { + return HUGE_VAL; + } + return 0.0f; +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double x; + double y; + double t; + int i; + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + x = ( 100.0f * rand_float() ) - 50.0f; + y = dirac_deltaf( x ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/native/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..1b756508592f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/benchmark/c/native/benchmark.c @@ -0,0 +1,136 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/dirac_deltaf.h" +#include +#include +#include +#include +#include + +#define NAME "dirac_deltaf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + float x[ 100 ]; + float y; + double t; + int i; + + for ( i = 0; i < 100 ; i++ ) { + x[ i ] = ( 100.0f * rand_float() ) - 50.0f; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dirac_deltaf( x[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/binding.gyp b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/img/equation_dirac_delta.svg b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/img/equation_dirac_delta.svg new file mode 100644 index 000000000000..60b6fe1d414a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/img/equation_dirac_delta.svg @@ -0,0 +1,44 @@ + +delta equals StartLayout Enlarged left-brace 1st Row 1st Column normal infinity 2nd Column if x equals 0 2nd Row 1st Column 0 2nd Column if x not-equals 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/img/equation_dirac_delta_integral.svg b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/img/equation_dirac_delta_integral.svg new file mode 100644 index 000000000000..fe4f8aa13bf7 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/img/equation_dirac_delta_integral.svg @@ -0,0 +1,35 @@ + +integral Subscript negative normal infinity Superscript plus normal infinity Baseline delta left-parenthesis x right-parenthesis d x equals 1 + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/repl.txt b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/repl.txt new file mode 100644 index 000000000000..8c648f2251eb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( x ) + Evaluates the Dirac delta function for a single-precision + floating-point number. + + Parameters + ---------- + x: number + Input value. + + Returns + ------- + y: number + Function value. + + Examples + -------- + > var y = {{alias}}( 3.14 ) + 0.0 + > y = {{alias}}( 0.0 ) + Infinity + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/types/index.d.ts new file mode 100644 index 000000000000..4ad65db19ba3 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/types/index.d.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the Dirac delta function for a single-precision floating-point number. +* +* @param x - input value +* @returns function value +* +* @example +* var v = diracDeltaf( 0.0 ); +* // returns Infinity +* +* @example +* var v = diracDeltaf( 3.14 ); +* // returns 0.0 +* +* @example +* var v = diracDeltaf( NaN ); +* // returns NaN +*/ +declare function diracDeltaf( x: number ): number; + + +// EXPORTS // + +export = diracDeltaf; diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/types/test.ts new file mode 100644 index 000000000000..d4438fe58bc2 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import diracDeltaf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + diracDeltaf( 8 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + diracDeltaf( true ); // $ExpectError + diracDeltaf( false ); // $ExpectError + diracDeltaf( null ); // $ExpectError + diracDeltaf( undefined ); // $ExpectError + diracDeltaf( '5' ); // $ExpectError + diracDeltaf( [] ); // $ExpectError + diracDeltaf( {} ); // $ExpectError + diracDeltaf( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + diracDeltaf(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/c/example.c new file mode 100644 index 000000000000..0cf283bfcf0f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/c/example.c @@ -0,0 +1,32 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/dirac_deltaf.h" +#include +#include + +int main( void ) { + const float x[] = { -1.0f, -0.5f, 0.0f, 0.5f, 1.0f, 3.14f, 2.0f }; + + float v; + int i; + for ( i = 0; i < 7; i++ ) { + v = stdlib_base_dirac_deltaf( x[ i ] ); + printf( "dirac(%f) = %f\n", x[ i ], v ); + } +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/index.js b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/index.js new file mode 100644 index 000000000000..c73fc1acf1a0 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var linspace = require( '@stdlib/array/base/linspace' ); +var diracDeltaf = require( './../lib' ); + +var x = linspace( -1.0, 1.0, 101 ); + +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( 'dirac(%d) = %d', x[ i ], diracDeltaf( x[ i ] ) ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/include.gypi b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "dirac", + "delta", + "distribution", + "dist", + "continuous", + "kronecker", + "spike", + "impulse" + ] +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/Makefile b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/addon.c b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/addon.c new file mode 100644 index 000000000000..6b3981b68f1d --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/dirac_deltaf.h" +#include "stdlib/math/base/napi/unary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_F_F( stdlib_base_dirac_deltaf ) diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/main.c b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/main.c new file mode 100644 index 000000000000..2f95a61e60b2 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/src/main.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/dirac_deltaf.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/constants/float32/pinf.h" + +/** +* Evaluates the Dirac delta function for a single-precision floating-point number. +* +* @param x input value +* @return output value +* +* @example +* float out = stdlib_base_dirac_deltaf( 3.14f ); +* // returns 0.0f +*/ +float stdlib_base_dirac_deltaf( const float x ) { + if ( stdlib_base_is_nanf( x ) ) { + return 0.0f / 0.0f; // NaN + } + if ( x == 0.0f ) { + return STDLIB_CONSTANT_FLOAT32_PINF; + } + return 0.0f; +} diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/test/test.js b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/test/test.js new file mode 100644 index 000000000000..318a99db6bea --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/test/test.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var PINF = require( '@stdlib/constants/float32/pinf' ); +var NINF = require( '@stdlib/constants/float32/ninf' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var randu = require( '@stdlib/random/base/randu' ); +var diracDeltaf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof diracDeltaf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `0` if `x` does not equal `0`', function test( t ) { + var x; + var v; + var i; + + for ( i = 0; i < 1e3; i++ ) { + x = ( randu() * 100.0 ) - 50.0; + if ( x === 0.0 ) { + x += EPS; + } + v = diracDeltaf( x ); + t.equal( isPositiveZerof( v ), true, 'returns 0 when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `+infinity` if `x` equals `0`', function test( t ) { + var v = diracDeltaf( 0.0 ); + t.equal( v, PINF, 'returns +infinity' ); + t.end(); +}); + +tape( 'the function returns `NaN` if provided a `NaN`', function test( t ) { + var v = diracDeltaf( NaN ); + t.equal( isnanf( v ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'the function returns `0` if provided `+infinity`', function test( t ) { + var v = diracDeltaf( PINF ); + t.equal( v, 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'the function returns `0` if provided `-infinity`', function test( t ) { + var v = diracDeltaf( NINF ); + t.equal( v, 0.0, 'returns 0' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/test/test.native.js new file mode 100644 index 000000000000..0b62e4645147 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/dirac-deltaf/test/test.native.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var PINF = require( '@stdlib/constants/float32/pinf' ); +var NINF = require( '@stdlib/constants/float32/ninf' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var randu = require( '@stdlib/random/base/randu' ); + + +// VARIABLES // + +var diracDeltaf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( diracDeltaf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof diracDeltaf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `0` if `x` does not equal `0`', opts, function test( t ) { + var x; + var v; + var i; + + for ( i = 0; i < 1e3; i++ ) { + x = ( randu() * 100.0 ) - 50.0; + if ( x === 0.0 ) { + x += EPS; + } + v = diracDeltaf( x ); + t.equal( isPositiveZerof( v ), true, 'returns 0 when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `+infinity` if `x` equals `0`', opts, function test( t ) { + var v = diracDeltaf( 0.0 ); + t.equal( v, PINF, 'returns +infinity' ); + t.end(); +}); + +tape( 'the function returns `NaN` if provided a `NaN`', opts, function test( t ) { + var v = diracDeltaf( NaN ); + t.equal( isnanf( v ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'the function returns `0` if provided `+infinity`', opts, function test( t ) { + var v = diracDeltaf( PINF ); + t.equal( v, 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'the function returns `0` if provided `-infinity`', opts, function test( t ) { + var v = diracDeltaf( NINF ); + t.equal( v, 0.0, 'returns 0' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/falling-factorial/README.md b/lib/node_modules/@stdlib/math/base/special/falling-factorial/README.md index 40a00b3bbd49..565168d0b99c 100644 --- a/lib/node_modules/@stdlib/math/base/special/falling-factorial/README.md +++ b/lib/node_modules/@stdlib/math/base/special/falling-factorial/README.md @@ -81,18 +81,16 @@ v = fallingFactorial( 3.0, -2 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var ceil = require( '@stdlib/math/base/special/ceil' ); +var randu = require( '@stdlib/random/array/uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var fallingFactorial = require( '@stdlib/math/base/special/falling-factorial' ); -var n; -var x; -var i; +var x = randu( 100, -20.0, 20.0 ); +var n = discreteUniform( 100, 0, 20 ); +var i; for ( i = 0; i < 100; i++ ) { - x = ( randu()*40.0 ) - 20.0; - n = ceil( randu()*20.0 ); - console.log( 'fallingFactorial(%d,%d) = %d', x, n, fallingFactorial( x, n ) ); + console.log( 'fallingFactorial(%d,%d) = %d', x[ i ], n[ i ], fallingFactorial( x[ i ], n[ i ] ) ); } ``` diff --git a/lib/node_modules/@stdlib/math/base/special/falling-factorial/examples/index.js b/lib/node_modules/@stdlib/math/base/special/falling-factorial/examples/index.js index 3eb35464d32a..89efce699332 100644 --- a/lib/node_modules/@stdlib/math/base/special/falling-factorial/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/special/falling-factorial/examples/index.js @@ -22,13 +22,10 @@ var randu = require( '@stdlib/random/array/uniform' ); var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var fallingFactorial = require( './../lib' ); -var n; -var x; -var i; - -x = randu( 100, -20.0, 20.0 ); -n = discreteUniform( 100, 0, 20 ); +var x = randu( 100, -20.0, 20.0 ); +var n = discreteUniform( 100, 0, 20 ); +var i; for ( i = 0; i < 100; i++ ) { console.log( 'fallingFactorial(%d,%d) = %d', x[ i ], n[ i ], fallingFactorial( x[ i ], n[ i ] ) ); } diff --git a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md index 07289198dc11..43a3a14918d6 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md +++ b/lib/node_modules/@stdlib/math/base/special/fast/alpha-max-plus-beta-min/README.md @@ -159,12 +159,12 @@ for ( i = 0; i < 100; i++ ) { #include "stdlib/math/base/special/fast/alpha_max_plus_beta_min.h" ``` -#### stdlib_base_fast_ampbm( x, y ) +#### stdlib_base_fast_ampbm( x, y ) Computes the hypotenuse using the alpha max plus beta min algorithm. ```c -double h = stdlib_base_fast_ampbm( -5.0, 12.0 ); +double h = stdlib_base_fast_ampbm( -5.0, 12.0 ); // returns ~13.5 ``` diff --git a/lib/node_modules/@stdlib/math/base/special/fmod/src/main.c b/lib/node_modules/@stdlib/math/base/special/fmod/src/main.c index 201818e1e294..d96defe21bb3 100644 --- a/lib/node_modules/@stdlib/math/base/special/fmod/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/fmod/src/main.c @@ -144,7 +144,7 @@ double stdlib_base_fmod( const double x, const double y ) { if ( n <= 31 ) { hx = ( (uint32_t)hx << n ) | ( lx >> ( 32 - n ) ); lx <<= n; - } else { + } else { hx = lx << ( n - 32 ); lx = 0; } diff --git a/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md b/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md index 1b4954820b2a..40135d3a8aaa 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md +++ b/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md @@ -201,6 +201,12 @@ int main( void ) {
+* * * + +## See Also + +- [`@stdlib/math/base/special/gamma`][@stdlib/math/base/special/gamma]: gamma function. +
diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/README.md b/lib/node_modules/@stdlib/math/base/special/heavisidef/README.md new file mode 100644 index 000000000000..805032c2731f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/README.md @@ -0,0 +1,182 @@ + + +# Heaviside Function + +> Evaluate the [Heaviside function][heaviside-function] for a single-precision floating-point number. + +
+ +The [Heaviside function][heaviside-function] is defined as + + + +```math +H(x) = \begin{cases} 1 & \textrm{if}\ x \gt 0 \\ 0 & \textrm{if}\ x \lt 0\end{cases} +``` + + + + + +and is discontinuous at `0`. Depending on the context, the [Heaviside function][heaviside-function] may be defined as a continuous function. To define the [Heaviside function][heaviside-function] such that the function has rotational symmetry, + + + +```math +H(x) = \begin{cases} x & \textrm{if}\ x \gt 0 \\ \frac{1}{2} & \textrm{if}\ x = 0 \\ 0 & \textrm{if}\ x \lt 0\end{cases} +``` + + + + + +To define the [Heaviside function][heaviside-function] as a left-continuous function, + + + +```math +H(x) = \begin{cases} x & \textrm{if}\ x \gt 0 \\ 0 & \textrm{if}\ x \leq 0\end{cases} +``` + + + + + +To define the [Heaviside function][heaviside-function] as a right-continuous function, + + + +```math +H(x) = \begin{cases} x & \textrm{if}\ x \geq 0 \\ 0 & \textrm{if}\ x \lt 0\end{cases} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var heavisidef = require( '@stdlib/math/base/special/heavisidef' ); +``` + +#### heavisidef( x\[, continuity] ) + +Evaluates the [Heaviside function][heaviside-function] for a single-precision floating-point number. + +```javascript +var v = heavisidef( 3.14 ); +// returns 1.0 + +v = heavisidef( -3.14 ); +// returns 0.0 + +v = heavisidef( NaN ); +// returns NaN +``` + +The `continuity` parameter may be one of the following values: + +- `'half-maximum'`: if `x == 0`, the function returns `0.5`. +- `'left-continuous'`: if `x == 0`, the function returns `0.0`. +- `'right-continuous'`: if `x == 0`, the function returns `1.0`. + +By default, the function is discontinuous at `0`. + +```javascript +var v = heavisidef( 0.0 ); +// returns NaN +``` + +To define the [Heaviside function][heaviside-function] as a continuous function, set the `continuity` parameter. + +```javascript +var v = heavisidef( 0.0, 'half-maximum' ); +// returns 0.5 + +v = heavisidef( 0.0, 'left-continuous' ); +// returns 0.0 + +v = heavisidef( 0.0, 'right-continuous' ); +// returns 1.0 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var linspace = require( '@stdlib/array/base/linspace' ); +var heavisidef = require( '@stdlib/math/base/special/heavisidef' ); + +var x = linspace( -10.0, 10.0, 101 ); + +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( 'H(%d) = %f', x[ i ], heavisidef( x[ i ] ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[heaviside-function]: https://en.wikipedia.org/wiki/Heaviside_step_function + +
+ + diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/heavisidef/benchmark/benchmark.js new file mode 100644 index 000000000000..25e067228472 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pkg = require( './../package.json' ).name; +var heavisidef = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var x; + var y; + var i; + + x = uniform( 100, -50.0, 50.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = heavisidef( x[ i % x.length ] ); + if ( y > 1.0 ) { + b.fail( 'should not return a value greater than 1' ); + } + } + b.toc(); + if ( y > 1.0 ) { + b.fail( 'should not return a value greater than 1' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::left-continuous', function benchmark( b ) { + var x; + var y; + var i; + + x = uniform( 100, -50.0, 50.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = heavisidef( x[ i % x.length ], 'left-continuous' ); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::right-continuous', function benchmark( b ) { + var x; + var y; + var i; + + x = uniform( 100, -50.0, 50.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = heavisidef( x[ i % x.length ], 'right-continuous' ); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::half-maximum', function benchmark( b ) { + var x; + var y; + var i; + + x = uniform( 100, -50.0, 50.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = heavisidef( x[ i % x.length ], 'half-maximum' ); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function.svg b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function.svg new file mode 100644 index 000000000000..2196d674a9b2 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function.svg @@ -0,0 +1,50 @@ + +upper H left-parenthesis x right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column 1 2nd Column if x greater-than 0 2nd Row 1st Column 0 2nd Column if x less-than 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_half_maximum.svg b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_half_maximum.svg new file mode 100644 index 000000000000..1608e3bb4599 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_half_maximum.svg @@ -0,0 +1,74 @@ + +upper H left-parenthesis x right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column x 2nd Column if x greater-than 0 2nd Row 1st Column one-half 2nd Column if x equals 0 3rd Row 1st Column 0 2nd Column if x less-than 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_left_continuous.svg b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_left_continuous.svg new file mode 100644 index 000000000000..3d98435d2174 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_left_continuous.svg @@ -0,0 +1,49 @@ + +upper H left-parenthesis x right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column x 2nd Column if x greater-than 0 2nd Row 1st Column 0 2nd Column if x less-than-or-equal-to 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_right_continuous.svg b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_right_continuous.svg new file mode 100644 index 000000000000..d556954c5554 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/img/equation_heaviside_function_right_continuous.svg @@ -0,0 +1,49 @@ + +upper H left-parenthesis x right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column x 2nd Column if x greater-than-or-equal-to 0 2nd Row 1st Column 0 2nd Column if x less-than 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/repl.txt b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/repl.txt new file mode 100644 index 000000000000..dc072e24045b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/repl.txt @@ -0,0 +1,46 @@ + +{{alias}}( x[, continuity] ) + Evaluates the Heaviside function for a single-precision floating-point + number. + + The `continuity` parameter may be one of the following: + + - 'half-maximum': if `x == 0`, the function returns `0.5`. + - 'left-continuous': if `x == 0`, the function returns `0`. + - 'right-continuous': if `x == 0`, the function returns `1`. + + By default, if `x == 0`, the function returns `NaN` (i.e., the function is + discontinuous). + + Parameters + ---------- + x: number + Input value. + + continuity: string (optional) + Specifies how to handle `x == 0`. By default, if `x == 0`, the function + returns `NaN`. + + Returns + ------- + y: number + Function value. + + Examples + -------- + > var y = {{alias}}( 3.14 ) + 1.0 + > y = {{alias}}( -3.14 ) + 0.0 + > y = {{alias}}( 0.0 ) + NaN + > y = {{alias}}( 0.0, 'half-maximum' ) + 0.5 + > y = {{alias}}( 0.0, 'left-continuous' ) + 0.0 + > y = {{alias}}( 0.0, 'right-continuous' ) + 1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/types/index.d.ts new file mode 100644 index 000000000000..d66b9efa85e0 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/types/index.d.ts @@ -0,0 +1,71 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the Heaviside function for a single-precision floating-point number. +* +* ## Notes +* +* - The `continuity` parameter may be one of the following: +* +* - 'half-maximum': if `x == 0`, the function returns `0.5`. +* - 'left-continuous': if `x == 0`, the function returns `0`. +* - 'right-continuous': if `x == 0`, the function returns `1`. +* +* - By default, if `x == 0`, the function returns `NaN` (i.e., the function is discontinuous). +* +* @param x - input value +* @param continuity - continuity option +* @returns function value +* +* @example +* var v = heavisidef( 3.14 ); +* // returns 1.0 +* +* @example +* var v = heavisidef( -3.14 ); +* // returns 0.0 +* +* @example +* var v = heavisidef( 0.0 ); +* // returns NaN +* +* @example +* var v = heavisidef( 0.0, 'half-maximum' ); +* // returns 0.5 +* +* @example +* var v = heavisidef( 0.0, 'left-continuous' ); +* // returns 0.0 +* +* @example +* var v = heavisidef( 0.0, 'right-continuous' ); +* // returns 1.0 +* +* @example +* var v = heavisidef( NaN ); +* // returns NaN +*/ +declare function heavisidef( x: number, continuity?: 'half-maximum' | 'left-continuous' | 'right-continuous' ): number; + + +// EXPORTS // + +export = heavisidef; diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/types/test.ts new file mode 100644 index 000000000000..822904262069 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import heavisidef = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + heavisidef( 3.141592653589793 ); // $ExpectType number + heavisidef( 0, 'half-maximum' ); // $ExpectType number + heavisidef( 0, 'left-continuous' ); // $ExpectType number + heavisidef( 0, 'right-continuous' ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument other than a number... +{ + heavisidef( true, 'half-maximum' ); // $ExpectError + heavisidef( false, 'half-maximum' ); // $ExpectError + heavisidef( '5', 'half-maximum' ); // $ExpectError + heavisidef( [], 'half-maximum' ); // $ExpectError + heavisidef( {}, 'half-maximum' ); // $ExpectError + heavisidef( ( x: number ): number => x, 'half-maximum' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a value other than `left-continuous`, `left-continuous`, or `half-maximum` as its second argument... +{ + heavisidef( 0, true ); // $ExpectError + heavisidef( 0, false ); // $ExpectError + heavisidef( 0, '5' ); // $ExpectError + heavisidef( 0, 'abc' ); // $ExpectError + heavisidef( 0, [] ); // $ExpectError + heavisidef( 0, {} ); // $ExpectError + heavisidef( 0, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + heavisidef(); // $ExpectError + heavisidef( 3, 'half-maximum', 8 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/examples/index.js b/lib/node_modules/@stdlib/math/base/special/heavisidef/examples/index.js new file mode 100644 index 000000000000..d1dfdcdd1574 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var linspace = require( '@stdlib/array/base/linspace' ); +var heavisidef = require( './../lib' ); + +var x = linspace( -10.0, 10.0, 101 ); + +var i; +for ( i = 0; i < x.length; i++ ) { + console.log( 'H(%d) = %f', x[ i ], heavisidef( x[ i ] ) ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/lib/index.js b/lib/node_modules/@stdlib/math/base/special/heavisidef/lib/index.js new file mode 100644 index 000000000000..74356df2adc6 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/lib/index.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Evaluate the Heaviside function for a single-precision floating-point number. +* +* @module @stdlib/math/base/special/heavisidef +* +* @example +* var heavisidef = require( '@stdlib/math/base/special/heavisidef' ); +* +* var v = heavisidef( 3.14 ); +* // returns 1.0 +* +* v = heavisidef( -3.14 ); +* // returns 0.0 +* +* v = heavisidef( 0.0 ); +* // returns NaN +* +* v = heavisidef( 0.0, 'half-maximum' ); +* // returns 0.5 +* +* v = heavisidef( 0.0, 'left-continuous' ); +* // returns 0.0 +* +* v = heavisidef( 0.0, 'right-continuous' ); +* // returns 1.0 +* +* v = heavisidef( NaN ); +* // returns NaN +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/lib/main.js b/lib/node_modules/@stdlib/math/base/special/heavisidef/lib/main.js new file mode 100644 index 000000000000..247700292d5d --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/lib/main.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); + + +// MAIN // + +/** +* Evaluates the Heaviside function for a single-precision floating-point number. +* +* @param {number} x - input value +* @param {string} [continuity] - continuity option +* @returns {number} function value +* +* @example +* var v = heavisidef( 3.14 ); +* // returns 1.0 +* +* @example +* var v = heavisidef( -3.14 ); +* // returns 0.0 +* +* @example +* var v = heavisidef( 0.0 ); +* // returns NaN +* +* @example +* var v = heavisidef( 0.0, 'half-maximum' ); +* // returns 0.5 +* +* @example +* var v = heavisidef( 0.0, 'left-continuous' ); +* // returns 0.0 +* +* @example +* var v = heavisidef( 0.0, 'right-continuous' ); +* // returns 1.0 +* +* @example +* var v = heavisidef( NaN ); +* // returns NaN +*/ +function heavisidef( x, continuity ) { + if ( isnanf( x ) ) { + return NaN; + } + if ( x > 0.0 ) { + return 1.0; + } + // Handle `+-0`... + if ( x === 0.0 ) { + if ( continuity === 'half-maximum' ) { + return 0.5; + } + if ( continuity === 'left-continuous' ) { + return 0.0; + } + if ( continuity === 'right-continuous' ) { + return 1.0; + } + // Default behavior is discontinuity... + return NaN; + } + return 0.0; +} + + +// EXPORTS // + +module.exports = heavisidef; diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/package.json b/lib/node_modules/@stdlib/math/base/special/heavisidef/package.json new file mode 100644 index 000000000000..21dc66cd1853 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/math/base/special/heavisidef", + "version": "0.0.0", + "description": "Evaluate the Heaviside function for a single-precision floating-point number.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "heavisidef", + "discontinuous", + "unit step function", + "step function", + "distribution", + "dist", + "ramp", + "digital signal processing", + "dsp" + ] +} diff --git a/lib/node_modules/@stdlib/math/base/special/heavisidef/test/test.js b/lib/node_modules/@stdlib/math/base/special/heavisidef/test/test.js new file mode 100644 index 000000000000..0f8e15510704 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/heavisidef/test/test.js @@ -0,0 +1,131 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var PINF = require( '@stdlib/constants/float32/pinf' ); +var NINF = require( '@stdlib/constants/float32/ninf' ); +var EPS = require( '@stdlib/constants/float32/eps' ); +var randu = require( '@stdlib/random/base/randu' ); +var heavisidef = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof heavisidef, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `0` if `x` is negative', function test( t ) { + var x; + var v; + var i; + + for ( i = 0; i < 1e3; i++ ) { + x = -( randu()*100.0 ) - EPS; + v = heavisidef( x ); + t.equal( isPositiveZerof( v ), true, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'the function returns `1` if `x` is positive', function test( t ) { + var x; + var v; + var i; + + for ( i = 0; i < 1e3; i++ ) { + x = ( randu()*100.0 ) + EPS; + v = heavisidef( x ); + t.equal( v, 1.0, 'returns expected value when provided '+x ); + } + t.end(); +}); + +tape( 'by default, the function returns `NaN` if provided `+-0`', function test( t ) { + var v; + + v = heavisidef( -0.0 ); + t.equal( isnanf( v ), true, 'returns expected value' ); + + v = heavisidef( +0.0 ); + t.equal( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if the `continuity` option is `half-maximum`, the function returns `0.5` if provided `+-0`', function test( t ) { + var v; + + v = heavisidef( -0.0, 'half-maximum' ); + t.equal( v, 0.5, 'returns expected value' ); + + v = heavisidef( +0.0, 'half-maximum' ); + t.equal( v, 0.5, 'returns expected value' ); + + t.end(); +}); + +tape( 'if the `continuity` option is `left-continuous`, the function returns `0.0` if provided `+-0`', function test( t ) { + var v; + + v = heavisidef( -0.0, 'left-continuous' ); + t.equal( isPositiveZerof( v ), true, 'returns expected value' ); + + v = heavisidef( +0.0, 'left-continuous' ); + t.equal( isPositiveZerof( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if the `continuity` option is `right-continuous`, the function returns `1` if provided `+-0`', function test( t ) { + var v; + + v = heavisidef( -0.0, 'right-continuous' ); + t.equal( v, 1.0, 'returns expected value' ); + + v = heavisidef( +0.0, 'right-continuous' ); + t.equal( v, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { + var v = heavisidef( NaN ); + t.equal( isnanf( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `0` if provided `-infinity`', function test( t ) { + var v = heavisidef( NINF ); + t.equal( v, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `+1` if provided `+infinity`', function test( t ) { + var v = heavisidef( PINF ); + t.equal( v, 1.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/README.md b/lib/node_modules/@stdlib/math/base/special/hypot/README.md index f7dd7e3239d6..544978fdf947 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/README.md +++ b/lib/node_modules/@stdlib/math/base/special/hypot/README.md @@ -119,20 +119,16 @@ h = hypot( 5.0, NaN ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var hypot = require( '@stdlib/math/base/special/hypot' ); -var x; -var y; -var h; -var i; +var len = 100; +var x = discreteUniform( len, -50, 50 ); +var y = discreteUniform( len, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = round( randu()*100.0 ) - 50.0; - y = round( randu()*100.0 ) - 50.0; - h = hypot( x, y ); - console.log( 'h(%d,%d) = %d', x, y, h ); +var i; +for ( i = 0; i < len; i++ ) { + console.log( 'h(%d,%d) = %d', x[ i ], y[ i ], hypot( x[ i ], y[ i ] ) ); } ``` diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.js index 1ad88a69b8d4..0649d486ad90 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.js @@ -21,8 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var uniform = require( '@stdlib/random/array/uniform' ); var pkg = require( './../package.json' ).name; var hypot = require( './../lib' ); @@ -37,16 +37,19 @@ var opts = { // MAIN // bench( pkg, function benchmark( b ) { + var len; var x; var y; var z; var i; + len = 100; + x = uniform( len, -50, 50 ); + y = uniform( len, -50, 50 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - y = ( randu()*100.0 ) - 50.0; - z = hypot( x, y ); + z = hypot( x[ i % len ], y[ i % len ] ); if ( isnan( z ) ) { b.fail( 'should not return NaN' ); } @@ -60,16 +63,19 @@ bench( pkg, function benchmark( b ) { }); bench( pkg+'::built-in', opts, function benchmark( b ) { + var len; var x; var y; var z; var i; + len = 100; + x = uniform( len, -50, 50 ); + y = uniform( len, -50, 50 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - y = ( randu()*100.0 ) - 50.0; - z = Math.hypot( x, y ); // eslint-disable-line stdlib/no-builtin-math + z = Math.hypot( x[ i % len ], y[ i % len ] ); // eslint-disable-line stdlib/no-builtin-math if ( isnan( z ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.native.js index a8dfef48eca9..530480ddcdf4 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/benchmark.native.js @@ -22,8 +22,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var uniform = require( '@stdlib/random/array/uniform' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -39,16 +39,19 @@ var opts = { // MAIN // bench( pkg+'::native', opts, function benchmark( b ) { + var len; var x; var y; var z; var i; + len = 100; + x = uniform( len, -50, 50 ); + y = uniform( len, -50, 50 ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - y = ( randu()*100.0 ) - 50.0; - z = hypot( x, y ); + z = hypot( x[ i % len ], y[ i % len ] ); if ( isnan( z ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/c/native/benchmark.c index ac9a91e3ddcf..4355b034728e 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/special/hypot/benchmark/c/native/benchmark.c @@ -91,17 +91,20 @@ static double rand_double( void ) { */ static double benchmark( void ) { double elapsed; - double x; - double y; + double x[ 100 ]; + double y[ 100 ]; double z; double t; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = ( rand_double() * 100.0 ) - 50.0; + y[ i ] = ( rand_double() * 100.0 ) - 50.0; + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( 100.0*rand_double() ) - 50.0; - y = ( 100.0*rand_double() ) - 50.0; - z = stdlib_base_hypot( x, y ); + z = stdlib_base_hypot( x[ i % 100 ], y[ i % 100 ] ); if ( z != z ) { printf( "should not return NaN\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/examples/index.js b/lib/node_modules/@stdlib/math/base/special/hypot/examples/index.js index 51bd0803d70e..2a1bff6903b3 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/special/hypot/examples/index.js @@ -18,18 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var hypot = require( './../lib' ); -var x; -var y; -var h; -var i; +var len = 100; +var x = discreteUniform( len, -50, 50 ); +var y = discreteUniform( len, -50, 50 ); -for ( i = 0; i < 100; i++ ) { - x = round( randu()*100.0 ) - 50.0; - y = round( randu()*100.0 ) - 50.0; - h = hypot( x, y ); - console.log( 'h(%d,%d) = %d', x, y, h ); +var i; +for ( i = 0; i < len; i++ ) { + console.log( 'h(%d,%d) = %d', x[ i ], y[ i ], hypot( x[ i ], y[ i ] ) ); } diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json b/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json index 33c41d36613f..755db550a9d9 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json @@ -28,7 +28,7 @@ { "task": "build", "src": [ - "./src/hypot.c" + "./src/main.c" ], "include": [ "./include" @@ -41,13 +41,14 @@ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/constants/float64/pinf" ] }, { "task": "benchmark", "src": [ - "./src/hypot.c" + "./src/main.c" ], "include": [ "./include" @@ -59,13 +60,14 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/constants/float64/pinf" ] }, { "task": "examples", "src": [ - "./src/hypot.c" + "./src/main.c" ], "include": [ "./include" @@ -77,7 +79,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/special/sqrt" + "@stdlib/math/base/special/sqrt", + "@stdlib/constants/float64/pinf" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/src/hypot.c b/lib/node_modules/@stdlib/math/base/special/hypot/src/hypot.c deleted file mode 100644 index 58a77e970c42..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/hypot/src/hypot.c +++ /dev/null @@ -1,64 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2018 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/hypot.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_infinite.h" -#include "stdlib/math/base/special/sqrt.h" -#include - -/** -* Computes the hypotenuse avoiding overflow and underflow. -* -* @param x number -* @param y number -* @return hypotenuse -* -* @example -* double h = stdlib_base_hypot( 5.0, 12.0 ); -* // returns 13.0 -*/ -double stdlib_base_hypot( const double x, const double y ) { - double tmp; - double a; - double b; - if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0 / 0.0; // NaN - } - if ( stdlib_base_is_infinite( x ) || stdlib_base_is_infinite( y ) ) { - return HUGE_VAL; - } - a = x; - b = y; - if ( a < 0.0 ) { - a = -a; - } - if ( b < 0.0 ) { - b = -b; - } - if ( a < b ) { - tmp = b; - b = a; - a = tmp; - } - if ( a == 0.0 ) { - return 0.0; - } - b /= a; - return a * stdlib_base_sqrt( 1.0 + (b*b) ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c b/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c new file mode 100644 index 000000000000..11ba026d6247 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/hypot.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_infinite.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/constants/float64/pinf.h" + +/** +* Computes the hypotenuse avoiding overflow and underflow. +* +* @param x number +* @param y number +* @return hypotenuse +* +* @example +* double h = stdlib_base_hypot( 5.0, 12.0 ); +* // returns 13.0 +*/ +double stdlib_base_hypot( const double x, const double y ) { + double tmp; + double a; + double b; + if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { + return 0.0 / 0.0; // NaN + } + if ( stdlib_base_is_infinite( x ) || stdlib_base_is_infinite( y ) ) { + return STDLIB_CONSTANT_FLOAT64_PINF; + } + a = x; + b = y; + if ( a < 0.0 ) { + a = -a; + } + if ( b < 0.0 ) { + b = -b; + } + if ( a < b ) { + tmp = b; + b = a; + a = tmp; + } + if ( a == 0.0 ) { + return 0.0; + } + b /= a; + return a * stdlib_base_sqrt( 1.0 + ( b * b ) ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/test/test.js b/lib/node_modules/@stdlib/math/base/special/hypot/test/test.js index 7e88764fab65..122526efbd49 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/hypot/test/test.js @@ -49,28 +49,28 @@ tape( 'the function returns `+infinity` if either argument is `+-infinity`', fun var h; h = hypot( PINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( 3.14, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( NINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( 3.14, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( PINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( NINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( PINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( NINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); t.end(); }); @@ -79,13 +79,13 @@ tape( 'the function returns `NaN` if either argument is `NaN`', function test( t var h; h = hypot( NaN, 3.14 ); - t.strictEqual( isnan( h ), true, 'returns NaN' ); + t.strictEqual( isnan( h ), true, 'returns expected value' ); h = hypot( 3.14, NaN ); - t.strictEqual( isnan( h ), true, 'returns NaN' ); + t.strictEqual( isnan( h ), true, 'returns expected value' ); h = hypot( NaN, NaN ); - t.strictEqual( isnan( h ), true, 'returns NaN' ); + t.strictEqual( isnan( h ), true, 'returns expected value' ); t.end(); }); @@ -94,16 +94,16 @@ tape( 'the function returns `+0` if both arguments are `+-0`', function test( t var h; h = hypot( +0.0, +0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); h = hypot( -0.0, +0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); h = hypot( +0.0, -0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); h = hypot( -0.0, -0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); t.end(); }); @@ -138,13 +138,13 @@ tape( 'the function computes the hypotenuse (canonical inputs)', function test( var h; h = hypot( 3.0, 4.0 ); - t.strictEqual( h, 5.0, 'returns 5.0' ); + t.strictEqual( h, 5.0, 'returns expected value' ); h = hypot( 6.0, 8.0 ); - t.strictEqual( h, 10.0, 'returns 10.0' ); + t.strictEqual( h, 10.0, 'returns expected value' ); h = hypot( 5.0, 12.0 ); - t.strictEqual( h, 13.0, 'returns 13.0' ); + t.strictEqual( h, 13.0, 'returns expected value' ); t.end(); }); @@ -153,7 +153,7 @@ tape( 'the function avoids overflow', function test( t ) { var h; h = sqrt( pow( 1.0e308, 2 ) + pow( 1.0e308, 2 ) ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( 1.0e308, 1.0e308 ); t.strictEqual( h, 1.4142135623730951e308, 'avoids overflow' ); diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/hypot/test/test.native.js index 24d1c02f6219..575e0db62023 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/hypot/test/test.native.js @@ -58,28 +58,28 @@ tape( 'the function returns `+infinity` if either argument is `+-infinity`', opt var h; h = hypot( PINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( 3.14, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( NINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( 3.14, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( PINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( NINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( PINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( NINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); t.end(); }); @@ -88,13 +88,13 @@ tape( 'the function returns `NaN` if either argument is `NaN`', opts, function t var h; h = hypot( NaN, 3.14 ); - t.strictEqual( isnan( h ), true, 'returns NaN' ); + t.strictEqual( isnan( h ), true, 'returns expected value' ); h = hypot( 3.14, NaN ); - t.strictEqual( isnan( h ), true, 'returns NaN' ); + t.strictEqual( isnan( h ), true, 'returns expected value' ); h = hypot( NaN, NaN ); - t.strictEqual( isnan( h ), true, 'returns NaN' ); + t.strictEqual( isnan( h ), true, 'returns expected value' ); t.end(); }); @@ -103,16 +103,16 @@ tape( 'the function returns `+0` if both arguments are `+-0`', opts, function te var h; h = hypot( +0.0, +0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); h = hypot( -0.0, +0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); h = hypot( +0.0, -0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); h = hypot( -0.0, -0.0 ); - t.strictEqual( isPositiveZero( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZero( h ), true, 'returns expected value' ); t.end(); }); @@ -147,13 +147,13 @@ tape( 'the function computes the hypotenuse (canonical inputs)', opts, function var h; h = hypot( 3.0, 4.0 ); - t.strictEqual( h, 5.0, 'returns 5.0' ); + t.strictEqual( h, 5.0, 'returns expected value' ); h = hypot( 6.0, 8.0 ); - t.strictEqual( h, 10.0, 'returns 10.0' ); + t.strictEqual( h, 10.0, 'returns expected value' ); h = hypot( 5.0, 12.0 ); - t.strictEqual( h, 13.0, 'returns 13.0' ); + t.strictEqual( h, 13.0, 'returns expected value' ); t.end(); }); @@ -162,7 +162,7 @@ tape( 'the function avoids overflow', opts, function test( t ) { var h; h = sqrt( pow( 1.0e308, 2 ) + pow( 1.0e308, 2 ) ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypot( 1.0e308, 1.0e308 ); t.strictEqual( h, 1.4142135623730951e308, 'avoids overflow' ); diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/README.md b/lib/node_modules/@stdlib/math/base/special/hypotf/README.md index 906d3e561914..facf49747c08 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/README.md @@ -83,20 +83,19 @@ h = hypotf( 5.0, NaN ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var hypotf = require( '@stdlib/math/base/special/hypotf' ); -var x; -var y; -var h; -var i; +var len = 100; +var opts = { + 'dtype': 'float32' +}; +var x = discreteUniform( len, -50, 50, opts ); +var y = discreteUniform( len, -50, 50, opts ); -for ( i = 0; i < 100; i++ ) { - x = round( randu()*100.0 ) - 50.0; - y = round( randu()*100.0 ) - 50.0; - h = hypotf( x, y ); - console.log( 'h(%d,%d) = %d', x, y, h ); +var i; +for ( i = 0; i < len; i++ ) { + console.log( 'h(%d,%d) = %d', x[ i ], y[ i ], hypotf( x[ i ], y[ i ] ) ); } ``` diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.js index dffda0f39e6c..feb4a9a9cf44 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pkg = require( './../package.json' ).name; var hypotf = require( './../lib' ); @@ -37,16 +37,24 @@ var opts = { // MAIN // bench( pkg, function benchmark( b ) { + var opts; + var len; var x; var y; var z; var i; + opts = { + 'dtype': 'float32' + }; + + len = 100; + x = uniform( len, -50, 50, opts ); + y = uniform( len, -50, 50, opts ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - y = ( randu()*100.0 ) - 50.0; - z = hypotf( x, y ); + z = hypotf( x[ i % len ], y[ i % len ] ); if ( isnanf( z ) ) { b.fail( 'should not return NaN' ); } @@ -60,16 +68,24 @@ bench( pkg, function benchmark( b ) { }); bench( pkg+'::built-in', opts, function benchmark( b ) { + var opts; + var len; var x; var y; var z; var i; + opts = { + 'dtype': 'float32' + }; + + len = 100; + x = uniform( len, -50, 50, opts ); + y = uniform( len, -50, 50, opts ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - y = ( randu()*100.0 ) - 50.0; - z = Math.hypot( x, y ); // eslint-disable-line stdlib/no-builtin-math + z = Math.hypot( x[ i % len ], y[ i % len ] ); // eslint-disable-line stdlib/no-builtin-math if ( isnanf( z ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.native.js index b0caa25454c4..32aa166d8f34 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -39,16 +39,24 @@ var opts = { // MAIN // bench( pkg+'::native', opts, function benchmark( b ) { + var opts; + var len; var x; var y; var z; var i; + opts = { + 'dtype': 'float32' + }; + + len = 100; + x = uniform( len, -50, 50, opts ); + y = uniform( len, -50, 50, opts ); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - y = ( randu()*100.0 ) - 50.0; - z = hypotf( x, y ); + z = hypotf( x[ i % len ], y[ i % len ] ); if ( isnanf( z ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/c/native/benchmark.c index bd87f27631f2..b5190aa3e6a8 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/c/native/benchmark.c +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/benchmark/c/native/benchmark.c @@ -92,16 +92,19 @@ static float rand_float( void ) { static double benchmark( void ) { double elapsed; double t; - float x; - float y; + float x[ 100 ]; + float y[ 100 ]; float z; int i; + for ( i = 0; i < 100; i++ ) { + x[ i ] = ( 100.0f * rand_float() ) - 50.0f; + y[ i ] = ( 100.0f * rand_float() ) - 50.0f; + } + t = tic(); for ( i = 0; i < ITERATIONS; i++ ) { - x = ( 100.0f*rand_float() ) - 50.0f; - y = ( 100.0f*rand_float() ) - 50.0f; - z = stdlib_base_hypotf( x, y ); + z = stdlib_base_hypotf( x[ i % 100 ], y[ i % 100 ] ); if ( z != z ) { printf( "should not return NaN\n" ); break; diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/examples/index.js b/lib/node_modules/@stdlib/math/base/special/hypotf/examples/index.js index 62ee757ca55e..31abb3480876 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/examples/index.js +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/examples/index.js @@ -18,18 +18,17 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var hypotf = require( './../lib' ); -var x; -var y; -var h; -var i; +var len = 100; +var opts = { + 'dtype': 'float32' +}; +var x = discreteUniform( len, -50, 50, opts ); +var y = discreteUniform( len, -50, 50, opts ); -for ( i = 0; i < 100; i++ ) { - x = round( randu()*100.0 ) - 50.0; - y = round( randu()*100.0 ) - 50.0; - h = hypotf( x, y ); - console.log( 'h(%d,%d) = %d', x, y, h ); +var i; +for ( i = 0; i < len; i++ ) { + console.log( 'h(%d,%d) = %d', x[ i ], y[ i ], hypotf( x[ i ], y[ i ] ) ); } diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/manifest.json b/lib/node_modules/@stdlib/math/base/special/hypotf/manifest.json index d7b2bc5b8414..a88451e865fa 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/manifest.json @@ -1,84 +1,87 @@ { - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/hypotf.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nanf", - "@stdlib/math/base/assert/is-infinitef", - "@stdlib/math/base/special/sqrtf" - ] - }, - { - "task": "benchmark", - "src": [ - "./src/hypotf.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nanf", - "@stdlib/math/base/assert/is-infinitef", - "@stdlib/math/base/special/sqrtf" - ] - }, - { - "task": "examples", - "src": [ - "./src/hypotf.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nanf", - "@stdlib/math/base/assert/is-infinitef", - "@stdlib/math/base/special/sqrtf" - ] - } - ] + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-infinitef", + "@stdlib/math/base/special/sqrtf", + "@stdlib/constants/float32/pinf" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-infinitef", + "@stdlib/math/base/special/sqrtf", + "@stdlib/constants/float32/pinf" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [ + "-lm" + ], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-infinitef", + "@stdlib/math/base/special/sqrtf", + "@stdlib/constants/float32/pinf" + ] + } + ] } diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/src/hypotf.c b/lib/node_modules/@stdlib/math/base/special/hypotf/src/hypotf.c deleted file mode 100644 index 23820dca5311..000000000000 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/src/hypotf.c +++ /dev/null @@ -1,64 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/math/base/special/hypotf.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include "stdlib/math/base/assert/is_infinitef.h" -#include "stdlib/math/base/special/sqrtf.h" -#include - -/** -* Computes the hypotenuse avoiding overflow and underflow (single-precision). -* -* @param x number -* @param y number -* @return hypotenuse -* -* @example -* float h = stdlib_base_hypotf( 5.0f, 12.0f ); -* // returns 13.0 -*/ -float stdlib_base_hypotf( const float x, const float y ) { - float tmp; - float a; - float b; - if ( stdlib_base_is_nanf( x ) || stdlib_base_is_nanf( y ) ) { - return 0.0f / 0.0f; // NaN - } - if ( stdlib_base_is_infinitef( x ) || stdlib_base_is_infinitef( y ) ) { - return INFINITY; - } - a = x; - b = y; - if ( a < 0.0f ) { - a = -a; - } - if ( b < 0.0f ) { - b = -b; - } - if ( a < b ) { - tmp = b; - b = a; - a = tmp; - } - if ( a == 0.0f ) { - return 0.0f; - } - b /= a; - return a * stdlib_base_sqrtf( 1.0f + (b*b) ); -} diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/src/main.c b/lib/node_modules/@stdlib/math/base/special/hypotf/src/main.c new file mode 100644 index 000000000000..c8b34f785e09 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/src/main.c @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/hypotf.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/assert/is_infinitef.h" +#include "stdlib/math/base/special/sqrtf.h" +#include "stdlib/constants/float32/pinf.h" + +/** +* Computes the hypotenuse avoiding overflow and underflow (single-precision). +* +* @param x number +* @param y number +* @return hypotenuse +* +* @example +* float h = stdlib_base_hypotf( 5.0f, 12.0f ); +* // returns 13.0 +*/ +float stdlib_base_hypotf( const float x, const float y ) { + float tmp; + float a; + float b; + if ( stdlib_base_is_nanf( x ) || stdlib_base_is_nanf( y ) ) { + return 0.0f / 0.0f; // NaN + } + if ( stdlib_base_is_infinitef( x ) || stdlib_base_is_infinitef( y ) ) { + return STDLIB_CONSTANT_FLOAT32_PINF; + } + a = x; + b = y; + if ( a < 0.0f ) { + a = -a; + } + if ( b < 0.0f ) { + b = -b; + } + if ( a < b ) { + tmp = b; + b = a; + a = tmp; + } + if ( a == 0.0f ) { + return 0.0f; + } + b /= a; + return a * stdlib_base_sqrtf( 1.0f + ( b * b ) ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.js b/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.js index 194261e04dda..73ba408de3bf 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.js @@ -26,7 +26,7 @@ var PINF = require( '@stdlib/constants/float32/pinf' ); var NINF = require( '@stdlib/constants/float32/ninf' ); var EPS = require( '@stdlib/constants/float32/eps' ); var absf = require( '@stdlib/math/base/special/absf' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var sqrtf = require( '@stdlib/math/base/special/sqrtf' ); var pow = require( '@stdlib/math/base/special/pow' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); @@ -50,28 +50,28 @@ tape( 'the function returns `+infinity` if either argument is `+-infinity`', fun var h; h = hypotf( PINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( 3.14, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( NINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( 3.14, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( PINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( NINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( PINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( NINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); t.end(); }); @@ -80,13 +80,13 @@ tape( 'the function returns `NaN` if either argument is `NaN`', function test( t var h; h = hypotf( NaN, 3.14 ); - t.strictEqual( isnanf( h ), true, 'returns NaN' ); + t.strictEqual( isnanf( h ), true, 'returns expected value' ); h = hypotf( 3.14, NaN ); - t.strictEqual( isnanf( h ), true, 'returns NaN' ); + t.strictEqual( isnanf( h ), true, 'returns expected value' ); h = hypotf( NaN, NaN ); - t.strictEqual( isnanf( h ), true, 'returns NaN' ); + t.strictEqual( isnanf( h ), true, 'returns expected value' ); t.end(); }); @@ -95,16 +95,16 @@ tape( 'the function returns `+0` if both arguments are `+-0`', function test( t var h; h = hypotf( +0.0, +0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); h = hypotf( -0.0, +0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); h = hypotf( +0.0, -0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); h = hypotf( -0.0, -0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); t.end(); }); @@ -139,13 +139,13 @@ tape( 'the function computes the hypotenuse (canonical inputs)', function test( var h; h = hypotf( 3.0, 4.0 ); - t.strictEqual( h, 5.0, 'returns 5.0' ); + t.strictEqual( h, 5.0, 'returns expected value' ); h = hypotf( 6.0, 8.0 ); - t.strictEqual( h, 10.0, 'returns 10.0' ); + t.strictEqual( h, 10.0, 'returns expected value' ); h = hypotf( 5.0, 12.0 ); - t.strictEqual( h, 13.0, 'returns 13.0' ); + t.strictEqual( h, 13.0, 'returns expected value' ); t.end(); }); @@ -153,7 +153,7 @@ tape( 'the function computes the hypotenuse (canonical inputs)', function test( tape( 'the function avoids overflow', function test( t ) { var h; - h = float64ToFloat32( sqrt( float64ToFloat32( float64ToFloat32( pow( 1.0e38, 2 ) ) + float64ToFloat32( pow( 1.0e38, 2 ) ) ) ) ); // eslint-disable-line max-len + h = sqrtf( float64ToFloat32( float64ToFloat32( pow( 1.0e38, 2 ) ) + float64ToFloat32( pow( 1.0e38, 2 ) ) ) ); // eslint-disable-line max-len t.strictEqual( h, PINF, 'returns +infinity' ); h = hypotf( 1.0e38, 1.0e38 ); @@ -165,7 +165,7 @@ tape( 'the function avoids overflow', function test( t ) { tape( 'the function avoids underflow', function test( t ) { var h; - h = float64ToFloat32( sqrt( float64ToFloat32( float64ToFloat32( pow( 1.0e-45, 2 ) ) + float64ToFloat32( pow( 1.0e-45, 2 ) ) ) ) ); // eslint-disable-line max-len + h = sqrtf( float64ToFloat32( float64ToFloat32( pow( 1.0e-45, 2 ) ) + float64ToFloat32( pow( 1.0e-45, 2 ) ) ) ); // eslint-disable-line max-len t.strictEqual( h, 0.0, 'returns 0' ); h = hypotf( 1.0e-45, 1.0e-45 ); diff --git a/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.native.js index d6fc91d9c5f5..aa9efd5a15b6 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/hypotf/test/test.native.js @@ -27,7 +27,7 @@ var PINF = require( '@stdlib/constants/float32/pinf' ); var NINF = require( '@stdlib/constants/float32/ninf' ); var EPS = require( '@stdlib/constants/float32/eps' ); var absf = require( '@stdlib/math/base/special/absf' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var sqrtf = require( '@stdlib/math/base/special/sqrtf' ); var pow = require( '@stdlib/math/base/special/pow' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); @@ -59,28 +59,28 @@ tape( 'the function returns `+infinity` if either argument is `+-infinity`', opt var h; h = hypotf( PINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( 3.14, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( NINF, 3.14 ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( 3.14, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( PINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( NINF, PINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( PINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); h = hypotf( NINF, NINF ); - t.strictEqual( h, PINF, 'returns +infinity' ); + t.strictEqual( h, PINF, 'returns expected value' ); t.end(); }); @@ -89,13 +89,13 @@ tape( 'the function returns `NaN` if either argument is `NaN`', opts, function t var h; h = hypotf( NaN, 3.14 ); - t.strictEqual( isnanf( h ), true, 'returns NaN' ); + t.strictEqual( isnanf( h ), true, 'returns expected value' ); h = hypotf( 3.14, NaN ); - t.strictEqual( isnanf( h ), true, 'returns NaN' ); + t.strictEqual( isnanf( h ), true, 'returns expected value' ); h = hypotf( NaN, NaN ); - t.strictEqual( isnanf( h ), true, 'returns NaN' ); + t.strictEqual( isnanf( h ), true, 'returns expected value' ); t.end(); }); @@ -104,16 +104,16 @@ tape( 'the function returns `+0` if both arguments are `+-0`', opts, function te var h; h = hypotf( +0.0, +0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); h = hypotf( -0.0, +0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); h = hypotf( +0.0, -0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); h = hypotf( -0.0, -0.0 ); - t.strictEqual( isPositiveZerof( h ), true, 'returns +0' ); + t.strictEqual( isPositiveZerof( h ), true, 'returns expected value' ); t.end(); }); @@ -137,7 +137,7 @@ tape( 'the function computes the hypotenuse', opts, function test( t ) { t.ok( true, 'x: '+x[i]+'. y: '+y[i]+'. h: '+h+'. Expected: '+expected[i]+'.' ); } else { delta = absf( h - expected[ i ] ); - tol = 1.4 * EPS * absf( expected[ i ] ); + tol = 2.0 * EPS * absf( expected[ i ] ); t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y[i]+'. h: '+h+'. Expected: '+expected[i]+'. Delta: '+delta+'. Tol: '+tol+'.' ); } } @@ -148,13 +148,13 @@ tape( 'the function computes the hypotenuse (canonical inputs)', opts, function var h; h = hypotf( 3.0, 4.0 ); - t.strictEqual( h, 5.0, 'returns 5.0' ); + t.strictEqual( h, 5.0, 'returns expected value' ); h = hypotf( 6.0, 8.0 ); - t.strictEqual( h, 10.0, 'returns 10.0' ); + t.strictEqual( h, 10.0, 'returns expected value' ); h = hypotf( 5.0, 12.0 ); - t.strictEqual( h, 13.0, 'returns 13.0' ); + t.strictEqual( h, 13.0, 'returns expected value' ); t.end(); }); @@ -162,7 +162,7 @@ tape( 'the function computes the hypotenuse (canonical inputs)', opts, function tape( 'the function avoids overflow', opts, function test( t ) { var h; - h = float64ToFloat32( sqrt( float64ToFloat32( float64ToFloat32( pow( 1.0e38, 2 ) ) + float64ToFloat32( pow( 1.0e38, 2 ) ) ) ) ); // eslint-disable-line max-len + h = sqrtf( float64ToFloat32( float64ToFloat32( pow( 1.0e38, 2 ) ) + float64ToFloat32( pow( 1.0e38, 2 ) ) ) ); // eslint-disable-line max-len t.strictEqual( h, PINF, 'returns +infinity' ); h = hypotf( 1.0e38, 1.0e38 ); @@ -174,7 +174,7 @@ tape( 'the function avoids overflow', opts, function test( t ) { tape( 'the function avoids underflow', opts, function test( t ) { var h; - h = float64ToFloat32( sqrt( float64ToFloat32( float64ToFloat32( pow( 1.0e-45, 2 ) ) + float64ToFloat32( pow( 1.0e-45, 2 ) ) ) ) ); // eslint-disable-line max-len + h = sqrtf( float64ToFloat32( float64ToFloat32( pow( 1.0e-45, 2 ) ) + float64ToFloat32( pow( 1.0e-45, 2 ) ) ) ); // eslint-disable-line max-len t.strictEqual( h, 0.0, 'returns 0' ); h = hypotf( 1.0e-45, 1.0e-45 ); diff --git a/lib/node_modules/@stdlib/math/base/tools/normhermitepoly/README.md b/lib/node_modules/@stdlib/math/base/tools/normhermitepoly/README.md index ea7147817c1c..07cf8dd41de9 100644 --- a/lib/node_modules/@stdlib/math/base/tools/normhermitepoly/README.md +++ b/lib/node_modules/@stdlib/math/base/tools/normhermitepoly/README.md @@ -170,7 +170,7 @@ logEach( 'He_%d(%.3f) = %.3f', 3, x, y ); ## See Also -- [`@stdlib/math/base/tools/evalpoly`][@stdlib/math/base/tools/evalpoly]: evaluate a polynomial. +- [`@stdlib/math/base/tools/evalpoly`][@stdlib/math/base/tools/evalpoly]: evaluate a polynomial using double-precision floating-point arithmetic. - [`@stdlib/math/base/tools/hermitepoly`][@stdlib/math/base/tools/hermitepoly]: evaluate a physicist's Hermite polynomial. diff --git a/lib/node_modules/@stdlib/math/iter/special/log/README.md b/lib/node_modules/@stdlib/math/iter/special/log/README.md index 228500dd99fd..b83ecff7598f 100644 --- a/lib/node_modules/@stdlib/math/iter/special/log/README.md +++ b/lib/node_modules/@stdlib/math/iter/special/log/README.md @@ -166,7 +166,7 @@ while ( true ) { ## See Also -- [`@stdlib/math/base/special/log`][@stdlib/math/base/special/log]: base `b` logarithm. +- [`@stdlib/math/base/special/log`][@stdlib/math/base/special/log]: compute the base `b` logarithm of a double-precision floating-point number. - [`@stdlib/math/iter/special/log10`][@stdlib/math/iter/special/log10]: create an iterator which evaluates the common logarithm (logarithm with base 10) for each iterated value. - [`@stdlib/math/iter/special/log1p`][@stdlib/math/iter/special/log1p]: create an iterator which evaluates the natural logarithm of 1+x for each iterated value. - [`@stdlib/math/iter/special/log2`][@stdlib/math/iter/special/log2]: create an iterator which evaluates the binary logarithm for each iterated value. diff --git a/lib/node_modules/@stdlib/math/iter/tools/map/README.md b/lib/node_modules/@stdlib/math/iter/tools/map/README.md index da591e1928d1..20b9c3d033e8 100644 --- a/lib/node_modules/@stdlib/math/iter/tools/map/README.md +++ b/lib/node_modules/@stdlib/math/iter/tools/map/README.md @@ -70,7 +70,7 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the The invoked `function` is provided one argument: -- `value`: iterated value +- `value`: iterated value. ```javascript var array2iterator = require( '@stdlib/array/to-iterator' ); diff --git a/lib/node_modules/@stdlib/math/strided/special/atanh-by/README.md b/lib/node_modules/@stdlib/math/strided/special/atanh-by/README.md index ac25191f9c57..f8dd40771ddf 100644 --- a/lib/node_modules/@stdlib/math/strided/special/atanh-by/README.md +++ b/lib/node_modules/@stdlib/math/strided/special/atanh-by/README.md @@ -229,6 +229,12 @@ console.log( y );
+* * * + +## See Also + +- [`@stdlib/math/strided/special/atan-by`][@stdlib/math/strided/special/atan-by]: compute the arctangent of each element retrieved from an input strided array via a callback function. +
@@ -243,6 +249,12 @@ console.log( y ); [@stdlib/math/base/special/atanh]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/atanh + + +[@stdlib/math/strided/special/atan-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/strided/special/atan-by + + + diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 6e75dc2077a8..6ffe99797014 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1038,8 +1038,8 @@ base.strided.daxpy,"@stdlib/blas/base/daxpy" base.strided.dcbrt,"@stdlib/math/strided/special/dcbrt" base.strided.dceil,"@stdlib/math/strided/special/dceil" base.strided.dcopy,"@stdlib/blas/base/dcopy" -base.strided.dcumax,"@stdlib/stats/base/dcumax" -base.strided.dcumaxabs,"@stdlib/stats/base/dcumaxabs" +base.strided.dcumax,"@stdlib/stats/strided/dcumax" +base.strided.dcumaxabs,"@stdlib/stats/strided/dcumaxabs" base.strided.dcumin,"@stdlib/stats/base/dcumin" base.strided.dcuminabs,"@stdlib/stats/base/dcuminabs" base.strided.dcusum,"@stdlib/blas/ext/base/dcusum" @@ -1054,7 +1054,7 @@ base.strided.dfloor,"@stdlib/math/strided/special/dfloor" base.strided.dinv,"@stdlib/math/strided/special/dinv" base.strided.dmap,"@stdlib/strided/base/dmap" base.strided.dmap2,"@stdlib/strided/base/dmap2" -base.strided.dmax,"@stdlib/stats/base/dmax" +base.strided.dmax,"@stdlib/stats/strided/dmax" base.strided.dmaxabs,"@stdlib/stats/base/dmaxabs" base.strided.dmaxabssorted,"@stdlib/stats/base/dmaxabssorted" base.strided.dmaxsorted,"@stdlib/stats/base/dmaxsorted" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index d3c966066572..7a9217d86696 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ 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ognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdlib/stats/base/dists/normal/entropy","base.dists.normal.kurtosis":"@stdlib/stats/base/dists/normal/kurtosis","base.dists.normal.logcdf":"@stdlib/stats/base/dists/normal/logcdf","base.dists.normal.logpdf":"@stdlib/stats/base/dists/normal/logpdf","base.dists.normal.mean":"@stdlib/stats/base/dists/normal/mean","base.dists.normal.median":"@stdlib/stats/base/dists/normal/median","base.dists.normal.mgf":"@stdlib/stats/base/dists/normal/mgf","base.dists.normal.mode":"@stdlib/stats/base/dists/normal/mode","base.dists.normal.Normal":"@stdlib/stats/base/dists/normal/ctor","base.dists.normal.pdf":"@stdlib/stats/base/dists/normal/pdf","base.dists.normal.quantile":"@stdlib/stats/base/dists/normal/quantile","base.dists.normal.skewness":"@stdlib/stats/base/dists/normal/skewness","base.dists.normal.stdev":"@stdlib/stats/base/dists/normal/stdev","base.dists.normal.variance":"@stdlib/stats/base/dists/normal/variance","base.dists.pareto1.cdf":"@stdlib/stats/base/dists/pareto-type1/cdf","base.dists.pareto1.entropy":"@stdlib/stats/base/dists/pareto-type1/entropy","base.dists.pareto1.kurtosis":"@stdlib/stats/base/dists/pareto-type1/kurtosis","base.dists.pareto1.logcdf":"@stdlib/stats/base/dists/pareto-type1/logcdf","base.dists.pareto1.logpdf":"@stdlib/stats/base/dists/pareto-type1/logpdf","base.dists.pareto1.mean":"@stdlib/stats/base/dists/pareto-type1/mean","base.dists.pareto1.median":"@stdlib/stats/base/dists/pareto-type1/median","base.dists.pareto1.mode":"@stdlib/stats/base/dists/pareto-type1/mode","base.dists.pareto1.Pareto1":"@stdlib/stats/base/dists/pareto-type1/ctor","base.dists.pareto1.pdf":"@stdlib/stats/base/dists/pareto-type1/pdf","base.dists.pareto1.quantile":"@stdlib/stats/base/dists/pareto-type1/quantile","base.dists.pareto1.skewness":"@stdlib/stats/base/dists/pareto-type1/skewness","base.dists.pareto1.stdev":"@stdlib/stats/base/dists/pareto-type1/stdev","base.dists.pareto1.variance":"@stdlib/stats/base/dists/pareto-type1/variance","base.dists.poisson.cdf":"@stdlib/stats/base/dists/poisson/cdf","base.dists.poisson.entropy":"@stdlib/stats/base/dists/poisson/entropy","base.dists.poisson.kurtosis":"@stdlib/stats/base/dists/poisson/kurtosis","base.dists.poisson.logpmf":"@stdlib/stats/base/dists/poisson/logpmf","base.dists.poisson.mean":"@stdlib/stats/base/dists/poisson/mean","base.dists.poisson.median":"@stdlib/stats/base/dists/poisson/median","base.dists.poisson.mgf":"@stdlib/stats/base/dists/poisson/mgf","base.dists.poisson.mode":"@stdlib/stats/base/dists/poisson/mode","base.dists.poisson.pmf":"@stdlib/stats/base/dists/poisson/pmf","base.dists.poisson.Poisson":"@stdlib/stats/base/dists/poisson/ctor","base.dists.poisson.quantile":"@stdlib/stats/base/dists/poisson/quantile","base.dists.poisson.skewness":"@stdlib/stats/base/dists/poisson/skewness","base.dists.poisson.stdev":"@stdlib/stats/base/dists/poisson/stdev","base.dists.poisson.variance":"@stdlib/stats/base/dists/poisson/variance","base.dists.rayleigh.cdf":"@stdlib/stats/base/dists/rayleigh/cdf","base.dists.rayleigh.entropy":"@stdlib/stats/base/dists/rayleigh/entropy","base.dists.rayleigh.kurtosis":"@stdlib/stats/base/dists/rayleigh/kurtosis","base.dists.rayleigh.logcdf":"@stdlib/stats/base/dists/rayleigh/logcdf","base.dists.rayleigh.logpdf":"@stdlib/stats/base/dists/rayleigh/logpdf","base.dists.rayleigh.mean":"@stdlib/stats/base/dists/rayleigh/mean","base.dists.rayleigh.median":"@stdlib/stats/base/dists/rayleigh/median","base.dists.rayleigh.mgf":"@stdlib/stats/base/dists/rayleigh/mgf","base.dists.rayleigh.mode":"@stdlib/stats/base/dists/rayleigh/mode","base.dists.rayleigh.pdf":"@stdli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ognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdlib/stats/base/dists/normal/entropy","base.dists.normal.kurtosis":"@stdlib/stats/base/dists/normal/kurtosis","base.dists.normal.logcdf":"@stdlib/stats/base/dists/normal/logcdf","base.dists.normal.logpdf":"@stdlib/stats/base/dists/normal/logpdf","base.dists.normal.mean":"@stdlib/stats/base/dists/normal/mean","base.dists.normal.median":"@stdlib/stats/base/dists/normal/median","base.dists.normal.mgf":"@stdlib/stats/base/dists/normal/mgf","base.dists.normal.mode":"@stdlib/stats/base/dists/normal/mode","base.dists.normal.Normal":"@stdlib/stats/base/dists/normal/ctor","base.dists.normal.pdf":"@stdlib/stats/base/dists/normal/pdf","base.dists.normal.quantile":"@stdlib/stats/base/dists/normal/quantile","base.dists.normal.skewness":"@stdlib/stats/base/dists/normal/skewness","base.dists.normal.stdev":"@stdlib/stats/base/dists/normal/stdev","base.dists.normal.variance":"@stdlib/stats/base/dists/normal/variance","base.dists.pareto1.cdf":"@stdlib/stats/base/dists/pareto-type1/cdf","base.dists.pareto1.entropy":"@stdlib/stats/base/dists/pareto-type1/entropy","base.dists.pareto1.kurtosis":"@stdlib/stats/base/dists/pareto-type1/kurtosis","base.dists.pareto1.logcdf":"@stdlib/stats/base/dists/pareto-type1/logcdf","base.dists.pareto1.logpdf":"@stdlib/stats/base/dists/pareto-type1/logpdf","base.dists.pareto1.mean":"@stdlib/stats/base/dists/pareto-type1/mean","base.dists.pareto1.median":"@stdlib/stats/base/dists/pareto-type1/median","base.dists.pareto1.mode":"@stdlib/stats/base/dists/pareto-type1/mode","base.dists.pareto1.Pareto1":"@stdlib/stats/base/dists/pareto-type1/ctor","base.dists.pareto1.pdf":"@stdlib/stats/base/dists/pareto-type1/pdf","base.dists.pareto1.quantile":"@stdlib/stats/base/dists/pareto-type1/quantile","base.dists.pareto1.skewness":"@stdlib/stats/base/dists/pareto-type1/skewness","base.dists.pareto1.stdev":"@stdlib/stats/base/dists/pareto-type1/stdev","base.dists.pareto1.variance":"@stdlib/stats/base/dists/pareto-type1/variance","base.dists.poisson.cdf":"@stdlib/stats/base/dists/poisson/cdf","base.dists.poisson.entropy":"@stdlib/stats/base/dists/poisson/entropy","base.dists.poisson.kurtosis":"@stdlib/stats/base/dists/poisson/kurtosis","base.dists.poisson.logpmf":"@stdlib/stats/base/dists/poisson/logpmf","base.dists.poisson.mean":"@stdlib/stats/base/dists/poisson/mean","base.dists.poisson.median":"@stdlib/stats/base/dists/poisson/median","base.dists.poisson.mgf":"@stdlib/stats/base/dists/poisson/mgf","base.dists.poisson.mode":"@stdlib/stats/base/dists/poisson/mode","base.dists.poisson.pmf":"@stdlib/stats/base/dists/poisson/pmf","base.dists.poisson.Poisson":"@stdlib/stats/base/dists/poisson/ctor","base.dists.poisson.quantile":"@stdlib/stats/base/dists/poisson/quantile","base.dists.poisson.skewness":"@stdlib/stats/base/dists/poisson/skewness","base.dists.poisson.stdev":"@stdlib/stats/base/dists/poisson/stdev","base.dists.poisson.variance":"@stdlib/stats/base/dists/poisson/variance","base.dists.rayleigh.cdf":"@stdlib/stats/base/dists/rayleigh/cdf","base.dists.rayleigh.entropy":"@stdlib/stats/base/dists/rayleigh/entropy","base.dists.rayleigh.kurtosis":"@stdlib/stats/base/dists/rayleigh/kurtosis","base.dists.rayleigh.logcdf":"@stdlib/stats/base/dists/rayleigh/logcdf","base.dists.rayleigh.logpdf":"@stdlib/stats/base/dists/rayleigh/logpdf","base.dists.rayleigh.mean":"@stdlib/stats/base/dists/rayleigh/mean","base.dists.rayleigh.median":"@stdlib/stats/base/dists/rayleigh/median","base.dists.rayleigh.mgf":"@stdlib/stats/base/dists/rayleigh/mgf","base.dists.rayleigh.mode":"@stdlib/stats/base/dists/rayleigh/mode","base.dists.rayleigh.pdf":"@stdli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sin-by","strided.asinBy":"@stdlib/math/strided/special/asin-by","strided.asinhBy":"@stdlib/math/strided/special/asinh-by","strided.atanBy":"@stdlib/math/strided/special/atan-by","strided.atanhBy":"@stdlib/math/strided/special/atanh-by","strided.avercosBy":"@stdlib/math/strided/special/avercos-by","strided.aversinBy":"@stdlib/math/strided/special/aversin-by","strided.besselj0By":"@stdlib/math/strided/special/besselj0-by","strided.besselj1By":"@stdlib/math/strided/special/besselj1-by","strided.bessely0By":"@stdlib/math/strided/special/bessely0-by","strided.bessely1By":"@stdlib/math/strided/special/bessely1-by","strided.binetBy":"@stdlib/math/strided/special/binet-by","strided.cbrt":"@stdlib/math/strided/special/cbrt","strided.cbrtBy":"@stdlib/math/strided/special/cbrt-by","strided.ceil":"@stdlib/math/strided/special/ceil","strided.cosBy":"@stdlib/math/strided/special/cos-by","strided.deg2rad":"@stdlib/math/strided/special/deg2rad","strided.dataTypes":"@stdlib/strided/dtypes","strided.dcbrtBy":"@stdlib/math/strided/special/dcbrt-by","strided.dispatch":"@stdlib/strided/dispatch","strided.dispatchBy":"@stdlib/strided/dispatch-by","strided.floor":"@stdlib/math/strided/special/floor","strided.inv":"@stdlib/math/strided/special/inv","strided.mul":"@stdlib/math/strided/ops/mul","strided.mulBy":"@stdlib/math/strided/ops/mul-by","strided.ramp":"@stdlib/math/strided/special/ramp","strided.rsqrt":"@stdlib/math/strided/special/rsqrt","strided.sinBy":"@stdlib/math/strided/special/sin-by","strided.sqrt":"@stdlib/math/strided/special/sqrt","strided.sqrtBy":"@stdlib/math/strided/special/sqrt-by","strided.sub":"@stdlib/math/strided/ops/sub","strided.subBy":"@stdlib/math/strided/ops/sub-by","strided.trunc":"@stdlib/math/strided/special/trunc","stridedarray2iterator":"@stdlib/array/to-strided-iterator","stridedArrayStream":"@stdlib/streams/node/from-strided-array","string2buffer":"@stdlib/buffer/from-string","sub2ind":"@stdlib/ndarray/sub2ind","substringAfter":"@stdlib/string/substring-after","substringAfterLast":"@stdlib/string/substring-after-last","substringBefore":"@stdlib/string/substring-before","substringBeforeLast":"@stdlib/string/substring-before-last","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol/ctor","tabulate":"@stdlib/utils/tabulate","tabulateBy":"@stdlib/utils/tabulate-by","tabulateByAsync":"@stdlib/utils/async/tabulate-by","thunk":"@stdlib/utils/thunk","tic":"@stdlib/time/tic","timeit":"@stdlib/utils/timeit","tmpdir":"@stdlib/os/tmpdir","toc":"@stdlib/time/toc","tokenize":"@stdlib/nlp/tokenize","transformStream":"@stdlib/streams/node/transform","trim":"@stdlib/string/trim","truncate":"@stdlib/string/truncate","truncateMiddle":"@stdlib/string/truncate-middle","trycatch":"@stdlib/utils/try-catch","trycatchAsync":"@stdlib/utils/async/try-catch","tryFunction":"@stdlib/utils/try-function","tryRequire":"@stdlib/utils/try-require","trythen":"@stdlib/utils/try-then","trythenAsync":"@stdlib/utils/async/try-then","ttest":"@stdlib/stats/ttest","ttest2":"@stdlib/stats/ttest2","TWO_PI":"@stdlib/constants/float64/two-pi","typedarray":"@stdlib/array/typed","typedarray2json":"@stdlib/array/to-json","typedarrayCtors":"@stdlib/array/typed-ctors","typedarrayDataTypes":"@stdlib/array/typed-dtypes","typedarraypool":"@stdlib/array/pool","typemax":"@stdlib/utils/type-max","typemin":"@stdlib/utils/type-min","typeOf":"@stdlib/utils/type-of","UINT8_MAX":"@stdlib/constants/uint8/max","UINT8_NUM_BYTES":"@stdlib/constants/uint8/num-bytes","Uint8Array":"@stdlib/array/uint8","Uint8ClampedArray":"@stdlib/array/uint8c","UINT16_MAX":"@stdlib/constants/uint16/max","UINT16_NUM_BYTES":"@stdlib/constants/uint16/num-bytes","Uint16Array":"@stdlib/array/uint16","UINT32_MAX":"@stdlib/constants/uint32/max","UINT32_NUM_BYTES":"@stdlib/constants/uint32/num-bytes","Uint32Array":"@stdlib/array/uint32","umask":"@stdlib/process/umask","uncapitalize":"@stdlib/string/uncapitalize","uncapitalizeKeys":"@stdlib/utils/uncapitalize-keys","uncurry":"@stdlib/utils/uncurry","uncurryRight":"@stdlib/utils/uncurry-right","UNICODE_MAX":"@stdlib/constants/unicode/max","UNICODE_MAX_BMP":"@stdlib/constants/unicode/max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot/sparklines/unicode/column","UnicodeLineChartSparkline":"@stdlib/plot/sparklines/unicode/line","UnicodeSparkline":"@stdlib/plot/sparklines/unicode","UnicodeTristateChartSparkline":"@stdlib/plot/sparklines/unicode/tristate","UnicodeUpDownChartSparkline":"@stdlib/plot/sparklines/unicode/up-down","UnicodeWinLossChartSparkline":"@stdlib/plot/sparklines/unicode/win-loss","unlink":"@stdlib/fs/unlink","unshift":"@stdlib/utils/unshift","until":"@stdlib/utils/until","untilAsync":"@stdlib/utils/async/until","untilEach":"@stdlib/utils/until-each","untilEachRight":"@stdlib/utils/until-each-right","unzip":"@stdlib/utils/unzip","uppercase":"@stdlib/string/uppercase","uppercaseKeys":"@stdlib/utils/uppercase-keys","US_STATES_ABBR":"@stdlib/datasets/us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets/us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets/us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets/us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets/us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string/utf16-to-utf8-array","vartest":"@stdlib/stats/vartest","waterfall":"@stdlib/utils/async/series-waterfall","WebAssemblyMemory":"@stdlib/wasm/memory","whileAsync":"@stdlib/utils/async/while","whileEach":"@stdlib/utils/while-each","whileEachRight":"@stdlib/utils/while-each-right","whilst":"@stdlib/utils/while","wilcoxon":"@stdlib/stats/wilcoxon","writableProperties":"@stdlib/utils/writable-properties","writablePropertiesIn":"@stdlib/utils/writable-properties-in","writablePropertyNames":"@stdlib/utils/writable-property-names","writablePropertyNamesIn":"@stdlib/utils/writable-property-names-in","writablePropertySymbols":"@stdlib/utils/writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils/writable-property-symbols-in","writeFile":"@stdlib/fs/write-file","zip":"@stdlib/utils/zip","ztest":"@stdlib/stats/ztest","ztest2":"@stdlib/stats/ztest2"} diff --git a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv index 6d24b6992587..b058caf7eaa2 100644 --- a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv @@ -1038,7 +1038,7 @@ base.strided.daxpy,"@stdlib/blas-base-daxpy" base.strided.dcbrt,"@stdlib/math-strided-special-dcbrt" base.strided.dceil,"@stdlib/math-strided-special-dceil" base.strided.dcopy,"@stdlib/blas-base-dcopy" -base.strided.dcumax,"@stdlib/stats-base-dcumax" +base.strided.dcumax,"@stdlib/stats-strided-dcumax" base.strided.dcumaxabs,"@stdlib/stats-base-dcumaxabs" base.strided.dcumin,"@stdlib/stats-base-dcumin" base.strided.dcuminabs,"@stdlib/stats-base-dcuminabs" @@ -1054,7 +1054,7 @@ base.strided.dfloor,"@stdlib/math-strided-special-dfloor" base.strided.dinv,"@stdlib/math-strided-special-dinv" base.strided.dmap,"@stdlib/strided-base-dmap" base.strided.dmap2,"@stdlib/strided-base-dmap2" -base.strided.dmax,"@stdlib/stats-base-dmax" +base.strided.dmax,"@stdlib/stats-strided-dmax" base.strided.dmaxabs,"@stdlib/stats-base-dmaxabs" base.strided.dmaxabssorted,"@stdlib/stats-base-dmaxabssorted" base.strided.dmaxsorted,"@stdlib/stats-base-dmaxsorted" diff --git a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json index 755583c577fd..68bffe361be6 100644 --- a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json @@ -1 +1 @@ -{"abs":"@stdlib/math-special-abs","acartesianPower":"@stdlib/array-cartesian-power","acartesianProduct":"@stdlib/array-cartesian-product","acartesianSquare":"@stdlib/array-cartesian-square","acronym":"@stdlib/string-acronym","aempty":"@stdlib/array-empty","aemptyLike":"@stdlib/array-empty-like","AFINN_96":"@stdlib/datasets-afinn-96","AFINN_111":"@stdlib/datasets-afinn-111","afull":"@stdlib/array-full","afullLike":"@stdlib/array-full-like","alias2pkg":"@stdlib/namespace-alias2pkg","alias2related":"@stdlib/namespace-alias2related","alias2standalone":"@stdlib/namespace-alias2standalone","aliases":"@stdlib/namespace-aliases","allocUnsafe":"@stdlib/buffer-alloc-unsafe","amskfilter":"@stdlib/array-mskfilter","amskput":"@stdlib/array-mskput","amskreject":"@stdlib/array-mskreject","anans":"@stdlib/array-nans","anansLike":"@stdlib/array-nans-like","anova1":"@stdlib/stats-anova1","ANSCOMBES_QUARTET":"@stdlib/datasets-anscombes-quartet","any":"@stdlib/utils-any","anyBy":"@stdlib/utils-any-by","anyByAsync":"@stdlib/utils-async-any-by","anyByRight":"@stdlib/utils-any-by-right","anyByRightAsync":"@stdlib/utils-async-any-by-right","anyInBy":"@stdlib/utils-any-in-by","anyOwnBy":"@stdlib/utils-any-own-by","aones":"@stdlib/array-ones","aonesLike":"@stdlib/array-ones-like","aoneTo":"@stdlib/array-one-to","aoneToLike":"@stdlib/array-one-to-like","APERY":"@stdlib/constants-float64-apery","aplace":"@stdlib/array-place","append":"@stdlib/utils-append","aput":"@stdlib/array-put","ARCH":"@stdlib/os-arch","argumentFunction":"@stdlib/utils-argument-function","ARGV":"@stdlib/process-argv","array":"@stdlib/ndarray-array","array2buffer":"@stdlib/buffer-from-array","array2fancy":"@stdlib/array-to-fancy","array2iterator":"@stdlib/array-to-iterator","array2iteratorRight":"@stdlib/array-to-iterator-right","ArrayBuffer":"@stdlib/array-buffer","arraybuffer2buffer":"@stdlib/buffer-from-arraybuffer","arrayCtors":"@stdlib/array-ctors","arrayDataType":"@stdlib/array-dtype","arrayDataTypes":"@stdlib/array-dtypes","ArrayIndex":"@stdlib/array-index","arrayMinDataType":"@stdlib/array-min-dtype","arrayMostlySafeCasts":"@stdlib/array-mostly-safe-casts","arrayNextDataType":"@stdlib/array-next-dtype","arrayPromotionRules":"@stdlib/array-promotion-rules","arraySafeCasts":"@stdlib/array-safe-casts","arraySameKindCasts":"@stdlib/array-same-kind-casts","arrayShape":"@stdlib/array-shape","arrayStream":"@stdlib/streams-node-from-array","arrayview2iterator":"@stdlib/array-to-view-iterator","arrayview2iteratorRight":"@stdlib/array-to-view-iterator-right","aslice":"@stdlib/array-slice","AsyncIteratorSymbol":"@stdlib/symbol-async-iterator","atake":"@stdlib/array-take","azeros":"@stdlib/array-zeros","azerosLike":"@stdlib/array-zeros-like","azeroTo":"@stdlib/array-zero-to","azeroToLike":"@stdlib/array-zero-to-like","bartlettTest":"@stdlib/stats-bartlett-test","base.abs":"@stdlib/math-base-special-abs","base.abs2":"@stdlib/math-base-special-abs2","base.abs2f":"@stdlib/math-base-special-abs2f","base.absdiff":"@stdlib/math-base-utils-absolute-difference","base.absf":"@stdlib/math-base-special-absf","base.acartesianPower":"@stdlib/array-base-cartesian-power","base.acartesianProduct":"@stdlib/array-base-cartesian-product","base.acartesianSquare":"@stdlib/array-base-cartesian-square","base.acos":"@stdlib/math-base-special-acos","base.acosd":"@stdlib/math-base-special-acosd","base.acosf":"@stdlib/math-base-special-acosf","base.acosh":"@stdlib/math-base-special-acosh","base.acot":"@stdlib/math-base-special-acot","base.acotd":"@stdlib/math-base-special-acotd","base.acotf":"@stdlib/math-base-special-acotf","base.acoth":"@stdlib/math-base-special-acoth","base.acovercos":"@stdlib/math-base-special-acovercos","base.acoversin":"@stdlib/math-base-special-acoversin","base.acsc":"@stdlib/math-base-special-acsc","base.acscd":"@stdlib/math-base-special-acscd","base.acscdf":"@stdlib/math-base-special-acscdf","base.acscf":"@stdlib/math-base-special-acscf","base.acsch":"@stdlib/math-base-special-acsch","base.add":"@stdlib/math-base-ops-add","base.add3":"@stdlib/math-base-ops-add3","base.add4":"@stdlib/math-base-ops-add4","base.add5":"@stdlib/math-base-ops-add5","base.addf":"@stdlib/math-base-ops-addf","base.afilled":"@stdlib/array-base-filled","base.afilled2d":"@stdlib/array-base-filled2d","base.afilled2dBy":"@stdlib/array-base-filled2d-by","base.afilled3d":"@stdlib/array-base-filled3d","base.afilled3dBy":"@stdlib/array-base-filled3d-by","base.afilled4d":"@stdlib/array-base-filled4d","base.afilled4dBy":"@stdlib/array-base-filled4d-by","base.afilled5d":"@stdlib/array-base-filled5d","base.afilled5dBy":"@stdlib/array-base-filled5d-by","base.afilledBy":"@stdlib/array-base-filled-by","base.afillednd":"@stdlib/array-base-fillednd","base.afilledndBy":"@stdlib/array-base-fillednd-by","base.afilter":"@stdlib/array-base-filter","base.afirst":"@stdlib/array-base-first","base.aflatten":"@stdlib/array-base-flatten","base.aflatten2d":"@stdlib/array-base-flatten2d","base.aflatten2dBy":"@stdlib/array-b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-by","strided.asinBy":"@stdlib/math-strided-special-asin-by","strided.asinhBy":"@stdlib/math-strided-special-asinh-by","strided.atanBy":"@stdlib/math-strided-special-atan-by","strided.atanhBy":"@stdlib/math-strided-special-atanh-by","strided.avercosBy":"@stdlib/math-strided-special-avercos-by","strided.aversinBy":"@stdlib/math-strided-special-aversin-by","strided.besselj0By":"@stdlib/math-strided-special-besselj0-by","strided.besselj1By":"@stdlib/math-strided-special-besselj1-by","strided.bessely0By":"@stdlib/math-strided-special-bessely0-by","strided.bessely1By":"@stdlib/math-strided-special-bessely1-by","strided.binetBy":"@stdlib/math-strided-special-binet-by","strided.cbrt":"@stdlib/math-strided-special-cbrt","strided.cbrtBy":"@stdlib/math-strided-special-cbrt-by","strided.ceil":"@stdlib/math-strided-special-ceil","strided.cosBy":"@stdlib/math-strided-special-cos-by","strided.deg2rad":"@stdlib/math-strided-special-deg2rad","strided.dataTypes":"@stdlib/strided-dtypes","strided.dcbrtBy":"@stdlib/math-strided-special-dcbrt-by","strided.dispatch":"@stdlib/strided-dispatch","strided.dispatchBy":"@stdlib/strided-dispatch-by","strided.floor":"@stdlib/math-strided-special-floor","strided.inv":"@stdlib/math-strided-special-inv","strided.mul":"@stdlib/math-strided-ops-mul","strided.mulBy":"@stdlib/math-strided-ops-mul-by","strided.ramp":"@stdlib/math-strided-special-ramp","strided.rsqrt":"@stdlib/math-strided-special-rsqrt","strided.sinBy":"@stdlib/math-strided-special-sin-by","strided.sqrt":"@stdlib/math-strided-special-sqrt","strided.sqrtBy":"@stdlib/math-strided-special-sqrt-by","strided.sub":"@stdlib/math-strided-ops-sub","strided.subBy":"@stdlib/math-strided-ops-sub-by","strided.trunc":"@stdlib/math-strided-special-trunc","stridedarray2iterator":"@stdlib/array-to-strided-iterator","stridedArrayStream":"@stdlib/streams-node-from-strided-array","string2buffer":"@stdlib/buffer-from-string","sub2ind":"@stdlib/ndarray-sub2ind","substringAfter":"@stdlib/string-substring-after","substringAfterLast":"@stdlib/string-substring-after-last","substringBefore":"@stdlib/string-substring-before","substringBeforeLast":"@stdlib/string-substring-before-last","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets-suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets-suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol-ctor","tabulate":"@stdlib/utils-tabulate","tabulateBy":"@stdlib/utils-tabulate-by","tabulateByAsync":"@stdlib/utils-async-tabulate-by","thunk":"@stdlib/utils-thunk","tic":"@stdlib/time-tic","timeit":"@stdlib/utils-timeit","tmpdir":"@stdlib/os-tmpdir","toc":"@stdlib/time-toc","tokenize":"@stdlib/nlp-tokenize","transformStream":"@stdlib/streams-node-transform","trim":"@stdlib/string-trim","truncate":"@stdlib/string-truncate","truncateMiddle":"@stdlib/string-truncate-middle","trycatch":"@stdlib/utils-try-catch","trycatchAsync":"@stdlib/utils-async-try-catch","tryFunction":"@stdlib/utils-try-function","tryRequire":"@stdlib/utils-try-require","trythen":"@stdlib/utils-try-then","trythenAsync":"@stdlib/utils-async-try-then","ttest":"@stdlib/stats-ttest","ttest2":"@stdlib/stats-ttest2","TWO_PI":"@stdlib/constants-float64-two-pi","typedarray":"@stdlib/array-typed","typedarray2json":"@stdlib/array-to-json","typedarrayCtors":"@stdlib/array-typed-ctors","typedarrayDataTypes":"@stdlib/array-typed-dtypes","typedarraypool":"@stdlib/array-pool","typemax":"@stdlib/utils-type-max","typemin":"@stdlib/utils-type-min","typeOf":"@stdlib/utils-type-of","UINT8_MAX":"@stdlib/constants-uint8-max","UINT8_NUM_BYTES":"@stdlib/constants-uint8-num-bytes","Uint8Array":"@stdlib/array-uint8","Uint8ClampedArray":"@stdlib/array-uint8c","UINT16_MAX":"@stdlib/constants-uint16-max","UINT16_NUM_BYTES":"@stdlib/constants-uint16-num-bytes","Uint16Array":"@stdlib/array-uint16","UINT32_MAX":"@stdlib/constants-uint32-max","UINT32_NUM_BYTES":"@stdlib/constants-uint32-num-bytes","Uint32Array":"@stdlib/array-uint32","umask":"@stdlib/process-umask","uncapitalize":"@stdlib/string-uncapitalize","uncapitalizeKeys":"@stdlib/utils-uncapitalize-keys","uncurry":"@stdlib/utils-uncurry","uncurryRight":"@stdlib/utils-uncurry-right","UNICODE_MAX":"@stdlib/constants-unicode-max","UNICODE_MAX_BMP":"@stdlib/constants-unicode-max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot-sparklines-unicode-column","UnicodeLineChartSparkline":"@stdlib/plot-sparklines-unicode-line","UnicodeSparkline":"@stdlib/plot-sparklines-unicode","UnicodeTristateChartSparkline":"@stdlib/plot-sparklines-unicode-tristate","UnicodeUpDownChartSparkline":"@stdlib/plot-sparklines-unicode-up-down","UnicodeWinLossChartSparkline":"@stdlib/plot-sparklines-unicode-win-loss","unlink":"@stdlib/fs-unlink","unshift":"@stdlib/utils-unshift","until":"@stdlib/utils-until","untilAsync":"@stdlib/utils-async-until","untilEach":"@stdlib/utils-until-each","untilEachRight":"@stdlib/utils-until-each-right","unzip":"@stdlib/utils-unzip","uppercase":"@stdlib/string-uppercase","uppercaseKeys":"@stdlib/utils-uppercase-keys","US_STATES_ABBR":"@stdlib/datasets-us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets-us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets-us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets-us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets-us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string-utf16-to-utf8-array","vartest":"@stdlib/stats-vartest","waterfall":"@stdlib/utils-async-series-waterfall","WebAssemblyMemory":"@stdlib/wasm-memory","whileAsync":"@stdlib/utils-async-while","whileEach":"@stdlib/utils-while-each","whileEachRight":"@stdlib/utils-while-each-right","whilst":"@stdlib/utils-while","wilcoxon":"@stdlib/stats-wilcoxon","writableProperties":"@stdlib/utils-writable-properties","writablePropertiesIn":"@stdlib/utils-writable-properties-in","writablePropertyNames":"@stdlib/utils-writable-property-names","writablePropertyNamesIn":"@stdlib/utils-writable-property-names-in","writablePropertySymbols":"@stdlib/utils-writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils-writable-property-symbols-in","writeFile":"@stdlib/fs-write-file","zip":"@stdlib/utils-zip","ztest":"@stdlib/stats-ztest","ztest2":"@stdlib/stats-ztest2"} diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/c.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/c.js index fa95cc162f94..08c2794eeb13 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/c.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/c.js @@ -69,7 +69,7 @@ ns.push({ 'related': [ '@stdlib/stats/base/cumin', '@stdlib/stats/base/curange', - '@stdlib/stats/base/dcumax', + '@stdlib/stats/strided/dcumax', '@stdlib/stats/base/nancumax', '@stdlib/stats/base/scumax' ] @@ -84,7 +84,7 @@ ns.push({ '@stdlib/stats/base/cumax', '@stdlib/stats/base/cuminabs', '@stdlib/stats/base/curangeabs', - '@stdlib/stats/base/dcumaxabs', + '@stdlib/stats/strided/dcumaxabs', '@stdlib/stats/base/nancumaxabs', '@stdlib/stats/base/scumaxabs' ] diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js index 90e20ec0c918..869273a9ad3f 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js @@ -216,8 +216,8 @@ ns.push({ ns.push({ 'alias': 'base.strided.dcumax', - 'path': '@stdlib/stats/base/dcumax', - 'value': require( '@stdlib/stats/base/dcumax' ), + 'path': '@stdlib/stats/strided/dcumax', + 'value': require( '@stdlib/stats/strided/dcumax' ), 'type': 'Function', 'related': [ '@stdlib/stats/base/cumax', @@ -230,12 +230,12 @@ ns.push({ ns.push({ 'alias': 'base.strided.dcumaxabs', - 'path': '@stdlib/stats/base/dcumaxabs', - 'value': require( '@stdlib/stats/base/dcumaxabs' ), + 'path': '@stdlib/stats/strided/dcumaxabs', + 'value': require( '@stdlib/stats/strided/dcumaxabs' ), 'type': 'Function', 'related': [ '@stdlib/stats/base/cumaxabs', - '@stdlib/stats/base/dcumax', + '@stdlib/stats/strided/dcumax', '@stdlib/stats/base/dcuminabs', '@stdlib/stats/base/dnancumaxabs', '@stdlib/stats/base/scumaxabs' @@ -249,7 +249,7 @@ ns.push({ 'type': 'Function', 'related': [ '@stdlib/stats/base/cumin', - '@stdlib/stats/base/dcumax', + '@stdlib/stats/strided/dcumax', '@stdlib/stats/base/dcurange', '@stdlib/stats/base/dnancumin', '@stdlib/stats/base/scumin' @@ -263,7 +263,7 @@ ns.push({ 'type': 'Function', 'related': [ '@stdlib/stats/base/cuminabs', - '@stdlib/stats/base/dcumaxabs', + '@stdlib/stats/strided/dcumaxabs', '@stdlib/stats/base/dcumin', '@stdlib/stats/base/dnancuminabs', '@stdlib/stats/base/scuminabs' @@ -426,8 +426,8 @@ ns.push({ ns.push({ 'alias': 'base.strided.dmax', - 'path': '@stdlib/stats/base/dmax', - 'value': require( '@stdlib/stats/base/dmax' ), + 'path': '@stdlib/stats/strided/dmax', + 'value': require( '@stdlib/stats/strided/dmax' ), 'type': 'Function', 'related': [ '@stdlib/stats/base/dmin', @@ -443,7 +443,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/dmaxabs' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dminabs', '@stdlib/stats/base/dnanmaxabs', '@stdlib/stats/base/maxabs', @@ -472,7 +472,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/dmaxsorted' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dminsorted', '@stdlib/stats/base/dnanmaxsorted', '@stdlib/stats/base/maxsorted', @@ -680,7 +680,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/dmidrange' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dmean', '@stdlib/stats/base/dmin', '@stdlib/stats/base/dnanmidrange', @@ -696,7 +696,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/dmin' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dnanmin', '@stdlib/stats/base/min', '@stdlib/stats/base/smin' @@ -865,7 +865,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/dmskmax' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dmskmin', '@stdlib/stats/base/dnanmax', '@stdlib/stats/base/dnanmskmax', @@ -996,7 +996,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/dnanmax' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dnanmin', '@stdlib/stats/base/nanmax', '@stdlib/stats/base/snanmax' @@ -1507,7 +1507,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/drange' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/dmin', '@stdlib/stats/base/dnanrange', '@stdlib/stats/base/range', diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js index c69f9c924fa8..efa58dd22a18 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js @@ -56,7 +56,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/max' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/min', '@stdlib/stats/base/nanmax', '@stdlib/stats/base/smax' @@ -83,7 +83,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/max-by' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/max', '@stdlib/stats/base/min-by', '@stdlib/stats/base/nanmax-by', diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js index 217bf761b1f9..f0a97db01987 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js @@ -218,7 +218,7 @@ ns.push({ 'type': 'Function', 'related': [ '@stdlib/stats/base/cumax', - '@stdlib/stats/base/dcumax', + '@stdlib/stats/strided/dcumax', '@stdlib/stats/base/scumin', '@stdlib/stats/base/scurange', '@stdlib/stats/base/snancumax' @@ -232,7 +232,7 @@ ns.push({ 'type': 'Function', 'related': [ '@stdlib/stats/base/cumaxabs', - '@stdlib/stats/base/dcumaxabs', + '@stdlib/stats/strided/dcumaxabs', '@stdlib/stats/base/scumax', '@stdlib/stats/base/scuminabs', '@stdlib/stats/base/snancumaxabs' @@ -574,7 +574,7 @@ ns.push({ 'value': require( '@stdlib/stats/base/smax' ), 'type': 'Function', 'related': [ - '@stdlib/stats/base/dmax', + '@stdlib/stats/strided/dmax', '@stdlib/stats/base/max', '@stdlib/stats/base/smin', '@stdlib/stats/base/snanmax' diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index 8ffd9ff35b2d..4c7c7499d2ae 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1038,8 +1038,8 @@ "@stdlib/math/strided/special/dcbrt",base.strided.dcbrt "@stdlib/math/strided/special/dceil",base.strided.dceil "@stdlib/blas/base/dcopy",base.strided.dcopy -"@stdlib/stats/base/dcumax",base.strided.dcumax -"@stdlib/stats/base/dcumaxabs",base.strided.dcumaxabs +"@stdlib/stats/strided/dcumax",base.strided.dcumax +"@stdlib/stats/strided/dcumaxabs",base.strided.dcumaxabs "@stdlib/stats/base/dcumin",base.strided.dcumin "@stdlib/stats/base/dcuminabs",base.strided.dcuminabs "@stdlib/blas/ext/base/dcusum",base.strided.dcusum @@ -1054,7 +1054,7 @@ "@stdlib/math/strided/special/dinv",base.strided.dinv "@stdlib/strided/base/dmap",base.strided.dmap "@stdlib/strided/base/dmap2",base.strided.dmap2 -"@stdlib/stats/base/dmax",base.strided.dmax +"@stdlib/stats/strided/dmax",base.strided.dmax "@stdlib/stats/base/dmaxabs",base.strided.dmaxabs "@stdlib/stats/base/dmaxabssorted",base.strided.dmaxabssorted "@stdlib/stats/base/dmaxsorted",base.strided.dmaxsorted diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index d5f7c35f7169..e2bbb3b92ec1 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ -{"@stdlib/math/special/abs":"abs","@stdlib/array/cartesian-power":"acartesianPower","@stdlib/array/cartesian-product":"acartesianProduct","@stdlib/array/cartesian-square":"acartesianSquare","@stdlib/string/acronym":"acronym","@stdlib/array/empty":"aempty","@stdlib/array/empty-like":"aemptyLike","@stdlib/datasets/afinn-96":"AFINN_96","@stdlib/datasets/afinn-111":"AFINN_111","@stdlib/array/full":"afull","@stdlib/array/full-like":"afullLike","@stdlib/namespace/alias2pkg":"alias2pkg","@stdlib/namespace/alias2related":"alias2related","@stdlib/namespace/alias2standalone":"alias2standalone","@stdlib/namespace/aliases":"aliases","@stdlib/buffer/alloc-unsafe":"allocUnsafe","@stdlib/array/mskfilter":"amskfilter","@stdlib/array/mskput":"amskput","@stdlib/array/mskreject":"amskreject","@stdlib/array/nans":"anans","@stdlib/array/nans-like":"anansLike","@stdlib/stats/anova1":"anova1","@stdlib/datasets/anscombes-quartet":"ANSCOMBES_QUARTET","@stdlib/utils/any":"any","@stdlib/utils/any-by":"anyBy","@stdlib/utils/async/any-by":"anyByAsync","@stdlib/utils/any-by-right":"anyByRight","@stdlib/utils/async/any-by-right":"anyByRightAsync","@stdlib/utils/any-in-by":"anyInBy","@stdlib/utils/any-own-by":"anyOwnBy","@stdlib/array/ones":"aones","@stdlib/array/ones-like":"aonesLike","@stdlib/array/one-to":"aoneTo","@stdlib/array/one-to-like":"aoneToLike","@stdlib/constants/float64/apery":"APERY","@stdlib/array/place":"aplace","@stdlib/utils/append":"append","@stdlib/array/put":"aput","@stdlib/os/arch":"ARCH","@stdlib/utils/argument-function":"argumentFunction","@stdlib/process/argv":"ARGV","@stdlib/ndarray/array":"array","@stdlib/buffer/from-array":"array2buffer","@stdlib/array/to-fancy":"array2fancy","@stdlib/array/to-iterator":"array2iterator","@stdlib/array/to-iterator-right":"array2iteratorRight","@stdlib/array/buffer":"ArrayBuffer","@stdlib/buffer/from-arraybuffer":"arraybuffer2buffer","@stdlib/array/ctors":"arrayCtors","@stdlib/array/dtype":"arrayDataType","@stdlib/array/dtypes":"arrayDataTypes","@stdlib/array/index":"ArrayIndex","@stdlib/array/min-dtype":"arrayMinDataType","@stdlib/array/mostly-safe-casts":"arrayMostlySafeCasts","@stdlib/array/next-dtype":"arrayNextDataType","@stdlib/array/promotion-rules":"arrayPromotionRules","@stdlib/array/safe-casts":"arraySafeCasts","@stdlib/array/same-kind-casts":"arraySameKindCasts","@stdlib/array/shape":"arrayShape","@stdlib/streams/node/from-array":"arrayStream","@stdlib/array/to-view-iterator":"arrayview2iterator","@stdlib/array/to-view-iterator-right":"arrayview2iteratorRight","@stdlib/array/slice":"aslice","@stdlib/symbol/async-iterator":"AsyncIteratorSymbol","@stdlib/array/take":"atake","@stdlib/array/zeros":"azeros","@stdlib/array/zeros-like":"azerosLike","@stdlib/array/zero-to":"azeroTo","@stdlib/array/zero-to-like":"azeroToLike","@stdlib/stats/bartlett-test":"bartlettTest","@stdlib/math/base/special/abs":"base.abs","@stdlib/math/base/special/abs2":"base.abs2","@stdlib/math/base/special/abs2f":"base.abs2f","@stdlib/math/base/utils/absolute-difference":"base.absdiff","@stdlib/math/base/special/absf":"base.absf","@stdlib/array/base/cartesian-power":"base.acartesianPower","@stdlib/array/base/cartesian-product":"base.acartesianProduct","@stdlib/array/base/cartesian-square":"base.acartesianSquare","@stdlib/math/base/special/acos":"base.acos","@stdlib/math/base/special/acosd":"base.acosd","@stdlib/math/base/special/acosf":"base.acosf","@stdlib/math/base/special/acosh":"base.acosh","@stdlib/math/base/special/acot":"base.acot","@stdlib/math/base/special/acotd":"base.acotd","@stdlib/math/base/special/acotf":"base.acotf","@stdlib/math/base/special/acoth":"base.acoth","@stdlib/math/base/special/acovercos":"base.acovercos","@stdlib/math/base/special/acoversin":"base.acoversin","@stdlib/math/base/special/acsc":"base.acsc","@stdlib/math/base/special/acscd":"base.acscd","@stdlib/math/base/special/acscdf":"base.acscdf","@stdlib/math/base/special/acscf":"base.acscf","@stdlib/math/base/special/acsch":"base.acsch","@stdlib/math/base/ops/add":"base.add","@stdlib/math/base/ops/add3":"base.add3","@stdlib/math/base/ops/add4":"base.add4","@stdlib/math/base/ops/add5":"base.add5","@stdlib/math/base/ops/addf":"base.addf","@stdlib/array/base/filled":"base.afilled","@stdlib/array/base/filled2d":"base.afilled2d","@stdlib/array/base/filled2d-by":"base.afilled2dBy","@stdlib/array/base/filled3d":"base.afilled3d","@stdlib/array/base/filled3d-by":"base.afilled3dBy","@stdlib/array/base/filled4d":"base.afilled4d","@stdlib/array/base/filled4d-by":"base.afilled4dBy","@stdlib/array/base/filled5d":"base.afilled5d","@stdlib/array/base/filled5d-by":"base.afilled5dBy","@stdlib/array/base/filled-by":"base.afilledBy","@stdlib/array/base/fillednd":"base.afillednd","@stdlib/array/base/fillednd-by":"base.afilledndBy","@stdlib/array/base/filter":"base.afilter","@stdlib/array/base/first":"base.afirst","@stdlib/array/base/flatten":"base.aflatten","@stdlib/array/base/flatten2d":"base.aflatten2d","@stdlib/array/base/flatten2d-by":"b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ognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/entropy":"base.dists.normal.entropy","@stdlib/stats/base/dists/normal/kurtosis":"base.dists.normal.kurtosis","@stdlib/stats/base/dists/normal/logcdf":"base.dists.normal.logcdf","@stdlib/stats/base/dists/normal/logpdf":"base.dists.normal.logpdf","@stdlib/stats/base/dists/normal/mean":"base.dists.normal.mean","@stdlib/stats/base/dists/normal/median":"base.dists.normal.median","@stdlib/stats/base/dists/normal/mgf":"base.dists.normal.mgf","@stdlib/stats/base/dists/normal/mode":"base.dists.normal.mode","@stdlib/stats/base/dists/normal/ctor":"base.dists.normal.Normal","@stdlib/stats/base/dists/normal/pdf":"base.dists.normal.pdf","@stdlib/stats/base/dists/normal/quantile":"base.dists.normal.quantile","@stdlib/stats/base/dists/normal/skewness":"base.dists.normal.skewness","@stdlib/stats/base/dists/normal/stdev":"base.dists.normal.stdev","@stdlib/stats/base/dists/normal/variance":"base.dists.normal.variance","@stdlib/stats/base/dists/pareto-type1/cdf":"base.dists.pareto1.cdf","@stdlib/stats/base/dists/pareto-type1/entropy":"base.dists.pareto1.entropy","@stdlib/stats/base/dists/pareto-type1/kurtosis":"base.dists.pareto1.kurtosis","@stdlib/stats/base/dists/pareto-type1/logcdf":"base.dists.pareto1.logcdf","@stdlib/stats/base/dists/pareto-type1/logpdf":"base.dists.pareto1.logpdf","@stdlib/stats/base/dists/pareto-type1/mean":"base.dists.pareto1.mean","@stdlib/stats/base/dists/pareto-type1/median":"base.dists.pareto1.median","@stdlib/stats/base/dists/pareto-type1/mode":"base.dists.pareto1.mode","@stdlib/stats/base/dists/pareto-type1/ctor":"base.dists.pareto1.Pareto1","@stdlib/stats/base/dists/pareto-type1/pdf":"base.dists.pareto1.pdf","@stdlib/stats/base/dists/pareto-type1/quantile":"base.dists.pareto1.quantile","@stdlib/stats/base/dists/pareto-type1/skewness":"base.dists.pareto1.skewness","@stdlib/stats/base/dists/pareto-type1/stdev":"base.dists.pareto1.stdev","@stdlib/stats/base/dists/pareto-type1/variance":"base.dists.pareto1.variance","@stdlib/stats/base/dists/poisson/cdf":"base.dists.poisson.cdf","@stdlib/stats/base/dists/poisson/entropy":"base.dists.poisson.entropy","@stdlib/stats/base/dists/poisson/kurtosis":"base.dists.poisson.kurtosis","@stdlib/stats/base/dists/poisson/logpmf":"base.dists.poisson.logpmf","@stdlib/stats/base/dists/poisson/mean":"base.dists.poisson.mean","@stdlib/stats/base/dists/poisson/median":"base.dists.poisson.median","@stdlib/stats/base/dists/poisson/mgf":"base.dists.poisson.mgf","@stdlib/stats/base/dists/poisson/mode":"base.dists.poisson.mode","@stdlib/stats/base/dists/poisson/pmf":"base.dists.poisson.pmf","@stdlib/stats/base/dists/poisson/ctor":"base.dists.poisson.Poisson","@stdlib/stats/base/dists/poisson/quantile":"base.dists.poisson.quantile","@stdlib/stats/base/dists/poisson/skewness":"base.dists.poisson.skewness","@stdlib/stats/base/dists/poisson/stdev":"base.dists.poisson.stdev","@stdlib/stats/base/dists/poisson/variance":"base.dists.poisson.variance","@stdlib/stats/base/dists/rayleigh/cdf":"base.dists.rayleigh.cdf","@stdlib/stats/base/dists/rayleigh/entropy":"base.dists.rayleigh.entropy","@stdlib/stats/base/dists/rayleigh/kurtosis":"base.dists.rayleigh.kurtosis","@stdlib/stats/base/dists/rayleigh/logcdf":"base.dists.rayleigh.logcdf","@stdlib/stats/base/dists/rayleigh/logpdf":"base.dists.rayleigh.logpdf","@stdlib/stats/base/dists/rayleigh/mean":"base.dists.rayleigh.mean","@stdlib/stats/base/dists/rayleigh/median":"base.dists.rayleigh.median","@stdlib/stats/base/dists/rayleigh/mgf":"base.dists.rayleigh.mgf","@stdlib/stats/base/dists/rayleigh/mode":"base.dists.rayleigh.mode","@stdlib/stats/base/dists/rayleig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evy","@stdlib/random/array/logistic":"random.array.logistic","@stdlib/random/array/lognormal":"random.array.lognormal","@stdlib/random/array/minstd":"random.array.minstd","@stdlib/random/array/minstd-shuffle":"random.array.minstdShuffle","@stdlib/random/array/mt19937":"random.array.mt19937","@stdlib/random/array/negative-binomial":"random.array.negativeBinomial","@stdlib/random/array/normal":"random.array.normal","@stdlib/random/array/pareto-type1":"random.array.pareto1","@stdlib/random/array/poisson":"random.array.poisson","@stdlib/random/array/randu":"random.array.randu","@stdlib/random/array/rayleigh":"random.array.rayleigh","@stdlib/random/array/t":"random.array.t","@stdlib/random/array/triangular":"random.array.triangular","@stdlib/random/array/uniform":"random.array.uniform","@stdlib/random/array/weibull":"random.array.weibull","@stdlib/random/iter/arcsine":"random.iterators.arcsine","@stdlib/random/iter/bernoulli":"random.iterators.bernoulli","@stdlib/random/iter/beta":"random.iterators.beta","@stdlib/random/iter/betaprime":"random.iterators.betaprime","@stdlib/random/iter/binomial":"random.iterators.binomial","@stdlib/random/iter/box-muller":"random.iterators.boxMuller","@stdlib/random/iter/cauchy":"random.iterators.cauchy","@stdlib/random/iter/chi":"random.iterators.chi","@stdlib/random/iter/chisquare":"random.iterators.chisquare","@stdlib/random/iter/cosine":"random.iterators.cosine","@stdlib/random/iter/discrete-uniform":"random.iterators.discreteUniform","@stdlib/random/iter/erlang":"random.iterators.erlang","@stdlib/random/iter/exponential":"random.iterators.exponential","@stdlib/random/iter/f":"random.iterators.f","@stdlib/random/iter/frechet":"random.iterators.frechet","@stdlib/random/iter/gamma":"random.iterators.gamma","@stdlib/random/iter/geometric":"random.iterators.geometric","@stdlib/random/iter/gumbel":"random.iterators.gumbel","@stdlib/random/iter/hypergeometric":"random.iterators.hypergeometric","@stdlib/random/iter/improved-ziggurat":"random.iterators.improvedZiggurat","@stdlib/random/iter/invgamma":"random.iterators.invgamma","@stdlib/random/iter/kumaraswamy":"random.iterators.kumaraswamy","@stdlib/random/iter/laplace":"random.iterators.laplace","@stdlib/random/iter/levy":"random.iterators.levy","@stdlib/random/iter/logistic":"random.iterators.logistic","@stdlib/random/iter/lognormal":"random.iterators.lognormal","@stdlib/random/iter/minstd":"random.iterators.minstd","@stdlib/random/iter/minstd-shuffle":"random.iterators.minstdShuffle","@stdlib/random/iter/mt19937":"random.iterators.mt19937","@stdlib/random/iter/negative-binomial":"random.iterators.negativeBinomial","@stdlib/random/iter/normal":"random.iterators.normal","@stdlib/random/iter/pareto-type1":"random.iterators.pareto1","@stdlib/random/iter/poisson":"random.iterators.poisson","@stdlib/random/iter/randi":"random.iterators.randi","@stdlib/random/iter/randn":"random.iterators.randn","@stdlib/random/iter/randu":"random.iterators.randu","@stdlib/random/iter/rayleigh":"random.iterators.rayleigh","@stdlib/random/iter/t":"random.iterators.t","@stdlib/random/iter/triangular":"random.iterators.triangular","@stdlib/random/iter/uniform":"random.iterators.uniform","@stdlib/random/iter/weibull":"random.iterators.weibull","@stdlib/random/streams/arcsine":"random.streams.arcsine","@stdlib/random/streams/bernoulli":"random.streams.bernoulli","@stdlib/random/streams/beta":"random.streams.beta","@stdlib/random/streams/betaprime":"random.streams.betaprime","@stdlib/random/streams/binomial":"random.streams.binomial","@stdlib/random/streams/box-muller":"random.streams.boxMuller","@stdlib/random/streams/cauchy":"random.streams.cauchy","@stdlib/random/streams/chi":"random.streams.chi","@stdlib/random/streams/chisquare":"random.streams.chisquare","@stdlib/random/streams/cosine":"random.streams.cosine","@stdlib/random/streams/discrete-uniform":"random.streams.discreteUniform","@stdlib/random/streams/erlang":"random.streams.erlang","@stdlib/random/streams/exponential":"random.streams.exponential","@stdlib/random/streams/f":"random.streams.f","@stdlib/random/streams/frechet":"random.streams.frechet","@stdlib/random/streams/gamma":"random.streams.gamma","@stdlib/random/streams/geometric":"random.streams.geometric","@stdlib/random/streams/gumbel":"random.streams.gumbel","@stdlib/random/streams/hypergeometric":"random.streams.hypergeometric","@stdlib/random/streams/improved-ziggurat":"random.streams.improvedZiggurat","@stdlib/random/streams/invgamma":"random.streams.invgamma","@stdlib/random/streams/kumaraswamy":"random.streams.kumaraswamy","@stdlib/random/streams/laplace":"random.streams.laplace","@stdlib/random/streams/levy":"random.streams.levy","@stdlib/random/streams/logistic":"random.streams.logistic","@stdlib/random/streams/lognormal":"random.streams.lognormal","@stdlib/random/streams/minstd":"random.streams.minstd","@stdlib/random/streams/minstd-shuffle":"random.streams.minstdShuffle","@stdlib/random/streams/mt19937":"random.streams.mt19937","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rsinBy","@stdlib/math/strided/special/asin-by":"strided.asinBy","@stdlib/math/strided/special/asinh-by":"strided.asinhBy","@stdlib/math/strided/special/atan-by":"strided.atanBy","@stdlib/math/strided/special/atanh-by":"strided.atanhBy","@stdlib/math/strided/special/avercos-by":"strided.avercosBy","@stdlib/math/strided/special/aversin-by":"strided.aversinBy","@stdlib/math/strided/special/besselj0-by":"strided.besselj0By","@stdlib/math/strided/special/besselj1-by":"strided.besselj1By","@stdlib/math/strided/special/bessely0-by":"strided.bessely0By","@stdlib/math/strided/special/bessely1-by":"strided.bessely1By","@stdlib/math/strided/special/binet-by":"strided.binetBy","@stdlib/math/strided/special/cbrt":"strided.cbrt","@stdlib/math/strided/special/cbrt-by":"strided.cbrtBy","@stdlib/math/strided/special/ceil":"strided.ceil","@stdlib/math/strided/special/cos-by":"strided.cosBy","@stdlib/math/strided/special/deg2rad":"strided.deg2rad","@stdlib/strided/dtypes":"strided.dataTypes","@stdlib/math/strided/special/dcbrt-by":"strided.dcbrtBy","@stdlib/strided/dispatch":"strided.dispatch","@stdlib/strided/dispatch-by":"strided.dispatchBy","@stdlib/math/strided/special/floor":"strided.floor","@stdlib/math/strided/special/inv":"strided.inv","@stdlib/math/strided/ops/mul":"strided.mul","@stdlib/math/strided/ops/mul-by":"strided.mulBy","@stdlib/math/strided/special/ramp":"strided.ramp","@stdlib/math/strided/special/rsqrt":"strided.rsqrt","@stdlib/math/strided/special/sin-by":"strided.sinBy","@stdlib/math/strided/special/sqrt":"strided.sqrt","@stdlib/math/strided/special/sqrt-by":"strided.sqrtBy","@stdlib/math/strided/ops/sub":"strided.sub","@stdlib/math/strided/ops/sub-by":"strided.subBy","@stdlib/math/strided/special/trunc":"strided.trunc","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/string/substring-after":"substringAfter","@stdlib/string/substring-after-last":"substringAfterLast","@stdlib/string/substring-before":"substringBefore","@stdlib/string/substring-before-last":"substringBeforeLast","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/utils/thunk":"thunk","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/string/truncate":"truncate","@stdlib/string/truncate-middle":"truncateMiddle","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/float64/two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/uint8/max":"UINT8_MAX","@stdlib/constants/uint8/num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/constants/uint16/max":"UINT16_MAX","@stdlib/constants/uint16/num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/constants/uint32/max":"UINT32_MAX","@stdlib/constants/uint32/num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/utils/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/unicode/max":"UNICODE_MAX","@stdlib/constants/unicode/max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/utils/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/wasm/memory":"WebAssemblyMemory","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/stats/wilcoxon":"wilcoxon","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index b0101c54ea0f..a61a81402114 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1020,8 +1020,8 @@ "@stdlib/blas/base/ccopy","@stdlib/blas/base/cswap" "@stdlib/strided/base/cmap","@stdlib/strided/base/zmap,@stdlib/strided/base/unary" "@stdlib/blas/base/cswap","@stdlib/blas/base/ccopy" -"@stdlib/stats/base/cumax","@stdlib/stats/base/cumin,@stdlib/stats/base/dcumax,@stdlib/stats/base/scumax" -"@stdlib/stats/base/cumaxabs","@stdlib/stats/base/cumax,@stdlib/stats/base/cuminabs,@stdlib/stats/base/dcumaxabs,@stdlib/stats/base/scumaxabs" +"@stdlib/stats/base/cumax","@stdlib/stats/base/cumin,@stdlib/stats/strided/dcumax,@stdlib/stats/base/scumax" +"@stdlib/stats/base/cumaxabs","@stdlib/stats/base/cumax,@stdlib/stats/base/cuminabs,@stdlib/stats/strided/dcumaxabs,@stdlib/stats/base/scumaxabs" "@stdlib/stats/base/cumin","@stdlib/stats/base/cumax,@stdlib/stats/base/dcumin,@stdlib/stats/base/scumin" "@stdlib/stats/base/cuminabs","@stdlib/stats/base/cumaxabs,@stdlib/stats/base/cumin,@stdlib/stats/base/dcuminabs,@stdlib/stats/base/scuminabs" "@stdlib/math/strided/special/dabs","@stdlib/math/strided/special/abs,@stdlib/math/strided/special/dabs2,@stdlib/math/strided/special/sabs" @@ -1038,10 +1038,10 @@ "@stdlib/math/strided/special/dcbrt","@stdlib/math/strided/special/cbrt,@stdlib/math/strided/special/dsqrt,@stdlib/math/strided/special/scbrt" "@stdlib/math/strided/special/dceil","@stdlib/math/strided/special/ceil,@stdlib/math/strided/special/dfloor,@stdlib/math/strided/special/dtrunc,@stdlib/math/strided/special/sceil" "@stdlib/blas/base/dcopy","@stdlib/blas/base/dswap,@stdlib/blas/base/gcopy,@stdlib/blas/base/scopy" -"@stdlib/stats/base/dcumax","@stdlib/stats/base/cumax,@stdlib/stats/base/dcumin,@stdlib/stats/base/scumax" -"@stdlib/stats/base/dcumaxabs","@stdlib/stats/base/cumaxabs,@stdlib/stats/base/dcumax,@stdlib/stats/base/dcuminabs,@stdlib/stats/base/scumaxabs" -"@stdlib/stats/base/dcumin","@stdlib/stats/base/cumin,@stdlib/stats/base/dcumax,@stdlib/stats/base/scumin" -"@stdlib/stats/base/dcuminabs","@stdlib/stats/base/cuminabs,@stdlib/stats/base/dcumaxabs,@stdlib/stats/base/dcumin,@stdlib/stats/base/scuminabs" +"@stdlib/stats/strided/dcumax","@stdlib/stats/base/cumax,@stdlib/stats/base/dcumin,@stdlib/stats/base/scumax" +"@stdlib/stats/strided/dcumaxabs","@stdlib/stats/base/cumaxabs,@stdlib/stats/strided/dcumax,@stdlib/stats/base/dcuminabs,@stdlib/stats/base/scumaxabs" +"@stdlib/stats/base/dcumin","@stdlib/stats/base/cumin,@stdlib/stats/strided/dcumax,@stdlib/stats/base/scumin" +"@stdlib/stats/base/dcuminabs","@stdlib/stats/base/cuminabs,@stdlib/stats/strided/dcumaxabs,@stdlib/stats/base/dcumin,@stdlib/stats/base/scuminabs" "@stdlib/blas/ext/base/dcusum","@stdlib/blas/ext/base/dcusumpw,@stdlib/blas/ext/base/gcusum,@stdlib/blas/ext/base/scusum" "@stdlib/blas/ext/base/dcusumkbn","@stdlib/blas/ext/base/dcusum,@stdlib/blas/ext/base/gcusumkbn,@stdlib/blas/ext/base/scusumkbn" "@stdlib/blas/ext/base/dcusumkbn2","@stdlib/blas/ext/base/dcusum,@stdlib/blas/ext/base/gcusumkbn2,@stdlib/blas/ext/base/scusumkbn2" @@ -1054,10 +1054,10 @@ "@stdlib/math/strided/special/dinv","@stdlib/math/strided/special/inv,@stdlib/math/strided/special/sinv" "@stdlib/strided/base/dmap","@stdlib/strided/base/smap,@stdlib/strided/base/unary" "@stdlib/strided/base/dmap2","@stdlib/strided/base/smap2,@stdlib/strided/base/binary" -"@stdlib/stats/base/dmax","@stdlib/stats/base/dmin,@stdlib/stats/base/dnanmax,@stdlib/stats/base/max,@stdlib/stats/base/smax" -"@stdlib/stats/base/dmaxabs","@stdlib/stats/base/dmax,@stdlib/stats/base/dminabs,@stdlib/stats/base/dnanmaxabs,@stdlib/stats/base/maxabs,@stdlib/stats/base/smaxabs" +"@stdlib/stats/strided/dmax","@stdlib/stats/base/dmin,@stdlib/stats/base/dnanmax,@stdlib/stats/base/max,@stdlib/stats/base/smax" +"@stdlib/stats/base/dmaxabs","@stdlib/stats/strided/dmax,@stdlib/stats/base/dminabs,@stdlib/stats/base/dnanmaxabs,@stdlib/stats/base/maxabs,@stdlib/stats/base/smaxabs" "@stdlib/stats/base/dmaxabssorted","@stdlib/stats/base/dmaxabs,@stdlib/stats/base/dmaxsorted,@stdlib/stats/base/smaxabssorted" -"@stdlib/stats/base/dmaxsorted","@stdlib/stats/base/dmax,@stdlib/stats/base/dminsorted,@stdlib/stats/base/maxsorted,@stdlib/stats/base/smaxsorted" +"@stdlib/stats/base/dmaxsorted","@stdlib/stats/strided/dmax,@stdlib/stats/base/dminsorted,@stdlib/stats/base/maxsorted,@stdlib/stats/base/smaxsorted" "@stdlib/stats/base/dmean","@stdlib/stats/base/dnanmean,@stdlib/stats/base/mean,@stdlib/stats/base/smean" "@stdlib/stats/base/dmeankbn","@stdlib/stats/base/dmean,@stdlib/stats/base/meankbn,@stdlib/stats/base/smeankbn" "@stdlib/stats/base/dmeankbn2","@stdlib/stats/base/dmean,@stdlib/stats/base/meankbn2,@stdlib/stats/base/smeankbn2" @@ -1072,8 +1072,8 @@ "@stdlib/stats/base/dmeanvarpn","@stdlib/stats/base/dmeanpn,@stdlib/stats/base/dmeanstdevpn,@stdlib/stats/base/dmeanvar,@stdlib/stats/base/dvariancepn" "@stdlib/stats/base/dmeanwd","@stdlib/stats/base/dmean,@stdlib/stats/base/dnanmeanwd,@stdlib/stats/base/meanwd,@stdlib/stats/base/smeanwd" "@stdlib/stats/base/dmediansorted","@stdlib/stats/base/dmean,@stdlib/stats/base/mediansorted,@stdlib/stats/base/smediansorted" -"@stdlib/stats/base/dmidrange","@stdlib/stats/base/dmax,@stdlib/stats/base/dmean,@stdlib/stats/base/dmin,@stdlib/stats/base/drange,@stdlib/stats/base/smidrange" -"@stdlib/stats/base/dmin","@stdlib/stats/base/dmax,@stdlib/stats/base/dnanmin,@stdlib/stats/base/min,@stdlib/stats/base/smin" +"@stdlib/stats/base/dmidrange","@stdlib/stats/strided/dmax,@stdlib/stats/base/dmean,@stdlib/stats/base/dmin,@stdlib/stats/base/drange,@stdlib/stats/base/smidrange" +"@stdlib/stats/base/dmin","@stdlib/stats/strided/dmax,@stdlib/stats/base/dnanmin,@stdlib/stats/base/min,@stdlib/stats/base/smin" "@stdlib/stats/base/dminabs","@stdlib/stats/base/dmin,@stdlib/stats/base/dmaxabs,@stdlib/stats/base/dnanminabs,@stdlib/stats/base/minabs,@stdlib/stats/base/sminabs" "@stdlib/stats/base/dminsorted","@stdlib/stats/base/dmin,@stdlib/stats/base/dmaxsorted,@stdlib/stats/base/minsorted,@stdlib/stats/base/sminsorted" "@stdlib/math/strided/special/dmskabs","@stdlib/math/strided/special/dabs,@stdlib/math/strided/special/dmskabs2,@stdlib/math/strided/special/smskabs" @@ -1085,7 +1085,7 @@ "@stdlib/math/strided/special/dmskinv","@stdlib/math/strided/special/dinv,@stdlib/math/strided/special/smskinv" "@stdlib/strided/base/dmskmap","@stdlib/strided/base/dmap,@stdlib/strided/base/dmskmap2,@stdlib/strided/base/mskunary,@stdlib/strided/base/smskmap" "@stdlib/strided/base/dmskmap2","@stdlib/strided/base/dmap2,@stdlib/strided/base/dmskmap,@stdlib/strided/base/smskmap2" -"@stdlib/stats/base/dmskmax","@stdlib/stats/base/dmax,@stdlib/stats/base/dmskmin,@stdlib/stats/base/dnanmax,@stdlib/stats/base/dnanmskmax,@stdlib/stats/base/mskmax,@stdlib/stats/base/smskmax" +"@stdlib/stats/base/dmskmax","@stdlib/stats/strided/dmax,@stdlib/stats/base/dmskmin,@stdlib/stats/base/dnanmax,@stdlib/stats/base/dnanmskmax,@stdlib/stats/base/mskmax,@stdlib/stats/base/smskmax" "@stdlib/stats/base/dmskmin","@stdlib/stats/base/dmin,@stdlib/stats/base/dmskmax,@stdlib/stats/base/dnanmin,@stdlib/stats/base/dnanmskmin,@stdlib/stats/base/mskmin,@stdlib/stats/base/smskmin" "@stdlib/math/strided/special/dmskramp","@stdlib/math/strided/special/dramp,@stdlib/math/strided/special/smskramp" "@stdlib/stats/base/dmskrange","@stdlib/stats/base/dmskmax,@stdlib/stats/base/dmskmin,@stdlib/stats/base/dnanrange,@stdlib/stats/base/drange,@stdlib/stats/base/mskrange,@stdlib/stats/base/smskrange" @@ -1094,7 +1094,7 @@ "@stdlib/math/strided/special/dmsktrunc","@stdlib/math/strided/special/dmskceil,@stdlib/math/strided/special/dmskfloor,@stdlib/math/strided/special/dtrunc,@stdlib/math/strided/special/smsktrunc" "@stdlib/blas/ext/base/dnanasum","@stdlib/blas/base/dasum,@stdlib/blas/ext/base/dasumpw" "@stdlib/blas/ext/base/dnanasumors","@stdlib/blas/ext/base/dnanasum" -"@stdlib/stats/base/dnanmax","@stdlib/stats/base/dmax,@stdlib/stats/base/dnanmin,@stdlib/stats/base/nanmax,@stdlib/stats/base/snanmax" +"@stdlib/stats/base/dnanmax","@stdlib/stats/strided/dmax,@stdlib/stats/base/dnanmin,@stdlib/stats/base/nanmax,@stdlib/stats/base/snanmax" "@stdlib/stats/base/dnanmaxabs","@stdlib/stats/base/dmaxabs,@stdlib/stats/base/dnanmax,@stdlib/stats/base/dnanminabs,@stdlib/stats/base/nanmaxabs,@stdlib/stats/base/snanmaxabs" "@stdlib/stats/base/dnanmean","@stdlib/stats/base/dmean,@stdlib/stats/base/nanmean,@stdlib/stats/base/snanmean" "@stdlib/stats/base/dnanmeanors","@stdlib/stats/base/dmeanors,@stdlib/stats/base/dnanmean,@stdlib/stats/base/nanmeanors,@stdlib/stats/base/snanmeanors" @@ -1131,7 +1131,7 @@ "@stdlib/stats/base/dnanvarianceyc","@stdlib/stats/base/dvarianceyc,@stdlib/stats/base/dnanvariance,@stdlib/stats/base/nanvarianceyc,@stdlib/stats/base/snanvarianceyc" "@stdlib/blas/base/dnrm2","@stdlib/blas/base/gnrm2,@stdlib/blas/base/snrm2" "@stdlib/math/strided/special/dramp","@stdlib/math/strided/special/ramp,@stdlib/math/strided/special/sramp" -"@stdlib/stats/base/drange","@stdlib/stats/base/dmax,@stdlib/stats/base/dmin,@stdlib/stats/base/dnanrange,@stdlib/stats/base/range,@stdlib/stats/base/srange" +"@stdlib/stats/base/drange","@stdlib/stats/strided/dmax,@stdlib/stats/base/dmin,@stdlib/stats/base/dnanrange,@stdlib/stats/base/range,@stdlib/stats/base/srange" "@stdlib/blas/ext/base/drev","@stdlib/blas/ext/base/grev,@stdlib/blas/ext/base/srev" "@stdlib/math/strided/special/drsqrt","@stdlib/math/strided/special/dsqrt,@stdlib/math/strided/special/rsqrt,@stdlib/math/strided/special/srsqrt" "@stdlib/blas/ext/base/dsapxsum","@stdlib/blas/ext/base/dapxsum,@stdlib/blas/ext/base/dssum,@stdlib/blas/ext/base/sapxsum" @@ -1237,9 +1237,9 @@ "@stdlib/blas/base/gswap","@stdlib/blas/base/dswap,@stdlib/blas/base/gcopy,@stdlib/blas/base/sswap,@stdlib/blas/gswap" "@stdlib/strided/base/map-by","@stdlib/strided/base/map-by2,@stdlib/strided/base/unary" "@stdlib/strided/base/map-by2","@stdlib/strided/base/map-by,@stdlib/strided/base/binary" -"@stdlib/stats/base/max","@stdlib/stats/base/dmax,@stdlib/stats/base/min,@stdlib/stats/base/nanmax,@stdlib/stats/base/smax" +"@stdlib/stats/base/max","@stdlib/stats/strided/dmax,@stdlib/stats/base/min,@stdlib/stats/base/nanmax,@stdlib/stats/base/smax" "@stdlib/stats/base/maxabs","@stdlib/stats/base/dmaxabs,@stdlib/stats/base/max,@stdlib/stats/base/minabs,@stdlib/stats/base/nanmaxabs,@stdlib/stats/base/smaxabs" -"@stdlib/stats/base/max-by","@stdlib/stats/base/dmax,@stdlib/stats/base/max,@stdlib/stats/base/min-by,@stdlib/stats/base/nanmax-by,@stdlib/stats/base/smax" +"@stdlib/stats/base/max-by","@stdlib/stats/strided/dmax,@stdlib/stats/base/max,@stdlib/stats/base/min-by,@stdlib/stats/base/nanmax-by,@stdlib/stats/base/smax" "@stdlib/stats/base/maxsorted","@stdlib/stats/base/dmaxsorted,@stdlib/stats/base/max,@stdlib/stats/base/minsorted,@stdlib/stats/base/smaxsorted" "@stdlib/strided/base/max-view-buffer-index","" "@stdlib/stats/base/mean","@stdlib/stats/base/dmean,@stdlib/stats/base/nanmean,@stdlib/stats/base/smean" @@ -1312,8 +1312,8 @@ "@stdlib/math/strided/special/scbrt","@stdlib/math/strided/special/dcbrt,@stdlib/math/strided/special/cbrt,@stdlib/math/strided/special/ssqrt" "@stdlib/math/strided/special/sceil","@stdlib/math/strided/special/ceil,@stdlib/math/strided/special/dceil,@stdlib/math/strided/special/sfloor,@stdlib/math/strided/special/strunc" "@stdlib/blas/base/scopy","@stdlib/blas/base/dcopy,@stdlib/blas/base/gcopy,@stdlib/blas/base/sswap" -"@stdlib/stats/base/scumax","@stdlib/stats/base/cumax,@stdlib/stats/base/dcumax,@stdlib/stats/base/scumin" -"@stdlib/stats/base/scumaxabs","@stdlib/stats/base/cumaxabs,@stdlib/stats/base/dcumaxabs,@stdlib/stats/base/scumax,@stdlib/stats/base/scuminabs" +"@stdlib/stats/base/scumax","@stdlib/stats/base/cumax,@stdlib/stats/strided/dcumax,@stdlib/stats/base/scumin" +"@stdlib/stats/base/scumaxabs","@stdlib/stats/base/cumaxabs,@stdlib/stats/strided/dcumaxabs,@stdlib/stats/base/scumax,@stdlib/stats/base/scuminabs" "@stdlib/stats/base/scumin","@stdlib/stats/base/cumin,@stdlib/stats/base/dcumin,@stdlib/stats/base/scumax" "@stdlib/stats/base/scuminabs","@stdlib/stats/base/cuminabs,@stdlib/stats/base/dcuminabs,@stdlib/stats/base/scumaxabs,@stdlib/stats/base/scumin" "@stdlib/blas/ext/base/scusum","@stdlib/blas/ext/base/dcusum,@stdlib/blas/ext/base/gcusum,@stdlib/blas/ext/base/scusumpw" @@ -1339,7 +1339,7 @@ "@stdlib/math/strided/special/sinv","@stdlib/math/strided/special/dinv,@stdlib/math/strided/special/inv" "@stdlib/strided/base/smap","@stdlib/strided/base/dmap,@stdlib/strided/base/unary" "@stdlib/strided/base/smap2","@stdlib/strided/base/dmap2,@stdlib/strided/base/binary" -"@stdlib/stats/base/smax","@stdlib/stats/base/dmax,@stdlib/stats/base/max,@stdlib/stats/base/smin,@stdlib/stats/base/snanmax" +"@stdlib/stats/base/smax","@stdlib/stats/strided/dmax,@stdlib/stats/base/max,@stdlib/stats/base/smin,@stdlib/stats/base/snanmax" "@stdlib/stats/base/smaxabs","@stdlib/stats/base/dmaxabs,@stdlib/stats/base/maxabs,@stdlib/stats/base/smax,@stdlib/stats/base/sminabs,@stdlib/stats/base/snanmaxabs" "@stdlib/stats/base/smaxabssorted","@stdlib/stats/base/dmaxabssorted,@stdlib/stats/base/smaxabs,@stdlib/stats/base/smaxsorted" "@stdlib/stats/base/smaxsorted","@stdlib/stats/base/dmaxsorted,@stdlib/stats/base/maxsorted,@stdlib/stats/base/smax,@stdlib/stats/base/sminsorted" diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json index 03e6ea89cd6e..9928b10f6a84 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv index 844122eac6b9..05f9e3697504 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv @@ -1038,8 +1038,8 @@ "@stdlib/math/strided/special/dcbrt","@stdlib/math-strided-special-dcbrt" "@stdlib/math/strided/special/dceil","@stdlib/math-strided-special-dceil" "@stdlib/blas/base/dcopy","@stdlib/blas-base-dcopy" -"@stdlib/stats/base/dcumax","@stdlib/stats-base-dcumax" -"@stdlib/stats/base/dcumaxabs","@stdlib/stats-base-dcumaxabs" +"@stdlib/stats/strided/dcumax","@stdlib/stats-strided-dcumax" +"@stdlib/stats/strided/dcumaxabs","@stdlib/stats-base-dcumaxabs" "@stdlib/stats/base/dcumin","@stdlib/stats-base-dcumin" "@stdlib/stats/base/dcuminabs","@stdlib/stats-base-dcuminabs" "@stdlib/blas/ext/base/dcusum","@stdlib/blas-ext-base-dcusum" @@ -1054,7 +1054,7 @@ "@stdlib/math/strided/special/dinv","@stdlib/math-strided-special-dinv" "@stdlib/strided/base/dmap","@stdlib/strided-base-dmap" "@stdlib/strided/base/dmap2","@stdlib/strided-base-dmap2" -"@stdlib/stats/base/dmax","@stdlib/stats-base-dmax" +"@stdlib/stats/strided/dmax","@stdlib/stats-strided-dmax" "@stdlib/stats/base/dmaxabs","@stdlib/stats-base-dmaxabs" "@stdlib/stats/base/dmaxabssorted","@stdlib/stats-base-dmaxabssorted" "@stdlib/stats/base/dmaxsorted","@stdlib/stats-base-dmaxsorted" diff --git a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json index 62c0170ca24e..1fb331867dfb 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv index 33280ae5cf90..529e8a6789af 100644 --- a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv @@ -1038,8 +1038,8 @@ "@stdlib/math-strided-special-dcbrt","@stdlib/math/strided/special/dcbrt" "@stdlib/math-strided-special-dceil","@stdlib/math/strided/special/dceil" "@stdlib/blas-base-dcopy","@stdlib/blas/base/dcopy" -"@stdlib/stats-base-dcumax","@stdlib/stats/base/dcumax" -"@stdlib/stats-base-dcumaxabs","@stdlib/stats/base/dcumaxabs" +"@stdlib/stats-strided-dcumax","@stdlib/stats/strided/dcumax" +"@stdlib/stats-base-dcumaxabs","@stdlib/stats/strided/dcumaxabs" "@stdlib/stats-base-dcumin","@stdlib/stats/base/dcumin" "@stdlib/stats-base-dcuminabs","@stdlib/stats/base/dcuminabs" "@stdlib/blas-ext-base-dcusum","@stdlib/blas/ext/base/dcusum" @@ -1054,7 +1054,7 @@ "@stdlib/math-strided-special-dinv","@stdlib/math/strided/special/dinv" "@stdlib/strided-base-dmap","@stdlib/strided/base/dmap" "@stdlib/strided-base-dmap2","@stdlib/strided/base/dmap2" -"@stdlib/stats-base-dmax","@stdlib/stats/base/dmax" +"@stdlib/stats-strided-dmax","@stdlib/stats/strided/dmax" "@stdlib/stats-base-dmaxabs","@stdlib/stats/base/dmaxabs" "@stdlib/stats-base-dmaxabssorted","@stdlib/stats/base/dmaxabssorted" "@stdlib/stats-base-dmaxsorted","@stdlib/stats/base/dmaxsorted" diff --git a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json index 846f60e8c5db..58033e9ba4d8 100644 --- a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ndarray/base/README.md b/lib/node_modules/@stdlib/ndarray/base/README.md index c49f1b645504..714f6da02544 100644 --- a/lib/node_modules/@stdlib/ndarray/base/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/README.md @@ -98,6 +98,7 @@ var o = ns; - [`nextCartesianIndex( shape, order, idx, dim )`][@stdlib/ndarray/base/next-cartesian-index]: return the next Cartesian index (i.e., set of subscripts/dimension indices). - [`nonsingletonDimensions( shape )`][@stdlib/ndarray/base/nonsingleton-dimensions]: return the number of non-singleton dimensions. - [`normalizeIndex( idx, max )`][@stdlib/ndarray/base/normalize-index]: normalize an index to the interval `[0,max]`. +- [`normalizeIndices( indices, max )`][@stdlib/ndarray/base/normalize-indices]: normalize a list of indices to the interval `[0,max]`. - [`nullaryLoopOrder( shape, stridesX )`][@stdlib/ndarray/base/nullary-loop-interchange-order]: reorder ndarray dimensions and associated strides for loop interchange. - [`nullaryBlockSize( dtypeX )`][@stdlib/ndarray/base/nullary-tiling-block-size]: resolve a loop block size for multi-dimensional array tiled loops. - [`nullary( arrays, fcn )`][@stdlib/ndarray/base/nullary]: apply a nullary callback and assign results to elements in an output ndarray. @@ -124,13 +125,16 @@ var o = ns; - [`sliceFrom( x, start, strict, writable )`][@stdlib/ndarray/base/slice-from]: return a shifted view of an input ndarray. - [`sliceTo( x, stop, strict, writable )`][@stdlib/ndarray/base/slice-to]: return a truncated view of an input ndarray. - [`slice( x, slice, strict, writable )`][@stdlib/ndarray/base/slice]: return a view of an input ndarray. +- [`spreadDimensions( ndims, x, dims )`][@stdlib/ndarray/base/spread-dimensions]: expand the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. - [`stride( x, dim )`][@stdlib/ndarray/base/stride]: return the stride along a specified dimension for a provided ndarray. - [`strides( x, copy )`][@stdlib/ndarray/base/strides]: return the strides of a provided ndarray. - [`strides2offset( shape, strides )`][@stdlib/ndarray/base/strides2offset]: determine the index offset which specifies the location of the first indexed value in a multidimensional array based on a stride array. - [`strides2order( strides )`][@stdlib/ndarray/base/strides2order]: determine the order of a multidimensional array based on a provided stride array. - [`sub2ind( shape, strides, offset, ...subscripts, mode )`][@stdlib/ndarray/base/sub2ind]: convert subscripts to a linear index. - [`ndarray2array( buffer, shape, strides, offset, order )`][@stdlib/ndarray/base/to-array]: convert an ndarray buffer to a generic array. +- [`toNormalizedIndices( indices, max )`][@stdlib/ndarray/base/to-normalized-indices]: normalize a list of indices to the interval `[0,max]`. - [`toReversed( x )`][@stdlib/ndarray/base/to-reversed]: return a new ndarray where the order of elements of an input ndarray is reversed along each dimension. +- [`toUniqueNormalizedIndices( indices, max )`][@stdlib/ndarray/base/to-unique-normalized-indices]: return a list of unique indices after normalizing to the interval `[0,max]`. - [`transpose( x )`][@stdlib/ndarray/base/transpose]: transpose a matrix (or a stack of matrices). - [`unaryBy( arrays, fcn, clbk[, thisArg] )`][@stdlib/ndarray/base/unary-by]: apply a unary function to each element in an input ndarray according to a callback function and assign results to elements in an output ndarray. - [`unaryLoopOrder( shape, stridesX, stridesY )`][@stdlib/ndarray/base/unary-loop-interchange-order]: reorder ndarray dimensions and associated strides for loop interchange. @@ -307,6 +311,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/normalize-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/normalize-index +[@stdlib/ndarray/base/normalize-indices]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/normalize-indices + [@stdlib/ndarray/base/nullary-loop-interchange-order]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/nullary-loop-interchange-order [@stdlib/ndarray/base/nullary-tiling-block-size]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/nullary-tiling-block-size @@ -359,6 +365,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/slice +[@stdlib/ndarray/base/spread-dimensions]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/spread-dimensions + [@stdlib/ndarray/base/stride]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/stride [@stdlib/ndarray/base/strides]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/strides @@ -371,8 +379,12 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/to-array]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/to-array +[@stdlib/ndarray/base/to-normalized-indices]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/to-normalized-indices + [@stdlib/ndarray/base/to-reversed]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/to-reversed +[@stdlib/ndarray/base/to-unique-normalized-indices]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/to-unique-normalized-indices + [@stdlib/ndarray/base/transpose]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/transpose [@stdlib/ndarray/base/unary-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/unary-by diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/README.md b/lib/node_modules/@stdlib/ndarray/base/assert/README.md index 2344a4b7302a..01c15fcee8fe 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assert/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/assert/README.md @@ -50,6 +50,7 @@ var o = ns; - [`isBufferLengthCompatible( len, shape, strides, offset )`][@stdlib/ndarray/base/assert/is-buffer-length-compatible]: determine if a buffer length is compatible with ndarray meta data. - [`isCastingMode( value )`][@stdlib/ndarray/base/assert/is-casting-mode]: test if an input value is a supported ndarray casting mode. - [`isColumnMajorContiguous( shape, strides, offset )`][@stdlib/ndarray/base/assert/is-column-major-contiguous]: determine if an array is column-major contiguous. +- [`isColumnMajorString( value )`][@stdlib/ndarray/base/assert/is-column-major-string]: test whether an input value is the string representing column-major order. - [`isColumnMajor( strides )`][@stdlib/ndarray/base/assert/is-column-major]: given a stride array, determine whether an array is column-major. - [`isComplexFloatingPointDataType( value )`][@stdlib/ndarray/base/assert/is-complex-floating-point-data-type]: test if an input value is a supported ndarray complex-valued floating-point data type. - [`isContiguous( shape, strides, offset )`][@stdlib/ndarray/base/assert/is-contiguous]: determine if an array is contiguous. @@ -64,6 +65,7 @@ var o = ns; - [`isRealDataType( value )`][@stdlib/ndarray/base/assert/is-real-data-type]: test if an input value is a supported ndarray real-valued data type. - [`isRealFloatingPointDataType( value )`][@stdlib/ndarray/base/assert/is-real-floating-point-data-type]: test if an input value is a supported ndarray real-valued floating-point data type. - [`isRowMajorContiguous( shape, strides, offset )`][@stdlib/ndarray/base/assert/is-row-major-contiguous]: determine if an array is row-major contiguous. +- [`isRowMajorString( value )`][@stdlib/ndarray/base/assert/is-row-major-string]: test whether an input value is the string representing row-major order. - [`isRowMajor( strides )`][@stdlib/ndarray/base/assert/is-row-major]: given a stride array, determine whether an array is row-major. - [`isSafeDataTypeCast( from, to )`][@stdlib/ndarray/base/assert/is-safe-data-type-cast]: determine whether an ndarray data type can be safely cast to another ndarray data type. - [`isSameKindDataTypeCast( from, to )`][@stdlib/ndarray/base/assert/is-same-kind-data-type-cast]: determine whether an ndarray data type can be safely cast to, or is of the same "kind" as, another ndarray data type. @@ -126,6 +128,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/assert/is-column-major-contiguous]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-column-major-contiguous +[@stdlib/ndarray/base/assert/is-column-major-string]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-column-major-string + [@stdlib/ndarray/base/assert/is-column-major]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-column-major [@stdlib/ndarray/base/assert/is-complex-floating-point-data-type]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-complex-floating-point-data-type @@ -154,6 +158,8 @@ console.log( objectKeys( ns ) ); [@stdlib/ndarray/base/assert/is-row-major-contiguous]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-row-major-contiguous +[@stdlib/ndarray/base/assert/is-row-major-string]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-row-major-string + [@stdlib/ndarray/base/assert/is-row-major]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-row-major [@stdlib/ndarray/base/assert/is-safe-data-type-cast]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/assert/is-safe-data-type-cast diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/assert/docs/types/index.d.ts index 1d7dd395fa53..dac43c256839 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assert/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ndarray/base/assert/docs/types/index.d.ts @@ -28,6 +28,7 @@ import isBufferLengthCompatibleShape = require( '@stdlib/ndarray/base/assert/is- import isCastingMode = require( '@stdlib/ndarray/base/assert/is-casting-mode' ); import isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major' ); import isColumnMajorContiguous = require( '@stdlib/ndarray/base/assert/is-column-major-contiguous' ); +import isColumnMajorString = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); import isComplexFloatingPointDataType = require( '@stdlib/ndarray/base/assert/is-complex-floating-point-data-type' ); import isContiguous = require( '@stdlib/ndarray/base/assert/is-contiguous' ); import isDataType = require( '@stdlib/ndarray/base/assert/is-data-type' ); @@ -42,6 +43,7 @@ import isRealDataType = require( '@stdlib/ndarray/base/assert/is-real-data-type' import isRealFloatingPointDataType = require( '@stdlib/ndarray/base/assert/is-real-floating-point-data-type' ); import isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' ); import isRowMajorContiguous = require( '@stdlib/ndarray/base/assert/is-row-major-contiguous' ); +import isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); import isSafeDataTypeCast = require( '@stdlib/ndarray/base/assert/is-safe-data-type-cast' ); import isSameKindDataTypeCast = require( '@stdlib/ndarray/base/assert/is-same-kind-data-type-cast' ); import isSignedIntegerDataType = require( '@stdlib/ndarray/base/assert/is-signed-integer-data-type' ); @@ -262,6 +264,24 @@ interface Namespace { */ isColumnMajorContiguous: typeof isColumnMajorContiguous; + /** + * Tests whether an input value is the string representing column-major order. + * + * @param v - value to test + * @returns boolean result + * + * @example + * var bool = ns.isColumnMajorString( 'column-major' ); + * // returns true + * + * bool = ns.isColumnMajorString( 'row-major' ); + * // returns false + * + * bool = ns.isColumnMajorString( 'foo' ); + * // returns false + */ + isColumnMajorString: typeof isColumnMajorString; + /** * Tests whether an input value is a supported ndarray complex-valued floating-point data type. * @@ -747,6 +767,24 @@ interface Namespace { */ isRowMajorContiguous: typeof isRowMajorContiguous; + /** + * Tests whether an input value is the string representing row-major order. + * + * @param v - value to test + * @returns boolean result + * + * @example + * var bool = ns.isRowMajorString( 'row-major' ); + * // returns true + * + * bool = ns.isRowMajorString( 'column-major' ); + * // returns false + * + * bool = ns.isRowMajorString( 'foo' ); + * // returns false + */ + isRowMajorString: typeof isRowMajorString; + /** * Returns a boolean indicating if a provided ndarray data type can be safely cast to another ndarray data type. * diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/README.md b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/README.md new file mode 100644 index 000000000000..f9092ee4d04a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/README.md @@ -0,0 +1,117 @@ + + +# isColumnMajorString + +> Test whether an input value is the string representing column-major order. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var isColumnMajorString = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); +``` + +#### isColumnMajorString( value ) + +Test whether an input value is the string representing column-major order. + +```javascript +var bool = isColumnMajorString( 'column-major' ); +// returns true + +bool = isColumnMajorString( 'row-major' ); +// returns false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var isColumnMajorString = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); + +var bool = isColumnMajorString( 'column-major' ); +// returns true + +bool = isColumnMajorString( 'row-major' ); +// returns false + +bool = isColumnMajorString( '' ); +// returns false + +bool = isColumnMajorString( 'foo' ); +// returns false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/benchmark/benchmark.js new file mode 100644 index 000000000000..9536f88dd670 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/benchmark/benchmark.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var isColumnMajorString = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var v; + var i; + + values = [ + 'row-major', + 'column-major', + 'c', + 'fortran', + 'foo', + 'bar', + '', + 'beep', + 'boop' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = values[ i%values.length ]; + out = isColumnMajorString( v ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( out ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/repl.txt new file mode 100644 index 000000000000..830c9907e43a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( value ) + Tests whether an input value is the string representing column-major order. + + Parameters + ---------- + value: any + Value to test. + + Returns + ------- + bool: boolean + Boolean result. + + Examples + -------- + > var bool = {{alias}}( 'column-major' ) + true + > bool = {{alias}}( 'row-major' ) + false + > bool = {{alias}}( '' ) + false + > bool = {{alias}}( 'beep' ) + false + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/types/index.d.ts new file mode 100644 index 000000000000..8eb3597da51d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/types/index.d.ts @@ -0,0 +1,42 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Tests whether an input value is the string representing column-major order. +* +* @param v - value to test +* @returns boolean result +* +* @example +* var bool = isColumnMajorString( 'column-major' ); +* // returns true +* +* bool = isColumnMajorString( 'row-major' ); +* // returns false +* +* bool = isColumnMajorString( 'foo' ); +* // returns false +*/ +declare function isColumnMajorString( v: any ): v is 'column-major'; + + +// EXPORTS // + +export = isColumnMajorString; diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/types/test.ts new file mode 100644 index 000000000000..60d389341be4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/docs/types/test.ts @@ -0,0 +1,34 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isColumnMajorString = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isColumnMajorString( 'column-major' ); // $ExpectType boolean + isColumnMajorString( 'foo' ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isColumnMajorString(); // $ExpectError + isColumnMajorString( undefined, 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/examples/index.js new file mode 100644 index 000000000000..3e64c57f9191 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var isColumnMajorString = require( './../lib' ); + +var bool = isColumnMajorString( 'column-major' ); +console.log( bool ); +// => true + +bool = isColumnMajorString( 'row-major' ); +console.log( bool ); +// => false + +bool = isColumnMajorString( '' ); +console.log( bool ); +// => false + +bool = isColumnMajorString( 'foo' ); +console.log( bool ); +// => false diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/lib/index.js new file mode 100644 index 000000000000..2f7b79f1c99b --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/lib/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test whether an input value is the string representing column-major order. +* +* @module @stdlib/ndarray/base/assert/is-column-major-string +* +* @example +* var isColumnMajorString = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); +* +* var bool = isColumnMajorString( 'column-major' ); +* // returns true +* +* bool = isColumnMajorString( 'row-major' ); +* // returns false +* +* bool = isColumnMajorString( 'foo' ); +* // returns false +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/lib/main.js new file mode 100644 index 000000000000..f9f7935b486c --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/lib/main.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Tests whether an input value is the string representing column-major order. +* +* @param {*} v - value to test +* @returns {boolean} boolean result +* +* @example +* var bool = isColumnMajorString( 'column-major' ); +* // returns true +* +* bool = isColumnMajorString( 'row-major' ); +* // returns false +* +* bool = isColumnMajorString( 'foo' ); +* // returns false +*/ +function isColumnMajorString( v ) { + return ( v === 'column-major' ); +} + + +// EXPORTS // + +module.exports = isColumnMajorString; diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/package.json b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/package.json new file mode 100644 index 000000000000..3d6417cae4a1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/package.json @@ -0,0 +1,81 @@ +{ + "name": "@stdlib/ndarray/base/assert/is-column-major-string", + "version": "0.0.0", + "description": "Test whether an input value is the string representing column-major order.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "order", + "row-major", + "column-major", + "c", + "fortran", + "layout", + "memory", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util", + "assert", + "test", + "check", + "is", + "valid", + "validate", + "validation", + "isvalid", + "isorder" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/test/test.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/test/test.js new file mode 100644 index 000000000000..47c16626f13f --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-column-major-string/test/test.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isColumnMajorString = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof isColumnMajorString, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `true` if provided "column-major"', function test( t ) { + var values; + var bool; + var i; + + values = [ + 'column-major' + ]; + for ( i = 0; i < values.length; i++ ) { + bool = isColumnMajorString( values[ i ] ); + t.strictEqual( bool, true, 'returns expected value when provided '+values[ i ] ); + } + t.end(); +}); + +tape( 'the function returns `false` if not provided "column-major"', function test( t ) { + var values; + var bool; + var i; + + values = [ + 'row-major', + 'c', + 'fortran', + 'c-style', + 'fortran-style', + '', + 'beep', + 'boop', + 'foo', + 'bar', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + bool = isColumnMajorString( values[ i ] ); + t.strictEqual( bool, false, 'returns expected value when provided '+values[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-order/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-order/benchmark/benchmark.js index 9dce62a9fef8..5b594ab33098 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assert/is-order/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-order/benchmark/benchmark.js @@ -21,8 +21,6 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var pkg = require( './../package.json' ).name; var isOrder = require( './../lib' ); @@ -50,7 +48,7 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = values[ floor( randu()*values.length ) ]; + v = values[ i%values.length ]; out = isOrder( v ); if ( typeof out !== 'boolean' ) { b.fail( 'should return a boolean' ); diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-order/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-order/lib/main.js index 5112c5ee1fa9..74f9b13c4a5f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assert/is-order/lib/main.js +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-order/lib/main.js @@ -20,20 +20,17 @@ // MODULES // +var contains = require( '@stdlib/array/base/assert/contains' ).factory; var orders = require( '@stdlib/ndarray/orders' ); -// VARIABLES // - -var ORDERS = orders(); -var len = ORDERS.length; - - // MAIN // /** * Tests whether an input value is an ndarray order. * +* @name isOrder +* @type {Function} * @param {*} v - value to test * @returns {boolean} boolean indicating whether an input value is an ndarray order * @@ -47,15 +44,7 @@ var len = ORDERS.length; * bool = isOrder( 'foo' ); * // returns false */ -function isOrder( v ) { - var i; - for ( i = 0; i < len; i++ ) { - if ( v === ORDERS[ i ] ) { - return true; - } - } - return false; -} +var isOrder = contains( orders() ); // EXPORTS // diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/README.md b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/README.md new file mode 100644 index 000000000000..b0d4dabffc84 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/README.md @@ -0,0 +1,117 @@ + + +# isRowMajorString + +> Test whether an input value is the string representing row-major order. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); +``` + +#### isRowMajorString( value ) + +Test whether an input value is the string representing row-major order. + +```javascript +var bool = isRowMajorString( 'row-major' ); +// returns true + +bool = isRowMajorString( 'column-major' ); +// returns false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); + +var bool = isRowMajorString( 'row-major' ); +// returns true + +bool = isRowMajorString( 'column-major' ); +// returns false + +bool = isRowMajorString( '' ); +// returns false + +bool = isRowMajorString( 'foo' ); +// returns false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/benchmark/benchmark.js new file mode 100644 index 000000000000..e0f66e83ab6a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/benchmark/benchmark.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var isRowMajorString = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var v; + var i; + + values = [ + 'row-major', + 'column-major', + 'c', + 'fortran', + 'foo', + 'bar', + '', + 'beep', + 'boop' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = values[ i%values.length ]; + out = isRowMajorString( v ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( out ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/repl.txt new file mode 100644 index 000000000000..948385d8e3ed --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( value ) + Tests whether an input value is the string representing row-major order. + + Parameters + ---------- + value: any + Value to test. + + Returns + ------- + bool: boolean + Boolean result. + + Examples + -------- + > var bool = {{alias}}( 'row-major' ) + true + > bool = {{alias}}( 'column-major' ) + false + > bool = {{alias}}( '' ) + false + > bool = {{alias}}( 'beep' ) + false + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/types/index.d.ts new file mode 100644 index 000000000000..3303fe0ea2c1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/types/index.d.ts @@ -0,0 +1,42 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Tests whether an input value is the string representing row-major order. +* +* @param v - value to test +* @returns boolean result +* +* @example +* var bool = isRowMajorString( 'row-major' ); +* // returns true +* +* bool = isRowMajorString( 'column-major' ); +* // returns false +* +* bool = isRowMajorString( 'foo' ); +* // returns false +*/ +declare function isRowMajorString( v: any ): v is 'row-major'; + + +// EXPORTS // + +export = isRowMajorString; diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/types/test.ts new file mode 100644 index 000000000000..ae4ca4ecbe79 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/docs/types/test.ts @@ -0,0 +1,34 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isRowMajorString = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isRowMajorString( 'row-major' ); // $ExpectType boolean + isRowMajorString( 'foo' ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isRowMajorString(); // $ExpectError + isRowMajorString( undefined, 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/examples/index.js new file mode 100644 index 000000000000..b1fb05f3ecef --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var isRowMajorString = require( './../lib' ); + +var bool = isRowMajorString( 'row-major' ); +console.log( bool ); +// => true + +bool = isRowMajorString( 'column-major' ); +console.log( bool ); +// => false + +bool = isRowMajorString( '' ); +console.log( bool ); +// => false + +bool = isRowMajorString( 'foo' ); +console.log( bool ); +// => false diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/lib/index.js new file mode 100644 index 000000000000..3b660442b966 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/lib/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test whether an input value is the string representing row-major order. +* +* @module @stdlib/ndarray/base/assert/is-row-major-string +* +* @example +* var isRowMajorString = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); +* +* var bool = isRowMajorString( 'row-major' ); +* // returns true +* +* bool = isRowMajorString( 'column-major' ); +* // returns false +* +* bool = isRowMajorString( 'foo' ); +* // returns false +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/lib/main.js new file mode 100644 index 000000000000..c972a4639a2c --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/lib/main.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Tests whether an input value is the string representing row-major order. +* +* @param {*} v - value to test +* @returns {boolean} boolean result +* +* @example +* var bool = isRowMajorString( 'row-major' ); +* // returns true +* +* bool = isRowMajorString( 'column-major' ); +* // returns false +* +* bool = isRowMajorString( 'foo' ); +* // returns false +*/ +function isRowMajorString( v ) { + return ( v === 'row-major' ); +} + + +// EXPORTS // + +module.exports = isRowMajorString; diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/package.json b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/package.json new file mode 100644 index 000000000000..f235d17ebc81 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/package.json @@ -0,0 +1,81 @@ +{ + "name": "@stdlib/ndarray/base/assert/is-row-major-string", + "version": "0.0.0", + "description": "Test whether an input value is the string representing row-major order.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "order", + "row-major", + "column-major", + "c", + "fortran", + "layout", + "memory", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util", + "assert", + "test", + "check", + "is", + "valid", + "validate", + "validation", + "isvalid", + "isorder" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/test/test.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/test/test.js new file mode 100644 index 000000000000..51d74d416016 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major-string/test/test.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isRowMajorString = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof isRowMajorString, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `true` if provided "row-major"', function test( t ) { + var values; + var bool; + var i; + + values = [ + 'row-major' + ]; + for ( i = 0; i < values.length; i++ ) { + bool = isRowMajorString( values[ i ] ); + t.strictEqual( bool, true, 'returns expected value when provided '+values[ i ] ); + } + t.end(); +}); + +tape( 'the function returns `false` if not provided "row-major"', function test( t ) { + var values; + var bool; + var i; + + values = [ + 'column-major', + 'c', + 'fortran', + 'c-style', + 'fortran-style', + '', + 'beep', + 'boop', + 'foo', + 'bar', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + bool = isRowMajorString( values[ i ] ); + t.strictEqual( bool, false, 'returns expected value when provided '+values[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/assert/lib/index.js index 4bc0c830fd81..8aab1e02a9a3 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assert/lib/index.js +++ b/lib/node_modules/@stdlib/ndarray/base/assert/lib/index.js @@ -108,6 +108,15 @@ setReadOnly( ns, 'isColumnMajor', require( '@stdlib/ndarray/base/assert/is-colum */ setReadOnly( ns, 'isColumnMajorContiguous', require( '@stdlib/ndarray/base/assert/is-column-major-contiguous' ) ); +/** +* @name isColumnMajorString +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/assert/is-column-major-string} +*/ +setReadOnly( ns, 'isColumnMajorString', require( '@stdlib/ndarray/base/assert/is-column-major-string' ) ); + /** * @name isComplexFloatingPointDataType * @memberof ns @@ -234,6 +243,15 @@ setReadOnly( ns, 'isRowMajor', require( '@stdlib/ndarray/base/assert/is-row-majo */ setReadOnly( ns, 'isRowMajorContiguous', require( '@stdlib/ndarray/base/assert/is-row-major-contiguous' ) ); +/** +* @name isRowMajorString +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/assert/is-row-major-string} +*/ +setReadOnly( ns, 'isRowMajorString', require( '@stdlib/ndarray/base/assert/is-row-major-string' ) ); + /** * @name isSafeDataTypeCast * @memberof ns diff --git a/lib/node_modules/@stdlib/ndarray/base/assign/lib/9d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/assign/lib/9d_blocked_accessors.js index b6348cfbc07e..57f5f81938f6 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assign/lib/9d_blocked_accessors.js +++ b/lib/node_modules/@stdlib/ndarray/base/assign/lib/9d_blocked_accessors.js @@ -47,7 +47,7 @@ var blockSize = require( '@stdlib/ndarray/base/unary-tiling-block-size' ); * @param {IntegerArray} y.strides - stride lengths * @param {NonNegativeInteger} y.offset - index offset * @param {string} y.order - specifies whether `y` is row-major (C-style) or column-major (Fortran-style) -* @param {Array} x.accessors - data buffer accessors +* @param {Array} y.accessors - data buffer accessors * @returns {void} * * @example diff --git a/lib/node_modules/@stdlib/ndarray/base/assign/src/dispatch.c b/lib/node_modules/@stdlib/ndarray/base/assign/src/dispatch.c index fe33a3d33a72..339f72754322 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assign/src/dispatch.c +++ b/lib/node_modules/@stdlib/ndarray/base/assign/src/dispatch.c @@ -105,7 +105,7 @@ static int8_t stdlib_ndarray_unary_assign_1d_flatten( const ndarrayUnaryAssignFc int64_t sh[] = { N }; // Shallow copy and reshape the arrays... - int64_t sx1[] = { s2 }; + int64_t sx1[] = { s1 }; struct ndarray *x1c = stdlib_ndarray_allocate( stdlib_ndarray_dtype( x1 ), stdlib_ndarray_data( x1 ), @@ -245,6 +245,8 @@ static int8_t stdlib_ndarray_unary_assign_1d_flatten( const ndarrayUnaryAssignFc * } */ int8_t stdlib_ndarray_unary_assign_dispatch( const struct ndarrayUnaryAssignDispatchObject *obj, struct ndarray *arrays[] ) { + const int64_t *sh1; + const int64_t *sh2; struct ndarray *x1; struct ndarray *x2; int8_t status; @@ -253,8 +255,6 @@ int8_t stdlib_ndarray_unary_assign_dispatch( const struct ndarrayUnaryAssignDisp int64_t mab2; int64_t mib1; int64_t mib2; - int64_t *sh1; - int64_t *sh2; int64_t *s1; int64_t *s2; int64_t len; diff --git a/lib/node_modules/@stdlib/ndarray/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/docs/types/index.d.ts index aa9f901ba0f7..c4f6ba471b97 100644 --- a/lib/node_modules/@stdlib/ndarray/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ndarray/base/docs/types/index.d.ts @@ -76,6 +76,7 @@ import ndims = require( '@stdlib/ndarray/base/ndims' ); import nextCartesianIndex = require( '@stdlib/ndarray/base/next-cartesian-index' ); import nonsingletonDimensions = require( '@stdlib/ndarray/base/nonsingleton-dimensions' ); import normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); +import normalizeIndices = require( '@stdlib/ndarray/base/normalize-indices' ); import nullary = require( '@stdlib/ndarray/base/nullary' ); import nullaryLoopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); import nullaryBlockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); @@ -102,13 +103,16 @@ import sliceDimensionFrom = require( '@stdlib/ndarray/base/slice-dimension-from' import sliceDimensionTo = require( '@stdlib/ndarray/base/slice-dimension-to' ); import sliceFrom = require( '@stdlib/ndarray/base/slice-from' ); import sliceTo = require( '@stdlib/ndarray/base/slice-to' ); +import spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' ); import stride = require( '@stdlib/ndarray/base/stride' ); import strides = require( '@stdlib/ndarray/base/strides' ); import strides2offset = require( '@stdlib/ndarray/base/strides2offset' ); import strides2order = require( '@stdlib/ndarray/base/strides2order' ); import sub2ind = require( '@stdlib/ndarray/base/sub2ind' ); import ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +import toNormalizedIndices = require( '@stdlib/ndarray/base/to-normalized-indices' ); import toReversed = require( '@stdlib/ndarray/base/to-reversed' ); +import toUniqueNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' ); import transpose = require( '@stdlib/ndarray/base/transpose' ); import unary = require( '@stdlib/ndarray/base/unary' ); import unaryBy = require( '@stdlib/ndarray/base/unary-by' ); @@ -1865,6 +1869,27 @@ interface Namespace { */ normalizeIndex: typeof normalizeIndex; + /** + * Normalizes a list of indices to the interval `[0,max]`. + * + * ## Notes + * + * - If provided an out-of-bounds index, the function returns `null`. + * - The function mutates the input array, even when provided an out-of-bounds index. + * + * @param indices - indices + * @param max - maximum index + * @returns normalized indices or null + * + * @example + * var indices = ns.normalizeIndices( [ -2, 5 ], 10 ); + * // returns [ 9, 5 ] + * + * indices = ns.normalizeIndices( [ -2, 15 ], 10 ); + * // returns null + */ + normalizeIndices: typeof normalizeIndices; + /** * Applies a nullary callback and assigns results to elements in an output ndarray. * @@ -2662,6 +2687,48 @@ interface Namespace { */ sliceTo: typeof sliceTo; + /** + * Expands the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. + * + * ## Notes + * + * - Each provided dimension index must reside on the interval `[-ndims, ndims-1]`. If provided a negative dimension index, the position at which to place a respective dimension is computed as `ndims + index`. + * - Provided dimension indices must resolve to normalized dimension indices arranged in ascending order. + * + * @param ndims - number of dimensions in the output array + * @param x - input array + * @param dims - dimension indices + * @returns output array + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + * // returns + * + * var shx = x.shape; + * // returns [ 2, 2 ] + * + * var y = ns.spreadDimensions( 5, x, [ 1, 3 ] ); + * // returns + * + * var shy = y.shape; + * // returns [ 1, 2, 1, 2, 1 ] + * + * var v = y.get( 0, 0, 0, 0, 0 ); + * // returns 1 + * + * v = y.get( 0, 0, 0, 1, 0 ); + * // returns 2 + * + * v = y.get( 0, 1, 0, 0, 0 ); + * // returns 3 + * + * v = y.get( 0, 1, 0, 1, 0 ); + * // returns 4 + */ + spreadDimensions: typeof spreadDimensions; + /** * Returns the stride along a specified dimension for a provided ndarray. * @@ -2865,6 +2932,26 @@ interface Namespace { */ ndarray2array: typeof ndarray2array; + /** + * Normalizes a list of indices to the interval `[0,max]`. + * + * ## Notes + * + * - If provided an out-of-bounds index, the function normalizes the index to `-1`. + * + * @param indices - indices + * @param max - maximum index + * @returns normalized indices + * + * @example + * var indices = ns.toNormalizedIndices( [ -2, 5 ], 10 ); + * // returns [ 9, 5 ] + * + * indices = ns.toNormalizedIndices( [ -2, 15 ], 10 ); + * // returns [ 9, -1 ] + */ + toNormalizedIndices: typeof toNormalizedIndices; + /** * Returns a new ndarray where the order of elements of an input ndarray is reversed along each dimension. * @@ -2901,6 +2988,26 @@ interface Namespace { */ toReversed: typeof toReversed; + /** + * Returns a list of unique indices after normalizing to the interval `[0,max]`. + * + * ## Notes + * + * - If provided an out-of-bounds index, the function returns `null`. + * + * @param indices - indices + * @param max - maximum index + * @returns normalized indices (or null) + * + * @example + * var indices = ns.toUniqueNormalizedIndices( [ -2, 5 ], 10 ); + * // returns [ 9, 5 ] + * + * indices = ns.toUniqueNormalizedIndices( [ -2, 15 ], 10 ); + * // returns null + */ + toUniqueNormalizedIndices: typeof toUniqueNormalizedIndices; + /** * Transposes a matrix (or a stack of matrices). * diff --git a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js index 645f1e360de7..4968bb7c19ab 100644 --- a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js +++ b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/lib/main.js @@ -20,7 +20,9 @@ // MODULES // +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); var getDType = require( '@stdlib/ndarray/base/dtype' ); var getShape = require( '@stdlib/ndarray/base/shape' ); var getStrides = require( '@stdlib/ndarray/base/strides' ); @@ -74,39 +76,42 @@ var format = require( '@stdlib/string/format' ); function expandDimensions( x, axis ) { var strides; var shape; + var isrm; var ord; var sh; var st; + var d; var N; var i; sh = getShape( x, false ); st = getStrides( x, false ); ord = getOrder( x ); + + isrm = isRowMajor( ord ); N = sh.length; strides = []; shape = []; - if ( axis < 0 ) { - if ( axis < -N-1 ) { - throw new RangeError( format( 'invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.', N, N, axis ) ); - } - axis += N + 1; - } else if ( axis > N ) { - throw new RangeError( format( 'invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.', N, N, axis ) ); + d = normalizeIndex( axis, N ); + if ( d === -1 ) { + throw new RangeError( format( 'invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.', N+1, N, axis ) ); } - if ( axis === 0 ) { + if ( d === 0 ) { // Prepend singleton dimension... shape.push( 1 ); - strides.push( st[ 0 ] ); - + if ( isrm ) { + strides.push( sh[ 0 ] * st[ 0 ] ); + } else { + strides.push( st[ 0 ] ); + } // Copy remaining dimensions... for ( i = 0; i < N; i++ ) { shape.push( sh[ i ] ); strides.push( st[ i ] ); } - } else if ( axis === N ) { + } else if ( d === N ) { // Copy dimensions... for ( i = 0; i < N; i++ ) { shape.push( sh[ i ] ); @@ -114,21 +119,25 @@ function expandDimensions( x, axis ) { } // Append singleton dimension... shape.push( 1 ); - strides.push( st[ N-1 ] ); + if ( isrm ) { + strides.push( st[ N-1 ] ); + } else { + strides.push( sh[ N-1 ] * st[ N-1 ] ); + } } else { // Insert a singleton dimension... for ( i = 0; i < N+1; i++ ) { - if ( i === axis ) { + if ( i === d ) { shape.push( 1 ); - if ( ord === 'row-major' ) { + if ( isrm ) { strides.push( st[ i-1 ] ); } else { // ord === 'column-major' strides.push( st[ i ] ); } - } else if ( i < axis ) { + } else if ( i < d ) { shape.push( sh[ i ] ); strides.push( st[ i ] ); - } else { // i > axis + } else { // i > d shape.push( sh[ i-1 ] ); strides.push( st[ i-1 ] ); } diff --git a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js index bd4b41a26571..793431c4f56f 100644 --- a/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js +++ b/lib/node_modules/@stdlib/ndarray/base/expand-dimensions/test/test.js @@ -159,7 +159,7 @@ tape( 'the function prepends singleton dimensions (base; row-major)', function t t.notEqual( y, x, 'returns expected value' ); t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); - t.deepEqual( y.strides, [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 4, 2, 1 ], 'returns expected value' ); t.strictEqual( y.data, x.data, 'returns expected value' ); t.end(); @@ -174,7 +174,7 @@ tape( 'the function prepends singleton dimensions (base; row-major; negative axi t.notEqual( y, x, 'returns expected value' ); t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); - t.deepEqual( y.strides, [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 4, 2, 1 ], 'returns expected value' ); t.strictEqual( y.data, x.data, 'returns expected value' ); t.end(); @@ -249,7 +249,7 @@ tape( 'the function appends singleton dimensions (base; column-major)', function t.notEqual( y, x, 'returns expected value' ); t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); - t.deepEqual( y.strides, [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 2, 4 ], 'returns expected value' ); t.strictEqual( y.data, x.data, 'returns expected value' ); t.end(); @@ -264,7 +264,7 @@ tape( 'the function appends singleton dimensions (base; column-major; negative i t.notEqual( y, x, 'returns expected value' ); t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); - t.deepEqual( y.strides, [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 2, 4 ], 'returns expected value' ); t.strictEqual( y.data, x.data, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/ndarray/base/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/lib/index.js index 6cec1bf38edd..6cb2c39911cb 100644 --- a/lib/node_modules/@stdlib/ndarray/base/lib/index.js +++ b/lib/node_modules/@stdlib/ndarray/base/lib/index.js @@ -544,6 +544,15 @@ setReadOnly( ns, 'nonsingletonDimensions', require( '@stdlib/ndarray/base/nonsin */ setReadOnly( ns, 'normalizeIndex', require( '@stdlib/ndarray/base/normalize-index' ) ); +/** +* @name normalizeIndices +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/normalize-indices} +*/ +setReadOnly( ns, 'normalizeIndices', require( '@stdlib/ndarray/base/normalize-indices' ) ); + /** * @name nullary * @memberof ns @@ -778,6 +787,15 @@ setReadOnly( ns, 'sliceFrom', require( '@stdlib/ndarray/base/slice-from' ) ); */ setReadOnly( ns, 'sliceTo', require( '@stdlib/ndarray/base/slice-to' ) ); +/** +* @name spreadDimensions +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/spread-dimensions} +*/ +setReadOnly( ns, 'spreadDimensions', require( '@stdlib/ndarray/base/spread-dimensions' ) ); + /** * @name stride * @memberof ns @@ -832,6 +850,15 @@ setReadOnly( ns, 'sub2ind', require( '@stdlib/ndarray/base/sub2ind' ) ); */ setReadOnly( ns, 'ndarray2array', require( '@stdlib/ndarray/base/to-array' ) ); +/** +* @name toNormalizedIndices +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/to-normalized-indices} +*/ +setReadOnly( ns, 'toNormalizedIndices', require( '@stdlib/ndarray/base/to-normalized-indices' ) ); + /** * @name toReversed * @memberof ns @@ -841,6 +868,15 @@ setReadOnly( ns, 'ndarray2array', require( '@stdlib/ndarray/base/to-array' ) ); */ setReadOnly( ns, 'toReversed', require( '@stdlib/ndarray/base/to-reversed' ) ); +/** +* @name toUniqueNormalizedIndices +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/ndarray/base/to-unique-normalized-indices} +*/ +setReadOnly( ns, 'toUniqueNormalizedIndices', require( '@stdlib/ndarray/base/to-unique-normalized-indices' ) ); + /** * @name transpose * @memberof ns diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-index/README.md b/lib/node_modules/@stdlib/ndarray/base/normalize-index/README.md index 867002ff126f..9c8028eba546 100644 --- a/lib/node_modules/@stdlib/ndarray/base/normalize-index/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-index/README.md @@ -70,6 +70,10 @@ idx = normalizeIndex( -15, 10 );
+## Notes + +- During normalization, a negative index is converted to a nonnegative index according to `max + idx + 1`. If, after normalization, the resolved index is still negative, the value is considered out-of-bounds. +
diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/README.md b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/README.md new file mode 100644 index 000000000000..7ea4faad3a95 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/README.md @@ -0,0 +1,135 @@ + + +# normalizeIndices + +> Normalize a list of indices to the interval `[0,max]`. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var normalizeIndices = require( '@stdlib/ndarray/base/normalize-indices' ); +``` + +#### normalizeIndices( indices, max ) + +Normalizes a list of indices to the interval `[0,max]`. + +```javascript +var idx = normalizeIndices( [ 2, -5 ], 10 ); +// returns [ 2, 6 ] +``` + +If provided an out-of-bounds index, the function returns `null`. + +```javascript +var idx = normalizeIndices( [ 15, -15 ], 10 ); +// returns null +``` + +
+ + + + + +
+ +## Notes + +- The function mutates the input array, even when provided an out-of-bounds index. If mutation is undesired, copy the input array before calling this function. +- During normalization, a negative index is converted to a nonnegative index according to `max + idx + 1`. If, after normalization, the resolved index is still negative, the value is considered out-of-bounds. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var normalizeIndices = require( '@stdlib/ndarray/base/normalize-indices' ); + +// Generate a list of random indices: +var idx1 = discreteUniform( 100, -20, 20, { + 'dtype': 'generic' +}); + +// Normalize each index to the interval `[0, 15]`: +var idx2 = idx1.slice(); +var out = normalizeIndices( idx2, 15 ); + +// Check whether one or more indices was invalid: +if ( out === null ) { + console.log( 'One or more indices was invalid.' ); +} + +// Print the results... +var i; +for ( i = 0; i < idx1.length; i++ ) { + console.log( '%d => [%d, %d] => %d', idx1[ i ], 0, 15, idx2[ i ] ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/benchmark/benchmark.js new file mode 100644 index 000000000000..112ba113d7f5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives; +var Int32Array = require( '@stdlib/array/int32' ); +var pkg = require( './../package.json' ).name; +var normalizeIndices = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + [ -4, -5, 4, 5 ], + new Int32Array( [ -4, -5, 4, 5 ] ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = normalizeIndices( values[ i%values.length ], 10 ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isNonNegativeIntegerArray( out ) ) { + b.fail( 'should return an array of nonnegative integers' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/repl.txt new file mode 100644 index 000000000000..25ea6b11189d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/repl.txt @@ -0,0 +1,32 @@ + +{{alias}}( indices, max ) + Normalizes indices to the interval [0,max]. + + If an index exceeds index bounds, the function returns `null`. + + The function mutates the input array, even when provided an index which + exceeds index bounds. + + Parameters + ---------- + indices: Collection + Indices to normalize. + + max: integer + Maximum index value. + + Returns + ------- + out: Collection|null + Normalized indices. + + Examples + -------- + > var idx = {{alias}}( [ 2, -5 ], 10 ) + [ 2, 6 ] + > idx = {{alias}}( [ 15 ], 10 ) + null + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/types/index.d.ts new file mode 100644 index 000000000000..6b3060f19315 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/types/index.d.ts @@ -0,0 +1,49 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Normalizes a list of indices to the interval `[0,max]`. +* +* ## Notes +* +* - If provided an out-of-bounds index, the function returns `null`. +* - The function mutates the input array, even when provided an out-of-bounds index. +* +* @param indices - indices +* @param max - maximum index +* @returns normalized indices or null +* +* @example +* var indices = normalizeIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* indices = normalizeIndices( [ -2, 15 ], 10 ); +* // returns null +*/ +declare function normalizeIndices( indices: Collection, max: number ): Collection | null; + + +// EXPORTS // + +export = normalizeIndices; diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/types/test.ts new file mode 100644 index 000000000000..fa48a4f6fa18 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import normalizeIndices = require( './index' ); + + +// TESTS // + +// The function returns a collection of numbers or `null`... +{ + normalizeIndices( [ 0, 15 ], 10 ); // $ExpectType Collection | null +} + +// The compiler throws an error if the function is provided invalid values... +{ + normalizeIndices( true, 3 ); // $ExpectError + normalizeIndices( false, 2 ); // $ExpectError + normalizeIndices( '5', 1 ); // $ExpectError + normalizeIndices( [ '5' ], 1 ); // $ExpectError + normalizeIndices( {}, 2 ); // $ExpectError + normalizeIndices( ( x: number ): number => x, 2 ); // $ExpectError + + normalizeIndices( [ 9 ], true ); // $ExpectError + normalizeIndices( [ 9 ], false ); // $ExpectError + normalizeIndices( [ 5 ], '5' ); // $ExpectError + normalizeIndices( [ 8 ], [] ); // $ExpectError + normalizeIndices( [ 9 ], {} ); // $ExpectError + normalizeIndices( [ 8 ], ( x: number ): number => x ); // $ExpectError + + normalizeIndices( [], true ); // $ExpectError + normalizeIndices( {}, false ); // $ExpectError + normalizeIndices( false, '5' ); // $ExpectError + normalizeIndices( {}, [] ); // $ExpectError + normalizeIndices( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + normalizeIndices(); // $ExpectError + normalizeIndices( [ 3 ] ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/examples/index.js new file mode 100644 index 000000000000..ef5176225998 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var normalizeIndices = require( './../lib' ); + +// Generate a list of random indices: +var idx1 = discreteUniform( 100, -20, 20, { + 'dtype': 'generic' +}); + +// Normalize each index to the interval `[0, 15]`: +var idx2 = idx1.slice(); +var out = normalizeIndices( idx2, 15 ); + +// Check whether one or more indices was invalid: +if ( out === null ) { + console.log( 'One or more indices was invalid.' ); +} + +// Print the results... +var i; +for ( i = 0; i < idx1.length; i++ ) { + console.log( '%d => [%d, %d] => %d', idx1[ i ], 0, 15, idx2[ i ] ); +} diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/lib/index.js new file mode 100644 index 000000000000..de28b5099d58 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Normalize a list of indices to the interval `[0,max]`. +* +* @module @stdlib/ndarray/base/normalize-indices +* +* @example +* var normalizeIndices = require( '@stdlib/ndarray/base/normalize-indices' ); +* +* var idx = normalizeIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* idx = normalizeIndices( [ 15 ], 10 ); +* // returns null +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/lib/main.js new file mode 100644 index 000000000000..bd3803122406 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/lib/main.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); + + +// MAIN // + +/** +* Normalizes a list of indices to the interval `[0,max]`. +* +* @param {IntegerArray} indices - indices +* @param {NonNegativeInteger} max - maximum index +* @returns {(IntegerArray|null)} normalized indices or null +* +* @example +* var idx = normalizeIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* idx = normalizeIndices( [ 15 ], 10 ); +* // returns null +*/ +function normalizeIndices( indices, max ) { + var idx; + var flg; + var i; + + for ( i = 0; i < indices.length; i++ ) { + idx = normalizeIndex( indices[ i ], max ); + if ( idx === -1 ) { + flg = null; + } + indices[ i ] = idx; + } + return ( flg === null ) ? flg : indices; +} + + +// EXPORTS // + +module.exports = normalizeIndices; diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/package.json b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/package.json new file mode 100644 index 000000000000..f64f4dd54ff6 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/ndarray/base/normalize-indices", + "version": "0.0.0", + "description": "Normalize a list of indices to the interval [0,max].", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "index", + "idx", + "ind", + "subscript", + "normalize", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/normalize-indices/test/test.js b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/test/test.js new file mode 100644 index 000000000000..43e553b06d6e --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/normalize-indices/test/test.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var normalizeIndices = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof normalizeIndices, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function normalizes a list of indices to the interval `[0,max]`', function test( t ) { + var expected; + var actual; + var idx; + + idx = [ 2, 5, 0, 7, 1, -5, -1, -2, -10, -11 ]; + expected = [ 2, 5, 0, 7, 1, 6, 10, 9, 1, 0 ]; + + actual = normalizeIndices( idx, 10 ); + t.strictEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an out-of-bounds index, the function normalizes a list of indices and returns `null`', function test( t ) { + var expected; + var actual; + var idx; + + idx = [ 15, -15 ]; + expected = [ -1, -1 ]; + + actual = normalizeIndices( idx, 10 ); + t.strictEqual( actual, null, 'returns expected value' ); + t.deepEqual( idx, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/README.md b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/README.md new file mode 100644 index 000000000000..6a029f896d14 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/README.md @@ -0,0 +1,167 @@ + + +# spreadDimensions + +> Expand the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' ); +``` + +#### spreadDimensions( ndims, x, dims ) + +Expands the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. + +```javascript +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var array = require( '@stdlib/ndarray/array' ); + +// Create a 2x2 ndarray: +var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +// returns + +// Prepend a singleton dimension: +var y = spreadDimensions( 3, x, [ 1, 2 ] ); +// returns + +var sh = y.shape; +// returns [ 1, 2, 2 ] + +var a = ndarray2array( y ); +// returns [ [ [ 1, 2 ], [ 3, 4 ] ] ] + +// Append a singleton dimension: +y = spreadDimensions( 3, x, [ 0, 1 ] ); +// returns + +sh = y.shape; +// returns [ 2, 2, 1 ] + +a = ndarray2array( y ); +// returns [ [ [ 1 ], [ 2 ] ], [ [ 3 ], [ 4 ] ] ] + +// Insert a singleton dimension: +y = spreadDimensions( 3, x, [ 0, 2 ] ); +// returns + +sh = y.shape; +// returns [ 2, 1, 2 ] + +a = ndarray2array( y ); +// returns [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ] +``` + +
+ + + + + +
+ +## Notes + +- Each provided dimension index must reside on the interval `[-ndims, ndims-1]`. If provided a negative dimension index, the position at which to place a respective dimension is computed as `ndims + index`. +- Provided dimension indices must resolve to normalized dimension indices arranged in ascending order. + +
+ + + + + +
+ +## Examples + + + +```javascript +var array = require( '@stdlib/ndarray/array' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var ind2sub = require( '@stdlib/ndarray/ind2sub' ); +var spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' ); + +// Create a 2-dimensional array: +var x = array( [ [ 1, 2 ], [ 3, 4 ] ], { + 'order': 'column-major' +}); +// returns + +// Spread dimensions: +var y = spreadDimensions( 5, x, [ 1, 3 ] ); +// returns + +// Retrieve the shape: +var sh = y.shape; +// returns [ 1, 2, 1, 2, 1 ] + +// Retrieve the number of elements: +var N = numel( sh ); + +// Loop through the array elements... +var i; +for ( i = 0; i < N; i++ ) { + console.log( 'Y[%s] = %d', ind2sub( sh, i ).join( ', ' ), y.iget( i ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/benchmark/benchmark.js new file mode 100644 index 000000000000..fbe31bbcff3e --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarrayBase = require( '@stdlib/ndarray/base/ctor' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var pkg = require( './../package.json' ).name; +var spreadDimensions = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::base_ndarray,2d', function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 2 ); + shape = [ 2 ]; + strides = [ 1 ]; + offset = 0; + order = 'row-major'; + + values = [ + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ), + ndarrayBase( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = spreadDimensions( 2, values[ i%values.length ], [ 1 ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::ndarray,2d', function benchmark( b ) { + var strides; + var values; + var buffer; + var offset; + var dtype; + var shape; + var order; + var out; + var i; + + dtype = 'float64'; + buffer = new Float64Array( 2 ); + shape = [ 2 ]; + strides = [ 1 ]; + offset = 0; + order = 'row-major'; + + values = [ + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ), + ndarray( dtype, buffer, shape, strides, offset, order ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = spreadDimensions( 2, values[ i%values.length ], [ 1 ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/benchmark/benchmark.ndims.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/benchmark/benchmark.ndims.js new file mode 100644 index 000000000000..0bffcafeb3a4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/benchmark/benchmark.ndims.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var array = require( '@stdlib/ndarray/array' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var pkg = require( './../package.json' ).name; +var spreadDimensions = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} ndims - number of dimensions +* @returns {Function} benchmark function +*/ +function createBenchmark( ndims ) { + var x = array( [ 1, 2, 3, 4 ] ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = spreadDimensions( ndims, x, [ i%ndims ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isndarrayLike( out ) ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var min; + var max; + var f; + var i; + + min = 2; + max = 10; + + for ( i = min; i <= max; i++ ) { + f = createBenchmark( i ); + bench( pkg+'::ndarray:ndims='+i, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/repl.txt new file mode 100644 index 000000000000..a635a56578fe --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/repl.txt @@ -0,0 +1,51 @@ + +{{alias}}( ndims, x, dims ) + Expands the shape of an array to a specified dimensionality by spreading its + dimensions to specified dimension indices and inserting dimensions of size + one for the remaining dimensions. + + Each provided dimension index must reside on the interval [-ndims, ndims-1]. + + If provided a negative dimension index, the position at which to place a + respective dimension is computed as `ndims + index`. + + Parameters + ---------- + ndims: integer + Number of dimensions in the output array. Must be greater than or equal + to the number of dimensions in the input array. + + x: ndarray + Input array. + + dims: ArrayLikeObject + Dimension indices specifying where to place the dimensions of the input + array. Must resolve to normalized indices arranged in ascending order. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1, 2 ], [ 3, 4 ] ] ) + + > var sh = x.shape + [ 2, 2 ] + > var y = {{alias}}( 5, x, [ 1, 3 ] ) + + > sh = y.shape + [ 1, 2, 1, 2, 1 ] + > var v = y.get( 0, 0, 0, 0, 0 ) + 1 + > v = y.get( 0, 0, 0, 1, 0 ) + 2 + > v = y.get( 0, 1, 0, 0, 0 ) + 3 + > v = y.get( 0, 1, 0, 1, 0 ) + 4 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/types/index.d.ts new file mode 100644 index 000000000000..54ab48374335 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/types/index.d.ts @@ -0,0 +1,71 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ndarray } from '@stdlib/types/ndarray'; +import { Collection } from '@stdlib/types/array'; + +/** +* Expands the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. +* +* ## Notes +* +* - Each provided dimension index must reside on the interval `[-ndims, ndims-1]`. If provided a negative dimension index, the position at which to place a respective dimension is computed as `ndims + index`. +* - Provided dimension indices must resolve to normalized dimension indices arranged in ascending order. +* +* @param ndims - number of dimensions in the output array +* @param x - input array +* @param dims - dimension indices +* @returns output array +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +* // returns +* +* var shx = x.shape; +* // returns [ 2, 2 ] +* +* var y = spreadDimensions( 5, x, [ 1, 3 ] ); +* // returns +* +* var shy = y.shape; +* // returns [ 1, 2, 1, 2, 1 ] +* +* var v = y.get( 0, 0, 0, 0, 0 ); +* // returns 1 +* +* v = y.get( 0, 0, 0, 1, 0 ); +* // returns 2 +* +* v = y.get( 0, 1, 0, 0, 0 ); +* // returns 3 +* +* v = y.get( 0, 1, 0, 1, 0 ); +* // returns 4 +*/ +declare function spreadDimensions( ndims: number, x: T, dims: Collection ): T; + + +// EXPORTS // + +export = spreadDimensions; diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/types/test.ts new file mode 100644 index 000000000000..fe1f8053323a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/docs/types/test.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import array = require( '@stdlib/ndarray/array' ); +import zeros = require( '@stdlib/ndarray/zeros' ); +import spreadDimensions = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 2, 2 ] ); + + spreadDimensions( 5, x, [ 1, 3 ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is not provided a first argument which is a number... +{ + const x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + spreadDimensions( '5', x, [ 1, 3 ] ); // $ExpectError + spreadDimensions( true, x, [ 1, 3 ] ); // $ExpectError + spreadDimensions( false, x, [ 1, 3 ] ); // $ExpectError + spreadDimensions( null, x, [ 1, 3 ] ); // $ExpectError + spreadDimensions( {}, x, [ 1, 3 ] ); // $ExpectError + spreadDimensions( [ '5' ], x, [ 1, 3 ] ); // $ExpectError + spreadDimensions( ( x: number ): number => x, x, [ 1, 3 ] ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a second argument which is an ndarray... +{ + spreadDimensions( 5, '5', [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, 5, [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, true, [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, false, [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, null, [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, {}, [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, [ '5' ], [ 1, 3 ] ); // $ExpectError + spreadDimensions( 5, ( x: number ): number => x, [ 1, 3 ] ); // $ExpectError +} + +// The compiler throws an error if the function is not provided a third argument which is an array of numbers... +{ + const x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + spreadDimensions( 5, x, '5' ); // $ExpectError + spreadDimensions( 5, x, true ); // $ExpectError + spreadDimensions( 5, x, false ); // $ExpectError + spreadDimensions( 5, x, null ); // $ExpectError + spreadDimensions( 5, x, {} ); // $ExpectError + spreadDimensions( 5, x, [ '5' ] ); // $ExpectError + spreadDimensions( 5, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + spreadDimensions(); // $ExpectError + spreadDimensions( 5, x ); // $ExpectError + spreadDimensions( 5, x, [ 1, 3 ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/examples/index.js new file mode 100644 index 000000000000..0a0d9c92b184 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/examples/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var array = require( '@stdlib/ndarray/array' ); +var numel = require( '@stdlib/ndarray/base/numel' ); +var ind2sub = require( '@stdlib/ndarray/ind2sub' ); +var spreadDimensions = require( './../lib' ); + +// Create a 2-dimensional array: +var x = array( [ [ 1, 2 ], [ 3, 4 ] ], { + 'order': 'column-major' +}); +// returns + +// Spread dimensions: +var y = spreadDimensions( 5, x, [ 1, 3 ] ); +// returns + +// Retrieve the shape: +var sh = y.shape; +// returns [ 1, 2, 1, 2, 1 ] + +// Retrieve the number of elements: +var N = numel( sh ); + +// Loop through the array elements... +var i; +for ( i = 0; i < N; i++ ) { + console.log( 'Y[%s] = %d', ind2sub( sh, i ).join( ', ' ), y.iget( i ) ); +} diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/index.js new file mode 100644 index 000000000000..9a5bd0dc0a80 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/index.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Expand the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. +* +* @module @stdlib/ndarray/base/spread-dimensions +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +* // returns +* +* var shx = x.shape; +* // returns [ 2, 2 ] +* +* var y = spreadDimensions( 5, x, [ 1, 3 ] ); +* // returns +* +* var shy = y.shape; +* // returns [ 1, 2, 1, 2, 1 ] +* +* var v = y.get( 0, 0, 0, 0, 0 ); +* // returns 1 +* +* v = y.get( 0, 0, 0, 1, 0 ); +* // returns 2 +* +* v = y.get( 0, 1, 0, 0, 0 ); +* // returns 3 +* +* v = y.get( 0, 1, 0, 1, 0 ); +* // returns 4 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js new file mode 100644 index 000000000000..62efea9b2dc3 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/lib/main.js @@ -0,0 +1,166 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); +var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var isSortedAscending = require( '@stdlib/array/base/assert/is-sorted-ascending' ); +var toNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' ); +var getDType = require( '@stdlib/ndarray/base/dtype' ); +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getOrder = require( '@stdlib/ndarray/base/order' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ones = require( '@stdlib/array/base/ones' ); +var zeros = require( '@stdlib/array/base/zeros' ); +var format = require( '@stdlib/string/format' ); + + +// MAIN // + +/** +* Expands the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions. +* +* ## Notes +* +* - Each provided dimension index must reside on the interval `[-ndims, ndims-1]`. If provided a negative dimension index, the position at which to place a respective dimension is computed as `ndims + index`. +* - Provided dimension indices must resolve to normalized dimension indices arranged in ascending order. +* +* @param {NonNegativeInteger} ndims - number of dimensions in the output array +* @param {ndarray} x - input array +* @param {IntegerArray} dims - dimension indices at which to spread array dimensions +* @throws {RangeError} first argument must be greater than or equal to the number of dimensions in the input array +* @throws {RangeError} must provide the same number of dimension indices as the number of dimensions in the input array +* @throws {RangeError} must provide valid dimension indices +* @throws {Error} must provide unique dimension indices +* @throws {Error} dimension indices must resolve to normalized dimension indices arranged in ascending order +* @returns {ndarray} output array +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); +* // returns +* +* var shx = x.shape; +* // returns [ 2, 2 ] +* +* var y = spreadDimensions( 5, x, [ 1, 3 ] ); +* // returns +* +* var shy = y.shape; +* // returns [ 1, 2, 1, 2, 1 ] +* +* var v = y.get( 0, 0, 0, 0, 0 ); +* // returns 1 +* +* v = y.get( 0, 0, 0, 1, 0 ); +* // returns 2 +* +* v = y.get( 0, 1, 0, 0, 0 ); +* // returns 3 +* +* v = y.get( 0, 1, 0, 1, 0 ); +* // returns 4 +*/ +function spreadDimensions( ndims, x, dims ) { + var strides; + var shape; + var isrm; + var ord; + var sh; + var st; + var d; + var S; + var s; + var i; + var j; + + sh = getShape( x, false ); + st = getStrides( x, false ); + ord = getOrder( x ); + isrm = isRowMajor( ord ); + + if ( sh.length > ndims ) { + throw new RangeError( format( 'invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.', sh.length, ndims ) ); + } + // Resolve dimension indices... + d = toNormalizedIndices( dims, ndims-1 ); + if ( d === null ) { + throw new RangeError( format( 'invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.', ndims, ndims-1, dims.join( ', ' ) ) ); + } + if ( d.length !== dims.length ) { + throw new Error( format( 'invalid argument. Must provide unique dimension indices. Value: `[%s]`.', dims.join( ', ' ) ) ); + } + if ( d.length !== sh.length ) { + throw new RangeError( format( 'invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.', sh.length, dims.join( ', ' ) ) ); + } + if ( d.length && !isSortedAscending( d ) ) { + throw new Error( format( 'invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.', dims.join( ', ' ) ) ); + } + // When provided a zero-dimensional array, every expanded dimension is a singleton dimension having zero stride... + if ( sh.length === 0 ) { + shape = ones( ndims ); + strides = zeros( ndims ); + } else { + // Interweave singleton dimensions... + strides = []; + shape = []; + j = 0; + for ( i = 0; i < ndims; i++ ) { + if ( i === d[ j ] ) { + // If we have a match, we can move on to inserting singleton dimensions before the next dimension index... + S = sh[ j ]; + s = st[ j ]; + j += 1; + } else if ( j === sh.length ) { // append + // We should only get here after exhausting all the dimension indices... + S = 1; + s = st[ j-1 ]; + if ( !isrm ) { + s *= sh[ j-1 ]; + } + } else { // insert before + // We have yet to reach the next specified dimension index so we insert a singleton dimension... + S = 1; + s = st[ j ]; + if ( isrm ) { + s *= sh[ j ]; + } + } + shape.push( S ); + strides.push( s ); + } + } + if ( isReadOnly( x ) ) { + // If provided a read-only view, the returned array should also be read-only... + return new x.constructor( getDType( x ), getData( x ), shape, strides, getOffset( x ), ord, { // eslint-disable-line max-len + 'readonly': true + }); + } + return new x.constructor( getDType( x ), getData( x ), shape, strides, getOffset( x ), ord ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = spreadDimensions; diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/package.json b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/package.json new file mode 100644 index 000000000000..3a0f8366061b --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/ndarray/base/spread-dimensions", + "version": "0.0.0", + "description": "Expand the shape of an array to a specified dimensionality by spreading its dimensions to specified dimension indices and inserting dimensions of size one for the remaining dimensions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "expand", + "spread", + "broadcast", + "reshape", + "singleton", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js new file mode 100644 index 000000000000..101325c06deb --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/spread-dimensions/test/test.js @@ -0,0 +1,492 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var array = require( '@stdlib/ndarray/array' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var isReadOnly = require( '@stdlib/ndarray/base/assert/is-read-only' ); +var spreadDimensions = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof spreadDimensions, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is less than the number of input array dimensions', function test( t ) { + var values; + var x; + var i; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + values = [ + 0, + 1 + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + spreadDimensions( value, x, [ 0, 1 ] ); + }; + } +}); + +tape( 'the function throws an error if the number of provided dimension indices does not equal the number of input array dimensions', function test( t ) { + var values; + var x; + var i; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + values = [ + [], + [ 0 ], + [ 0, 1, 2 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + spreadDimensions( 5, x, value ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid dimension index', function test( t ) { + var values; + var x; + var i; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + values = [ + 10, + -10, + 99, + -99 + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + spreadDimensions( 5, x, [ 0, value ] ); + }; + } +}); + +tape( 'the function throws an error if not provided unique indices', function test( t ) { + var values; + var x; + var i; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + values = [ + [ 0, 0 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + spreadDimensions( 5, x, value ); + }; + } +}); + +tape( 'the function throws an error if not provided indices sorted in ascending order', function test( t ) { + var values; + var x; + var i; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + values = [ + [ 1, 0 ], // normalized + [ -1, -2 ] // un-normalized + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + spreadDimensions( 5, x, value ); + }; + } +}); + +tape( 'the function prepends singleton dimensions', function test( t ) { + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + y = spreadDimensions( 3, x, [ 1, 2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (negative axis)', function test( t ) { + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + y = spreadDimensions( 3, x, [ -2, -1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions', function test( t ) { + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + y = spreadDimensions( 3, x, [ 0, 1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (negative axis)', function test( t ) { + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + y = spreadDimensions( 3, x, [ -3, -2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions', function test( t ) { + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + y = spreadDimensions( 3, x, [ 0, 2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions (negative axis)', function test( t ) { + var x; + var y; + + x = array( [ [ 1, 2 ], [ 3, 4 ] ] ); + + y = spreadDimensions( 3, x, [ -3, -1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (base; row-major)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 3, x, [ 1, 2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (base; row-major; negative axis)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 3, x, [ -2, -1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 4, 2, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (base; column-major)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + y = spreadDimensions( 3, x, [ 1, 2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function prepends singleton dimensions (base; column-major; negative index)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + y = spreadDimensions( 3, x, [ -2, -1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (base; row-major)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 3, x, [ 0, 1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 2, 1, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (base; row-major; negative axis)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 3, x, [ -3, -2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 2, 1, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (base; column-major)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + y = spreadDimensions( 3, x, [ 0, 1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 2, 4 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function appends singleton dimensions (base; column-major; negative index)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + y = spreadDimensions( 3, x, [ -3, -2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 2, 1 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 2, 4 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions (base; row-major)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 3, x, [ 0, 2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 2, 2, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions (base; row-major; negative axis)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 3, x, [ -3, -1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 2, 2, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions (base; column-major)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + y = spreadDimensions( 3, x, [ 0, 2 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 2, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions (base; column-major; negative index)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + y = spreadDimensions( 3, x, [ -3, -1 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 2 ], 'returns expected value' ); + t.deepEqual( y.strides, [ 1, 2, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function inserts singleton dimensions (zero-dimensional array)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [], [], [ 0 ], 0, 'row-major' ); + + y = spreadDimensions( 3, x, [] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 1, 1 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a read-only array, the function returns a read-only array', function test( t ) { + var x; + var y; + + x = array( [ 1, 2, 3, 4 ], { + 'shape': [ 2, 1, 2 ], + 'readonly': true + }); + + y = spreadDimensions( 4, x, [ 0, 1, 3 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a writable array, the function returns a writable array', function test( t ) { + var x; + var y; + + x = array( [ 1, 2, 3, 4 ], { + 'shape': [ 2, 1, 2 ], + 'readonly': false + }); + + y = spreadDimensions( 4, x, [ 0, 2, 3 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 2, 1, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a writable array, the function returns a writable array (base)', function test( t ) { + var x; + var y; + + x = ndarray( 'generic', [ 1, 2, 3, 4 ], [ 2, 1, 2 ], [ 2, 2, 1 ], 0, 'row-major' ); + y = spreadDimensions( 4, x, [ 1, 2, 3 ] ); + + t.notEqual( y, x, 'returns expected value' ); + t.deepEqual( y.shape, [ 1, 2, 1, 2 ], 'returns expected value' ); + t.strictEqual( y.data, x.data, 'returns expected value' ); + t.strictEqual( isReadOnly( y ), false, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/README.md b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/README.md new file mode 100644 index 000000000000..c70feea9f7d5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/README.md @@ -0,0 +1,128 @@ + + +# toNormalizedIndices + +> Normalize a list of indices to the interval `[0,max]`. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var toNormalizedIndices = require( '@stdlib/ndarray/base/to-normalized-indices' ); +``` + +#### toNormalizedIndices( indices, max ) + +Normalizes a list of indices to the interval `[0,max]`. + +```javascript +var idx = toNormalizedIndices( [ 2, -5 ], 10 ); +// returns [ 2, 6 ] +``` + +If provided an out-of-bounds index, the function normalizes the index to `-1`. + +```javascript +var idx = toNormalizedIndices( [ 15, -15 ], 10 ); +// returns [ -1, -1 ] +``` + +
+ + + + + +
+ +## Notes + +- During normalization, a negative index is converted to a nonnegative index according to `max + idx + 1`. If, after normalization, the resolved index is still negative, the value is considered out-of-bounds. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var toNormalizedIndices = require( '@stdlib/ndarray/base/to-normalized-indices' ); + +// Generate a list of random indices: +var idx = discreteUniform( 100, -20, 20, { + 'dtype': 'generic' +}); + +// Normalize each index to the interval `[0, 15]`: +var out = toNormalizedIndices( idx, 15 ); + +// Print the results... +var i; +for ( i = 0; i < idx.length; i++ ) { + console.log( '%d => [%d, %d] => %d', idx[ i ], 0, 15, out[ i ] ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/benchmark/benchmark.js new file mode 100644 index 000000000000..5bef05120bdd --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives; +var Int32Array = require( '@stdlib/array/int32' ); +var pkg = require( './../package.json' ).name; +var toNormalizedIndices = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + [ -4, -5, 4, 5 ], + new Int32Array( [ -4, -5, 4, 5 ] ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = toNormalizedIndices( values[ i%values.length ], 10 ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isNonNegativeIntegerArray( out ) ) { + b.fail( 'should return an array of nonnegative integers' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/repl.txt new file mode 100644 index 000000000000..8cae7fad11fe --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}( indices, max ) + Normalizes indices to the interval [0,max]. + + If an index exceeds index bounds, the function normalizes the index to -1. + + Parameters + ---------- + indices: Collection + Indices to normalize. + + max: integer + Maximum index value. + + Returns + ------- + out: Collection + Normalized indices. + + Examples + -------- + > var idx = {{alias}}( [ 2, -5 ], 10 ) + [ 2, 6 ] + > idx = {{alias}}( [ 15 ], 10 ) + [ -1 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/types/index.d.ts new file mode 100644 index 000000000000..3163d84259a6 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/types/index.d.ts @@ -0,0 +1,48 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Normalizes a list of indices to the interval `[0,max]`. +* +* ## Notes +* +* - If provided an out-of-bounds index, the function normalizes the index to `-1`. +* +* @param indices - indices +* @param max - maximum index +* @returns normalized indices +* +* @example +* var indices = toNormalizedIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* indices = toNormalizedIndices( [ -2, 15 ], 10 ); +* // returns [ 9, -1 ] +*/ +declare function toNormalizedIndices( indices: Collection, max: number ): Collection; + + +// EXPORTS // + +export = toNormalizedIndices; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/types/test.ts new file mode 100644 index 000000000000..cd471a9f526d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import toNormalizedIndices = require( './index' ); + + +// TESTS // + +// The function returns a collection of numbers... +{ + toNormalizedIndices( [ 0, 15 ], 10 ); // $ExpectType Collection +} + +// The compiler throws an error if the function is provided invalid values... +{ + toNormalizedIndices( true, 3 ); // $ExpectError + toNormalizedIndices( false, 2 ); // $ExpectError + toNormalizedIndices( '5', 1 ); // $ExpectError + toNormalizedIndices( [ '5' ], 1 ); // $ExpectError + toNormalizedIndices( {}, 2 ); // $ExpectError + toNormalizedIndices( ( x: number ): number => x, 2 ); // $ExpectError + + toNormalizedIndices( [ 9 ], true ); // $ExpectError + toNormalizedIndices( [ 9 ], false ); // $ExpectError + toNormalizedIndices( [ 5 ], '5' ); // $ExpectError + toNormalizedIndices( [ 8 ], [] ); // $ExpectError + toNormalizedIndices( [ 9 ], {} ); // $ExpectError + toNormalizedIndices( [ 8 ], ( x: number ): number => x ); // $ExpectError + + toNormalizedIndices( [], true ); // $ExpectError + toNormalizedIndices( {}, false ); // $ExpectError + toNormalizedIndices( false, '5' ); // $ExpectError + toNormalizedIndices( {}, [] ); // $ExpectError + toNormalizedIndices( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + toNormalizedIndices(); // $ExpectError + toNormalizedIndices( [ 3 ] ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/examples/index.js new file mode 100644 index 000000000000..549f85f243df --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var toNormalizedIndices = require( './../lib' ); + +// Generate a list of random indices: +var idx = discreteUniform( 100, -20, 20, { + 'dtype': 'generic' +}); + +// Normalize each index to the interval `[0, 15]`: +var out = toNormalizedIndices( idx, 15 ); + +// Print the results... +var i; +for ( i = 0; i < idx.length; i++ ) { + console.log( '%d => [%d, %d] => %d', idx[ i ], 0, 15, out[ i ] ); +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/lib/index.js new file mode 100644 index 000000000000..4db094120279 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Normalize a list of indices to the interval `[0,max]`. +* +* @module @stdlib/ndarray/base/to-normalized-indices +* +* @example +* var toNormalizedIndices = require( '@stdlib/ndarray/base/to-normalized-indices' ); +* +* var idx = toNormalizedIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* idx = toNormalizedIndices( [ 15 ], 10 ); +* // returns [ -1 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/lib/main.js new file mode 100644 index 000000000000..e9d97fa9ba98 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/lib/main.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var emptyLike = require( '@stdlib/array/empty-like' ); +var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); + + +// MAIN // + +/** +* Normalizes a list of indices to the interval `[0,max]`. +* +* @param {IntegerArray} indices - indices +* @param {NonNegativeInteger} max - maximum index +* @returns {IntegerArray} normalized indices +* +* @example +* var idx = toNormalizedIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* idx = toNormalizedIndices( [ 15 ], 10 ); +* // returns [ -1 ] +*/ +function toNormalizedIndices( indices, max ) { + var out; + var i; + + out = emptyLike( indices ); + for ( i = 0; i < indices.length; i++ ) { + out[ i ] = normalizeIndex( indices[ i ], max ); + } + return out; +} + + +// EXPORTS // + +module.exports = toNormalizedIndices; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/package.json b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/package.json new file mode 100644 index 000000000000..f3e690c531cf --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/ndarray/base/to-normalized-indices", + "version": "0.0.0", + "description": "Normalize a list of indices to the interval [0,max].", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "index", + "idx", + "ind", + "subscript", + "normalize", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/test/test.js b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/test/test.js new file mode 100644 index 000000000000..a49c1233c789 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-normalized-indices/test/test.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isInt32Array = require( '@stdlib/assert/is-int32array' ); +var isArray = require( '@stdlib/assert/is-array' ); +var Int32Array = require( '@stdlib/array/int32' ); +var toNormalizedIndices = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof toNormalizedIndices, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function normalizes a list of indices to the interval `[0,max]`', function test( t ) { + var expected; + var actual; + var idx; + + idx = [ 2, 5, 0, 7, 1, -5, -1, -2, -10, -11 ]; + expected = [ 2, 5, 0, 7, 1, 6, 10, 9, 1, 0 ]; + + actual = toNormalizedIndices( idx, 10 ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + idx = new Int32Array( [ 2, 5, 0, 7, 1, -5, -1, -2, -10, -11 ] ); + expected = new Int32Array( [ 2, 5, 0, 7, 1, 6, 10, 9, 1, 0 ] ); + + actual = toNormalizedIndices( idx, 10 ); + t.strictEqual( isInt32Array( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an out-of-bounds index, the function normalizes the index to `-1`', function test( t ) { + var expected; + var actual; + var idx; + + idx = [ 15, -15 ]; + expected = [ -1, -1 ]; + + actual = toNormalizedIndices( idx, 10 ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + idx = new Int32Array( [ 15, -15 ] ); + expected = new Int32Array( [ -1, -1 ] ); + + actual = toNormalizedIndices( idx, 10 ); + t.strictEqual( isInt32Array( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/README.md b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/README.md new file mode 100644 index 000000000000..5bba364664be --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/README.md @@ -0,0 +1,126 @@ + + +# toUniqueNormalizedIndices + +> Return a list of unique indices after normalizing to the interval `[0,max]`. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var toUniqueNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' ); +``` + +#### toUniqueNormalizedIndices( indices, max ) + +Returns a list of unique indices after normalizing to the interval `[0,max]`. + +```javascript +var idx = toUniqueNormalizedIndices( [ 2, -5 ], 10 ); +// returns [ 2, 6 ] +``` + +If provided an out-of-bounds index, the function returns `null`. + +```javascript +var idx = toUniqueNormalizedIndices( [ 15, -15 ], 10 ); +// returns null +``` + +
+ + + + + +
+ +## Notes + +- During normalization, a negative index is converted to a nonnegative index according to `max + idx + 1`. If, after normalization, the resolved index is still negative, the value is considered out-of-bounds. +- When provided valid indices, the function always returns a "generic" array. +- The function preserves provided index order. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var toUniqueNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' ); + +// Generate a list of random indices: +var idx = discreteUniform( 100, -15, 15, { + 'dtype': 'generic' +}); +console.log( idx ); + +// Generate a list of unique indices normalized to the interval `[0, 15]`: +var out = toUniqueNormalizedIndices( idx, 15 ); +console.log( out ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/benchmark/benchmark.js new file mode 100644 index 000000000000..ed872ed6a1a4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives; +var Int32Array = require( '@stdlib/array/int32' ); +var pkg = require( './../package.json' ).name; +var toUniqueNormalizedIndices = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + [ -4, -5, 4, 5 ], + new Int32Array( [ -4, -5, 4, 5 ] ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = toUniqueNormalizedIndices( values[ i%values.length ], 10 ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isNonNegativeIntegerArray( out ) ) { + b.fail( 'should return an array of nonnegative integers' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/repl.txt new file mode 100644 index 000000000000..297f054b27c5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}( indices, max ) + Returns a list of unique indices after normalizing to the interval [0,max]. + + If an index exceeds index bounds, the function returns `null`. + + Parameters + ---------- + indices: Collection + Indices to normalize. + + max: integer + Maximum index value. + + Returns + ------- + out: Array|null + Normalized indices. + + Examples + -------- + > var idx = {{alias}}( [ 2, -5 ], 10 ) + [ 2, 6 ] + > idx = {{alias}}( [ 15 ], 10 ) + null + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/types/index.d.ts new file mode 100644 index 000000000000..eaf3bb9b13da --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/types/index.d.ts @@ -0,0 +1,48 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Returns a list of unique indices after normalizing to the interval `[0,max]`. +* +* ## Notes +* +* - If provided an out-of-bounds index, the function returns `null`. +* +* @param indices - indices +* @param max - maximum index +* @returns normalized indices (or null) +* +* @example +* var indices = toUniqueNormalizedIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* indices = toUniqueNormalizedIndices( [ -2, 15 ], 10 ); +* // returns null +*/ +declare function toUniqueNormalizedIndices( indices: Collection, max: number ): Array | null; + + +// EXPORTS // + +export = toUniqueNormalizedIndices; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/types/test.ts new file mode 100644 index 000000000000..a3ca06531291 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import toUniqueNormalizedIndices = require( './index' ); + + +// TESTS // + +// The function returns a collection of numbers or `null`... +{ + toUniqueNormalizedIndices( [ 0, 15 ], 10 ); // $ExpectType number[] | null +} + +// The compiler throws an error if the function is provided invalid values... +{ + toUniqueNormalizedIndices( true, 3 ); // $ExpectError + toUniqueNormalizedIndices( false, 2 ); // $ExpectError + toUniqueNormalizedIndices( '5', 1 ); // $ExpectError + toUniqueNormalizedIndices( [ '5' ], 1 ); // $ExpectError + toUniqueNormalizedIndices( {}, 2 ); // $ExpectError + toUniqueNormalizedIndices( ( x: number ): number => x, 2 ); // $ExpectError + + toUniqueNormalizedIndices( [ 9 ], true ); // $ExpectError + toUniqueNormalizedIndices( [ 9 ], false ); // $ExpectError + toUniqueNormalizedIndices( [ 5 ], '5' ); // $ExpectError + toUniqueNormalizedIndices( [ 8 ], [] ); // $ExpectError + toUniqueNormalizedIndices( [ 9 ], {} ); // $ExpectError + toUniqueNormalizedIndices( [ 8 ], ( x: number ): number => x ); // $ExpectError + + toUniqueNormalizedIndices( [], true ); // $ExpectError + toUniqueNormalizedIndices( {}, false ); // $ExpectError + toUniqueNormalizedIndices( false, '5' ); // $ExpectError + toUniqueNormalizedIndices( {}, [] ); // $ExpectError + toUniqueNormalizedIndices( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + toUniqueNormalizedIndices(); // $ExpectError + toUniqueNormalizedIndices( [ 3 ] ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/examples/index.js new file mode 100644 index 000000000000..2ffcf9424530 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/examples/index.js @@ -0,0 +1,32 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var toUniqueNormalizedIndices = require( './../lib' ); + +// Generate a list of random indices: +var idx = discreteUniform( 100, -15, 15, { + 'dtype': 'generic' +}); +console.log( idx ); + +// Generate a list of unique indices normalized to the interval `[0, 15]`: +var out = toUniqueNormalizedIndices( idx, 15 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/lib/index.js new file mode 100644 index 000000000000..bfe35e4010b2 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a list of unique indices after normalizing to the interval `[0,max]`. +* +* @module @stdlib/ndarray/base/to-unique-normalized-indices +* +* @example +* var toUniqueNormalizedIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' ); +* +* var idx = toUniqueNormalizedIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* idx = toUniqueNormalizedIndices( [ 15 ], 10 ); +* // returns null +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/lib/main.js new file mode 100644 index 000000000000..837bc3f7a871 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/lib/main.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var normalizeIndex = require( '@stdlib/ndarray/base/normalize-index' ); + + +// MAIN // + +/** +* Returns a list of unique indices after normalizing to the interval `[0,max]`. +* +* @param {IntegerArray} indices - indices +* @param {NonNegativeInteger} max - maximum index +* @returns {(IntegerArray|null)} normalized indices +* +* @example +* var idx = toUniqueNormalizedIndices( [ -2, 5 ], 10 ); +* // returns [ 9, 5 ] +* +* idx = toUniqueNormalizedIndices( [ 15 ], 10 ); +* // returns null +*/ +function toUniqueNormalizedIndices( indices, max ) { + var hash; + var out; + var idx; + var i; + + hash = {}; + out = []; + for ( i = 0; i < indices.length; i++ ) { + idx = normalizeIndex( indices[ i ], max ); + if ( idx < 0 ) { + return null; + } + if ( hash[ idx ] === void 0 ) { + hash[ idx ] = true; + out.push( idx ); + } + } + return out; +} + + +// EXPORTS // + +module.exports = toUniqueNormalizedIndices; diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/package.json b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/package.json new file mode 100644 index 000000000000..4e09f3a75f50 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/ndarray/base/to-unique-normalized-indices", + "version": "0.0.0", + "description": "Return a list of unique indices after normalizing to the interval [0,max].", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "types", + "base", + "ndarray", + "index", + "idx", + "ind", + "subscript", + "normalize", + "multidimensional", + "array", + "utilities", + "utility", + "utils", + "util" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/test/test.js b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/test/test.js new file mode 100644 index 000000000000..49287d3a42bb --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/to-unique-normalized-indices/test/test.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isArray = require( '@stdlib/assert/is-array' ); +var Int32Array = require( '@stdlib/array/int32' ); +var toUniqueNormalizedIndices = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof toUniqueNormalizedIndices, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a unique list of indices after normalizing to the interval `[0,max]`', function test( t ) { + var expected; + var actual; + var idx; + + idx = [ 2, 5, 0, 7, 1, -5, -1, -2, -10, -11 ]; + expected = [ 2, 5, 0, 7, 1, 6, 10, 9 ]; + + actual = toUniqueNormalizedIndices( idx, 10 ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + idx = new Int32Array( [ 2, 5, 0, 7, 1, -5, -1, -2, -10, -11 ] ); + expected = [ 2, 5, 0, 7, 1, 6, 10, 9 ]; + + actual = toUniqueNormalizedIndices( idx, 10 ); + t.strictEqual( isArray( actual ), true, 'returns expected value' ); + t.notEqual( actual, idx, 'returns expected value' ); + t.deepEqual( actual, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an out-of-bounds index, the function returns `null`', function test( t ) { + var actual; + var idx; + + idx = [ 15, -15 ]; + actual = toUniqueNormalizedIndices( idx, 10 ); + t.strictEqual( actual, null, 'returns expected value' ); + + idx = new Int32Array( [ 15, -15 ] ); + actual = toUniqueNormalizedIndices( idx, 10 ); + t.strictEqual( actual, null, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/README.md b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/README.md new file mode 100644 index 000000000000..0562734dfe58 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/README.md @@ -0,0 +1,419 @@ + + +# accumulateUnary + +> Perform a reduction over elements in an input ndarray. + +
+ +
+ + + +
+ +## Usage + +```javascript +var accumulateUnary = require( '@stdlib/ndarray/base/unary-accumulate' ); +``` + +#### accumulateUnary( arrays, initial, clbk ) + +Performs a reduction over elements in an input ndarray. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +function add( acc, x ) { + return acc + x; +} + +// Create a data buffer: +var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + +// Define the shape of the input array: +var shape = [ 3, 1, 2 ]; + +// Define the array strides: +var sx = [ 4, 4, 1 ]; + +// Define the index offset: +var ox = 1; + +// Create the input ndarray-like object: +var x = { + 'dtype': 'float64', + 'data': xbuf, + 'shape': shape, + 'strides': sx, + 'offset': ox, + 'order': 'row-major' +}; + +// Compute the sum: +var v = accumulateUnary( [ x ], 0.0, add ); +// returns 39.0 +``` + +The function accepts the following arguments: + +- **arrays**: array-like object containing one input ndarray. +- **initial**: initial value. +- **clbk**: callback function to apply. + +Each provided ndarray should be an object with the following properties: + +- **dtype**: data type. +- **data**: data buffer. +- **shape**: dimensions. +- **strides**: stride lengths. +- **offset**: index offset. +- **order**: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style). + +The callback is invoked with two arguments: + +- **acc**: the current accumulated value. The first time the callback is invoked, `acc` is equal to the initial value. +- **value**: the current element. + +After each callback invocation, the callback return value is subsequently used as the accumulated value for the next callback invocation. + +
+ + + +
+ +## Notes + +- For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before applying an accumulator in order to achieve better performance. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var add = require( '@stdlib/math/base/ops/add' ); +var accumulateUnary = require( '@stdlib/ndarray/base/unary-accumulate' ); + +var N = 10; +var x = { + 'dtype': 'generic', + 'data': discreteUniform( N, -100, 100, { + 'dtype': 'generic' + }), + 'shape': [ 5, 2 ], + 'strides': [ 2, 1 ], + 'offset': 0, + 'order': 'row-major' +}; + +var sum = accumulateUnary( [ x ], 0.0, add ); +console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); + +console.log( 'sum: %d', sum ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +Character codes for data types: + + + + + +- **x**: `bool` (boolean). +- **c**: `complex64` (single-precision floating-point complex number). +- **z**: `complex128` (double-precision floating-point complex number). +- **f**: `float32` (single-precision floating-point number). +- **d**: `float64` (double-precision floating-point number). +- **k**: `int16` (signed 16-bit integer). +- **i**: `int32` (signed 32-bit integer). +- **s**: `int8` (signed 8-bit integer). +- **t**: `uint16` (unsigned 16-bit integer). +- **u**: `uint32` (unsigned 32-bit integer). +- **b**: `uint8` (unsigned 8-bit integer). + + + +Function name suffix naming convention: + +```text +stdlib_ndarray__[_as__] +``` + +For example, + + + +```c +void stdlib_ndarray_accumulate_dd_d(...) {...} +``` + +is a function which performs accumulation in double-precision and accepts one double-precision floating-point input ndarray and one double-precision floating-point output ndarray. In other words, the suffix encodes the function type signature. + +To support callbacks whose input arguments and/or return values are of a different data type than the input and/or output ndarray data types, the naming convention supports appending an `as` suffix. For example, + + + +```c +void stdlib_ndarray_accumulate_ff_f_as_dd_d(...) {...} +``` + +is a function which performs accumulation in single-precision and accepts one single-precision floating-point input ndarray and one single-precision floating-point output ndarray. However, the callback accepts and returns double-precision floating-point numbers. Accordingly, the input and output values need to be cast using the following conversion sequence + +```c +// Convert the current accumulated value to double-precision: +double curr = (double)acc; + +// Convert each input array element to double-precision: +double in1 = (double)x[ i ]; + +// Evaluate the callback: +double out = f( curr, in1 ); + +// Convert the callback return value to single-precision: +acc = (float)out; +``` + +The accumulation data type and the output ndarray data type should **always** be the same. + +The callback is invoked with two arguments: + +- **acc**: the current accumulated value. The first time the callback is invoked, this argument is equal to the initial value. +- **value**: the current element. + +After each callback invocation, the callback return value is subsequently used as the accumulated value for the next callback invocation. + +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ndarray/base/unary_accumulate.h" +``` + + + + + + + + + + + + + +
+ + + + + +
+ +* * * + +### Notes + +- The initial value and output ndarrays are assumed to be zero-dimensional ndarrays. + +
+ + + + + +* * * + +
+ +### Examples + +```c +#include "stdlib/ndarray/base/unary_accumulate.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/ctor.h" +#include +#include +#include +#include + +static void print_ndarray_contents( const struct ndarray *x ) { + int64_t i; + int8_t s; + double v; + + for ( i = 0; i < stdlib_ndarray_length( x ); i++ ) { + s = stdlib_ndarray_iget_float64( x, i, &v ); + if ( s != 0 ) { + fprintf( stderr, "Unable to resolve data element.\n" ); + exit( EXIT_FAILURE ); + } + fprintf( stdout, "data[%"PRId64"] = %lf\n", i, v ); + } +} + +static double add( const double acc, const double x ) { + return acc + x; +} + +int main( void ) { + // Define the ndarray data type: + enum STDLIB_NDARRAY_DTYPE dtype = STDLIB_NDARRAY_FLOAT64; + + // Create underlying byte arrays: + double xvalues[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + double ivalues[] = { 0.0 }; + double ovalues[] = { 0.0 }; + + uint8_t *xbuf = (uint8_t *)xvalues; + uint8_t *ibuf = (uint8_t *)ivalues; + uint8_t *obuf = (uint8_t *)ovalues; + + // Define the number of dimensions: + int64_t ndims = 3; + + // Define the array shapes: + int64_t xsh[] = { 2, 2, 2 }; + int64_t ish[] = {}; + int64_t osh[] = {}; + + // Define the strides: + int64_t sx[] = { 32, 16, 8 }; + int64_t si[] = { 0 }; + int64_t so[] = { 0 }; + + // Define the offsets: + int64_t ox = 0; + int64_t oi = 0; + int64_t oo = 0; + + // Define the array order: + enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { imode }; + int64_t nsubmodes = 1; + + // Create an input ndarray: + struct ndarray *x = stdlib_ndarray_allocate( dtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); + } + + // Create an initial value zero-dimensional ndarray: + struct ndarray *initial = stdlib_ndarray_allocate( dtype, ibuf, ndims, ish, si, oi, order, imode, nsubmodes, submodes ); + if ( initial == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); + } + + // Create an output zero-dimensional ndarray: + struct ndarray *out = stdlib_ndarray_allocate( dtype, obuf, ndims, osh, so, oo, order, imode, nsubmodes, submodes ); + if ( out == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); + } + + // Define an array containing the ndarrays: + struct ndarray *arrays[] = { x, initial, out }; + + // Apply the callback: + int8_t status = stdlib_ndarray_accumulate_dd_d( arrays, (void *)add ); + if ( status != 0 ) { + fprintf( stderr, "Error during computation.\n" ); + exit( EXIT_FAILURE ); + } + + // Print the results: + print_ndarray_contents( out ); + fprintf( stdout, "\n" ); + + // Free allocated memory: + stdlib_ndarray_free( x ); + stdlib_ndarray_free( initial ); + stdlib_ndarray_free( out ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_blocked_columnmajor.js new file mode 100644 index 000000000000..8912e0b95831 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_blocked_columnmajor.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/10d_blocked.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'column-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( pow( len, 1.0/10.0 ) ); + sh = [ len, len, len, len, len, len, len, len, len, len ]; + len *= pow( len, 9 ); + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_blocked_rowmajor.js new file mode 100644 index 000000000000..ba115c5a9c61 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_blocked_rowmajor.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/10d_blocked.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( pow( len, 1.0/10.0 ) ); + sh = [ len, len, len, len, len, len, len, len, len, len ]; + len *= pow( len, 9 ); + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_columnmajor.js new file mode 100644 index 000000000000..ff09201330e8 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_columnmajor.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/10d.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'column-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( pow( len, 1.0/10.0 ) ); + sh = [ len, len, len, len, len, len, len, len, len, len ]; + len *= pow( len, 9 ); + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_rowmajor.js new file mode 100644 index 000000000000..de94a98951e9 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.10d_rowmajor.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/10d.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( pow( len, 1.0/10.0 ) ); + sh = [ len, len, len, len, len, len, len, len, len, len ]; + len *= pow( len, 9 ); + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.11d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.11d_columnmajor.js new file mode 100644 index 000000000000..13914be68d46 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.11d_columnmajor.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/nd.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'column-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( pow( len, 1.0/11.0 ) ); + sh = [ len, len, len, len, len, len, len, len, len, len, len ]; + len *= pow( len, 10 ); + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.11d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.11d_rowmajor.js new file mode 100644 index 000000000000..3d8fe71c9b24 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.11d_rowmajor.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/nd.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( pow( len, 1.0/11.0 ) ); + sh = [ len, len, len, len, len, len, len, len, len, len, len ]; + len *= pow( len, 10 ); + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.1d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.1d_columnmajor.js new file mode 100644 index 000000000000..883a18eb6f2e --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.1d_columnmajor.js @@ -0,0 +1,123 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'column-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( [ x ], 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.1d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.1d_rowmajor.js new file mode 100644 index 000000000000..8da4cb5a96b4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.1d_rowmajor.js @@ -0,0 +1,123 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( [ x ], 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_blocked_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_blocked_columnmajor.js new file mode 100644 index 000000000000..116b6da2d217 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_blocked_columnmajor.js @@ -0,0 +1,135 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/2d_blocked.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'column-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( sqrt( len ) ); + sh = [ len, len ]; + len *= len; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_blocked_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_blocked_rowmajor.js new file mode 100644 index 000000000000..e80a5da5a100 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_blocked_rowmajor.js @@ -0,0 +1,135 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/2d_blocked.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( sqrt( len ) ); + sh = [ len, len ]; + len *= len; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::blocked:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_columnmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_columnmajor.js new file mode 100644 index 000000000000..4dc08b3e13e7 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_columnmajor.js @@ -0,0 +1,135 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/2d.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'column-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( sqrt( len ) ); + sh = [ len, len ]; + len *= len; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor.js new file mode 100644 index 000000000000..cf165a74f54c --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor.js @@ -0,0 +1,135 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/2d.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( sqrt( len ) ); + sh = [ len, len ]; + len *= len; + f = createBenchmark( len, sh, t1 ); + bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor_accessors.js new file mode 100644 index 000000000000..f693364560a4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor_accessors.js @@ -0,0 +1,161 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/math/base/ops/add' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/2d_accessors.js' ); + + +// VARIABLES // + +var types = [ 'float64' ]; +var order = 'row-major'; + + +// FUNCTIONS // + +/** +* Returns an array data buffer element. +* +* @private +* @param {Collection} buf - data buffer +* @param {NonNegativeInteger} idx - element index +* @returns {*} element +*/ +function get( buf, idx ) { + return buf[ idx ]; +} + +/** +* Sets an array data buffer element. +* +* @private +* @param {Collection} buf - data buffer +* @param {NonNegativeInteger} idx - element index +* @param {*} value - value to set +*/ +function set( buf, idx, value ) { + buf[ idx ] = value; +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var x = uniform( len, -100.0, 100.0, { + 'dtype': xtype + }); + x = { + 'dtype': xtype, + 'data': x, + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order, + 'accessorProtocol': true, + 'accessors': [ get, set ] + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, 0.0, add ); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( out ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 6; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( sqrt( len ) ); + sh = [ len, len ]; + len *= len; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor_accessors_complex.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor_accessors_complex.js new file mode 100644 index 000000000000..7cb60f92a7ad --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/benchmark/benchmark.2d_rowmajor_accessors_complex.js @@ -0,0 +1,173 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var add = require( '@stdlib/complex/float32/base/add' ); +var ctors = require( '@stdlib/array/typed-complex-ctors' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var isComplex64 = require( '@stdlib/assert/is-complex64' ); +var shape2strides = require( '@stdlib/ndarray/base/shape2strides' ); +var pkg = require( './../package.json' ).name; +var accumulateUnary = require( './../lib/2d_accessors.js' ); + + +// VARIABLES // + +var types = [ 'complex64' ]; +var order = 'row-major'; +var abtype = { + 'complex64': 'float32', + 'complex128': 'float64' +}; + + +// FUNCTIONS // + +/** +* Returns an array data buffer element. +* +* @private +* @param {Collection} buf - data buffer +* @param {NonNegativeInteger} idx - element index +* @returns {*} element +*/ +function get( buf, idx ) { + return buf.get( idx ); +} + +/** +* Sets an array data buffer element. +* +* @private +* @param {Collection} buf - data buffer +* @param {NonNegativeInteger} idx - element index +* @param {*} value - value to set +*/ +function set( buf, idx, value ) { + buf.set( value, idx ); +} + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @param {NonNegativeIntegerArray} shape - ndarray shape +* @param {string} xtype - input ndarray data type +* @returns {Function} benchmark function +*/ +function createBenchmark( len, shape, xtype ) { + var xbuf; + var x; + + xbuf = uniform( len*2, -100.0, 100.0, { + 'dtype': abtype[ xtype ] + }); + x = { + 'dtype': xtype, + 'data': new ( ctors( xtype ) )( xbuf.buffer ), + 'shape': shape, + 'strides': shape2strides( shape, order ), + 'offset': 0, + 'order': order, + 'accessorProtocol': true, + 'accessors': [ get, set ] + }; + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var z; + var i; + + z = new Complex64( 3.0, 5.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = accumulateUnary( x, z, add ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isComplex64( out ) ) { + b.fail( 'should return a complex number' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var sh; + var t1; + var f; + var i; + var j; + + min = 1; // 10^min + max = 5; // 10^max + + for ( j = 0; j < types.length; j++ ) { + t1 = types[ j ]; + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + sh = [ len/2, 2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + sh = [ 2, len/2 ]; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + + len = floor( sqrt( len ) ); + sh = [ len, len ]; + len *= len; + f = createBenchmark( len, sh, t1 ); + bench( pkg+'::accessors:ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f ); + } + } +} + +main(); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/repl.txt new file mode 100644 index 000000000000..fba9d08a4368 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/repl.txt @@ -0,0 +1,72 @@ + +{{alias}}( arrays, initial, clbk ) + Performs a reduction over elements in an input ndarray. + + A provided "ndarray" should be an object with the following properties: + + - dtype: data type. + - data: data buffer. + - shape: dimensions. + - strides: stride lengths. + - offset: index offset. + - order: specifies whether an ndarray is row-major (C-style) or column-major + (Fortran-style). + + The callback function should be a binary function accepting two arguments: + + - accumulated: the accumulated result. + - currentValue: the current ndarray element. + + Each invocation of the callback should return an updated accumulated result. + This return value is subsequently provided to the callback upon next + invocation. + + After invoking the callback for each element in a provided ndarray, the + function returns the return value from the last invocation of the callback. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing one input ndarray. + + initial: any + Initial accumulator value. + + clbk: Function + Callback function. + + Returns + ------- + result: any + Accumulated result. + + Examples + -------- + // Define ndarray data and meta data... + > var xbuf = new {{alias:@stdlib/array/float64}}( [ -1.0, -2.0, -3.0, -4.0 ] ); + > var dtype = 'float64'; + > var shape = [ 2, 2 ]; + > var sx = [ 2, 1 ]; + > var ox = 0; + > var order = 'row-major'; + + // Using an ndarray... + > var x = {{alias:@stdlib/ndarray/ctor}}( dtype, xbuf, shape, sx, ox, order ); + > {{alias}}( [ x ], 0.0, {{alias:@stdlib/math/base/ops/add}} ) + -10.0 + + // Using a minimal ndarray-like objects... + > x = { + ... 'dtype': dtype, + ... 'data': xbuf, + ... 'shape': shape, + ... 'strides': sx, + ... 'offset': ox, + ... 'order': order + ... }; + > {{alias}}( [ x ], 0.0, {{alias:@stdlib/math/base/ops/add}} ) + -10.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/types/index.d.ts new file mode 100644 index 000000000000..9cc43c006fca --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/types/index.d.ts @@ -0,0 +1,81 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Callback invoked for each ndarray element. +* +* @param acc - accumulated result +* @param value - current ndarray element +* @returns result +*/ +type Callback = ( acc: T, value: U ) => T; + +/** +* Performs a reduction over elements in an ndarray. +* +* @param arrays - array-like object containing one input ndarray +* @param initial - initial value +* @param clbk - callback function +* @returns accumulated result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulateUnary( [ x ], 0.0, add ); +* // returns 39.0 +*/ +declare function accumulateUnary( arrays: ArrayLike>, initial: T, clbk: Callback ): T; + + +// EXPORTS // + +export = accumulateUnary; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/types/test.ts new file mode 100644 index 000000000000..b7d4a94d53b5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/docs/types/test.ts @@ -0,0 +1,79 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import accumulateUnary = require( './index' ); + +/** +* Callback function. +* +* @param acc - accumulated result +* @param x - input value +* @returns accumulated result +*/ +function clbk( acc: number, x: number ): number { + return acc + x; +} + + +// TESTS // + +// The function returns an accumulated result... +{ + const x = zeros( [ 2, 2 ] ); + const arrays = [ x ]; + + accumulateUnary( arrays, 0.0, clbk ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array-like object containing ndarray-like objects... +{ + accumulateUnary( 5, 0.0, clbk ); // $ExpectError + accumulateUnary( true, 0.0, clbk ); // $ExpectError + accumulateUnary( false, 0.0, clbk ); // $ExpectError + accumulateUnary( null, 0.0, clbk ); // $ExpectError + accumulateUnary( undefined, 0.0, clbk ); // $ExpectError + accumulateUnary( {}, 0.0, clbk ); // $ExpectError + accumulateUnary( [ 1 ], 0.0, clbk ); // $ExpectError + accumulateUnary( ( x: number ): number => x, 0.0, clbk ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a valid callback function... +{ + const x = zeros( [ 2, 2 ] ); + const arrays = [ x ]; + + accumulateUnary( arrays, 0.0, '10' ); // $ExpectError + accumulateUnary( arrays, 0.0, 5 ); // $ExpectError + accumulateUnary( arrays, 0.0, true ); // $ExpectError + accumulateUnary( arrays, 0.0, false ); // $ExpectError + accumulateUnary( arrays, 0.0, null ); // $ExpectError + accumulateUnary( arrays, 0.0, undefined ); // $ExpectError + accumulateUnary( arrays, 0.0, [] ); // $ExpectError + accumulateUnary( arrays, 0.0, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 2 ] ); + const arrays = [ x ]; + + accumulateUnary(); // $ExpectError + accumulateUnary( arrays ); // $ExpectError + accumulateUnary( arrays, 0.0, clbk, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/c/dd_d/Makefile b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/c/dd_d/Makefile new file mode 100644 index 000000000000..3441b6eb2fb6 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/c/dd_d/Makefile @@ -0,0 +1,148 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic \ + -march=native \ + -flto + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/c/dd_d/example.c b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/c/dd_d/example.c new file mode 100644 index 000000000000..c22803ef95f7 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/c/dd_d/example.c @@ -0,0 +1,128 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ndarray/base/unary_accumulate.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/ctor.h" +#include +#include +#include +#include + +static void print_ndarray_contents( const struct ndarray *x ) { + int64_t i; + int8_t s; + double v; + + for ( i = 0; i < stdlib_ndarray_length( x ); i++ ) { + s = stdlib_ndarray_iget_float64( x, i, &v ); + if ( s != 0 ) { + fprintf( stderr, "Unable to resolve data element.\n" ); + exit( EXIT_FAILURE ); + } + fprintf( stdout, "data[%"PRId64"] = %lf\n", i, v ); + } +} + +static double add( const double acc, const double x ) { + return acc + x; +} + +int main( void ) { + // Define the ndarray data type: + enum STDLIB_NDARRAY_DTYPE dtype = STDLIB_NDARRAY_FLOAT64; + + // Create underlying byte arrays: + double xvalues[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + double ivalues[] = { 0.0 }; + double ovalues[] = { 0.0 }; + + uint8_t *xbuf = (uint8_t *)xvalues; // cppcheck-suppress invalidPointerCast + uint8_t *ibuf = (uint8_t *)ivalues; // cppcheck-suppress invalidPointerCast + uint8_t *obuf = (uint8_t *)ovalues; // cppcheck-suppress invalidPointerCast + + // Define the number of dimensions: + int64_t ndims = 3; + + // Define the array shapes: + int64_t xsh[] = { 2, 2, 2 }; + int64_t ish[] = { 0 }; + int64_t osh[] = { 0 }; + + // Define the strides: + int64_t sx[] = { 32, 16, 8 }; + int64_t si[] = { 0 }; + int64_t so[] = { 0 }; + + // Define the offsets: + int64_t ox = 0; + int64_t oi = 0; + int64_t oo = 0; + + // Define the array order: + enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { imode }; + int64_t nsubmodes = 1; + + // Create an input ndarray: + struct ndarray *x = stdlib_ndarray_allocate( dtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); + } + + // Create an initial value zero-dimensional ndarray: + struct ndarray *initial = stdlib_ndarray_allocate( dtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); + if ( initial == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); + } + + // Create an output zero-dimensional ndarray: + struct ndarray *out = stdlib_ndarray_allocate( dtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); + if ( out == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); + } + + // Define an array containing the ndarrays: + struct ndarray *arrays[] = { x, initial, out }; + + // Apply the callback: + int8_t status = stdlib_ndarray_accumulate_dd_d( arrays, (void *)add ); + if ( status != 0 ) { + fprintf( stderr, "Error during computation.\n" ); + exit( EXIT_FAILURE ); + } + + // Print the results: + print_ndarray_contents( out ); + fprintf( stdout, "\n" ); + + // Free allocated memory: + stdlib_ndarray_free( x ); + stdlib_ndarray_free( initial ); + stdlib_ndarray_free( out ); +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/index.js new file mode 100644 index 000000000000..c102997456fe --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/base/to-array' ); +var add = require( '@stdlib/math/base/ops/add' ); +var accumulateUnary = require( './../lib' ); + +var N = 10; +var x = { + 'dtype': 'generic', + 'data': discreteUniform( N, -100, 100, { + 'dtype': 'generic' + }), + 'shape': [ 5, 2 ], + 'strides': [ 2, 1 ], + 'offset': 0, + 'order': 'row-major' +}; + +var sum = accumulateUnary( [ x ], 0.0, add ); +console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) ); + +console.log( 'sum: %d', sum ); diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/dispatch.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/dispatch.h new file mode 100644 index 000000000000..75c599b10dc1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/dispatch.h @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_DISPATCH_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_DISPATCH_H + +#include "stdlib/ndarray/base/unary-accumulate/dispatch_object.h" +#include "stdlib/ndarray/ctor.h" +#include + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Dispatches to a ndarray function according to the dimensionality of provided ndarray arguments. +*/ +int8_t stdlib_ndarray_unary_accumulate_dispatch( const struct ndarrayUnaryAccumulateDispatchObject *obj, struct ndarray *arrays[], void *fcn ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_DISPATCH_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/dispatch_object.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/dispatch_object.h new file mode 100644 index 000000000000..f870e2c5f5d1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/dispatch_object.h @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_DISPATCH_OBJECT_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_DISPATCH_OBJECT_H + +#include "stdlib/ndarray/base/unary-accumulate/typedefs.h" +#include + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Structure for grouping function dispatch information. +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/bb_b.h" +* #include +* #include +* +* ndarrayUnaryAccumulateFcn functions[] = { +* stdlib_ndarray_accumulate_bb_b_0d, +* stdlib_ndarray_accumulate_bb_b_1d, +* stdlib_ndarray_accumulate_bb_b_2d, +* stdlib_ndarray_accumulate_bb_b_3d, +* stdlib_ndarray_accumulate_bb_b_4d, +* stdlib_ndarray_accumulate_bb_b_5d, +* stdlib_ndarray_accumulate_bb_b_6d, +* stdlib_ndarray_accumulate_bb_b_7d, +* stdlib_ndarray_accumulate_bb_b_8d, +* stdlib_ndarray_accumulate_bb_b_9d, +* stdlib_ndarray_accumulate_bb_b_10d +* stdlib_ndarray_accumulate_bb_b_nd +* }; + +* ndarrayUnaryAccumulateFcn blocked_functions[] = { +* stdlib_ndarray_accumulate_bb_b_2d_blocked, +* stdlib_ndarray_accumulate_bb_b_3d_blocked, +* stdlib_ndarray_accumulate_bb_b_4d_blocked, +* stdlib_ndarray_accumulate_bb_b_5d_blocked, +* stdlib_ndarray_accumulate_bb_b_6d_blocked, +* stdlib_ndarray_accumulate_bb_b_7d_blocked, +* stdlib_ndarray_accumulate_bb_b_8d_blocked, +* stdlib_ndarray_accumulate_bb_b_9d_blocked, +* stdlib_ndarray_accumulate_bb_b_10d_blocked +* }; +* +* ndarrayUnaryAccumulateDispatchObject obj = { +* functions, +* 12, +* blocked_functions +* 9 +* }; +* +* // ... +*/ +struct ndarrayUnaryAccumulateDispatchObject { + // Array containing ndarray functions for performing accumulation: + ndarrayUnaryAccumulateFcn *functions; + + // Number of ndarray functions: + int32_t nfunctions; + + // Array containing ndarray functions for performing accumulation using loop blocking: + ndarrayUnaryAccumulateFcn *blocked_functions; + + // Number of blocked ndarray functions: + int32_t nblockedfunctions; +}; + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_DISPATCH_OBJECT_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/permute.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/permute.h new file mode 100644 index 000000000000..147bb7125ff3 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/permute.h @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_PERMUTE_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_PERMUTE_H + +#include + +/** +* Permutes an input array according to a provided index array. +*/ +void stdlib_ndarray_base_unary_accumulate_internal_permute( const int64_t n, const int64_t *arr, const int64_t *idx, int64_t *out ); + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_PERMUTE_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/range.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/range.h new file mode 100644 index 000000000000..c2ff43a7f207 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/range.h @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_RANGE_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_RANGE_H + +#include + +/** +* Writes `n` evenly spaced values from `0` to `n-1` to an output array. +*/ +void stdlib_ndarray_base_unary_accumulate_internal_range( const int64_t n, int64_t *out ); + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_RANGE_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/sort2ins.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/sort2ins.h new file mode 100644 index 000000000000..bda3a8f9ce1d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/internal/sort2ins.h @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_SORT2INS_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_SORT2INS_H + +#include + +/** +* Simultaneously sorts two arrays based on the sort order of the first array using insertion sort. +*/ +void stdlib_ndarray_base_unary_accumulate_internal_sort2ins( const int64_t n, int64_t *x, int64_t *y ); + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_INTERNAL_SORT2INS_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros.h new file mode 100644 index 000000000000..5f39e931ea0b --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros.h @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_H + +#include "stdlib/ndarray/base/unary-accumulate/macros/constants.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/1d.h" +#include "stdlib/ndarray/base/unary-accumulate/macros/2d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/2d_blocked.h" +#include "stdlib/ndarray/base/unary-accumulate/macros/3d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/3d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/4d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/4d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/5d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/5d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/6d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/6d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/7d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/7d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/8d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/8d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/9d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/9d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/10d.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/10d_blocked.h" +// #include "stdlib/ndarray/base/unary-accumulate/macros/nd.h" + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/2d.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/2d.h new file mode 100644 index 000000000000..afe0883ea037 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/2d.h @@ -0,0 +1,222 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_2D_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_2D_H + +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/orders.h" +#include + +/** +* Macro containing the preamble for nested loops which operate on elements of a two-dimensional ndarray. +* +* ## Notes +* +* - Variable naming conventions: +* +* - `sx#`, `px#`, and `d@x#` where `#` corresponds to the ndarray argument number, starting at `1`. +* - `S@`, `i@`, and `d@x#` where `@` corresponds to the loop number, with `0` being the innermost loop. +* +* @param tout output type +* +* @example +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREMABLE( double ) { +* // Innermost loop body... +* } +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREAMBLE( tout ) \ + struct ndarray *x1 = arrays[ 0 ]; \ + struct ndarray *x2 = arrays[ 1 ]; \ + struct ndarray *x3 = arrays[ 2 ]; \ + int64_t *shape = stdlib_ndarray_shape( x1 ); \ + int64_t *sx1 = stdlib_ndarray_strides( x1 ); \ + uint8_t *px1 = stdlib_ndarray_data( x1 ); \ + uint8_t *px2 = stdlib_ndarray_data( x2 ); \ + uint8_t *px3 = stdlib_ndarray_data( x3 ); \ + int64_t d0x1; \ + int64_t d1x1; \ + int64_t S0; \ + int64_t S1; \ + int64_t i0; \ + int64_t i1; \ + tout acc; \ + /* Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... */ \ + if ( stdlib_ndarray_order( x1 ) == STDLIB_NDARRAY_ROW_MAJOR ) { \ + /* For row-major ndarrays, the last dimensions have the fastest changing indices... */ \ + S0 = shape[ 1 ]; \ + S1 = shape[ 0 ]; \ + d0x1 = sx1[ 1 ]; \ + d1x1 = sx1[ 0 ] - ( S0*sx1[1] ); \ + } else { \ + /* For column-major ndarrays, the first dimensions have the fastest changing indices... */ \ + S0 = shape[ 0 ]; \ + S1 = shape[ 1 ]; \ + d0x1 = sx1[ 0 ]; \ + d1x1 = sx1[ 1 ] - ( S0*sx1[0] ); \ + } \ + /* Set the pointers to the first indexed elements... */ \ + px1 += stdlib_ndarray_offset( x1 ); \ + px2 += stdlib_ndarray_offset( x2 ); \ + px3 += stdlib_ndarray_offset( x3 ); \ + /* Initialize the accumulator: */ \ + acc = (tout *)px2; \ + /* Iterate over the ndarray dimensions... */ \ + for ( i1 = 0; i1 < S1; i1++, px1 += d1x1 ) { \ + for ( i0 = 0; i0 < S0; i0++, px1 += d0x1 ) + +/** +* Macro containing the epilogue for nested loops which operate on elements of a two-dimensional ndarray. +* +* @param tout output type +* +* @example +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREMABLE( double ) { +* // Innermost loop body... +* } +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( tout ) \ + } \ + *(tout *)px3 = acc; + +/** +* Macro for a two-dimensional ndarray loop which inlines an expression. +* +* ## Notes +* +* - Retrieves each input ndarray element according to type `tin` via the pointer `px1` as `in1`. +* - Expects a provided expression to operate on `tin in1` and update `acc`. +* +* @param tin input type +* @param tout output type +* @param expr expression to inline +* +* @example +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_INLINE( double, double, acc += in1 ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_INLINE( tin, tout, expr ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREAMBLE( tout ) { \ + const tin in1 = *(tin *)px1; \ + expr; \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a two-dimensional ndarray loop which invokes a callback. +* +* ## Notes +* +* - Retrieves each input ndarray element according to type `tin` via the pointer `px1`. +* - Explicitly casts each function `f` invocation result to `tout`. +* +* @param tin input type +* @param tout output type +* +* @example +* // e.g., dd_d +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK( double, double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK( tin, tout ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = (tout)f( acc, x ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a two-dimensional loop which invokes a callback and does not cast the return callback's return value (e.g., a `struct`). +* +* ## Notes +* +* - Retrieves each input ndarray element according to type `tin` via a pointer `px1`. +* +* @param tin input type +* @param tout output type +* +* @example +* #include "stdlib/complex/float64/ctor.h" +* +* // e.g., zz_z +* STDLIB_NDARRAY_UNARY_2D_LOOP_CLBK_RET_NOCAST( stdlib_complex128_t, stdlib_complex128_t ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK_RET_NOCAST( tin, tout ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = f( acc, x ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a two-dimensional ndarray loop which invokes a callback requiring arguments be explicitly cast to a different type. +* +* ## Notes +* +* - Retrieves each ndarray element according to type `tin` via the pointer `px1`. +* - Explicitly casts each function accumulator argument to `fin1`. +* - Explicitly casts each function element argument to `fin2`. +* - Explicitly casts each function `f` invocation result to `tout`. +* +* @param tin input type +* @param tout output type +* @param fin1 callback accumulator argument type +* @param fin2 callback element argument type +* +* @example +* // e.g., ff_f_as_dd_d +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK_ARG_CAST( float, float, double, double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK_ARG_CAST( tin, tout, fin1, fin2 ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = (tout)f( (fin1)acc, (fin2)x ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a two-dimensional ndarray loop which invokes a callback requiring arguments be cast to a different type via casting functions. +* +* ## Notes +* +* - Retrieves each ndarray element according to type `tin` via a pointer `px1`. +* - Explicitly casts each function accumulator argument via `cin1`. +* - Explicitly casts each function element argument via `cin2`. +* - Explicitly casts each function `f` invocation result via `cout`. +* +* @param tin input type +* @param tout output type +* @param cin1 input casting function for the accumulator argument +* @param cin2 input casting function for the element argument +* @param cout output casting function +* +* @example +* #include "stdlib/complex/float32/ctor.h" +* #include "stdlib/complex/float64/ctor.h" +* +* // e.g., cf_c_as_zz_z +* STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK_ARG_CAST_FCN( float, stdlib_complex64_t, stdlib_complex128_from_complex64, stdlib_complex128_from_float32, stdlib_complex128_to_complex64 ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_CLBK_ARG_CAST_FCN( tin, tout, cin1, cin2, cout ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = cout( f( cin1( acc ), cin2( x ) ) ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_EPILOGUE( tout ) + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_2D_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/3d.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/3d.h new file mode 100644 index 000000000000..a7c506fea6c0 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/3d.h @@ -0,0 +1,231 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_3D_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_3D_H + +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/orders.h" +#include + +/** +* Macro containing the preamble for nested loops which operate on elements of a three-dimensional ndarray. +* +* ## Notes +* +* - Variable naming conventions: +* +* - `sx#`, `px#`, and `d@x#` where `#` corresponds to the ndarray argument number, starting at `1`. +* - `S@`, `i@`, and `d@x#` where `@` corresponds to the loop number, with `0` being the innermost loop. +* +* @param tout output type +* +* @example +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREMABLE( double ) { +* // Innermost loop body... +* } +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREAMBLE( tout ) \ + struct ndarray *x1 = arrays[ 0 ]; \ + struct ndarray *x2 = arrays[ 1 ]; \ + struct ndarray *x3 = arrays[ 2 ]; \ + int64_t *shape = stdlib_ndarray_shape( x1 ); \ + int64_t *sx1 = stdlib_ndarray_strides( x1 ); \ + uint8_t *px1 = stdlib_ndarray_data( x1 ); \ + uint8_t *px2 = stdlib_ndarray_data( x2 ); \ + uint8_t *px3 = stdlib_ndarray_data( x3 ); \ + int64_t d0x1; \ + int64_t d1x1; \ + int64_t d2x1; \ + int64_t S0; \ + int64_t S1; \ + int64_t S2; \ + int64_t i0; \ + int64_t i1; \ + int64_t i2; \ + tout acc; \ + /* Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... */ \ + if ( stdlib_ndarray_order( x1 ) == STDLIB_NDARRAY_ROW_MAJOR ) { \ + /* For row-major ndarrays, the last dimensions have the fastest changing indices... */ \ + S0 = shape[ 2 ]; \ + S1 = shape[ 1 ]; \ + S2 = shape[ 0 ]; \ + d0x1 = sx1[ 2 ]; \ + d1x1 = sx1[ 1 ] - ( S0*sx1[2] ); \ + d2x1 = sx1[ 0 ] - ( S1*sx1[1] ); \ + } else { \ + /* For column-major ndarrays, the first dimensions have the fastest changing indices... */ \ + S0 = shape[ 0 ]; \ + S1 = shape[ 1 ]; \ + S2 = shape[ 2 ]; \ + d0x1 = sx1[ 0 ]; \ + d1x1 = sx1[ 1 ] - ( S0*sx1[0] ); \ + d2x1 = sx1[ 2 ] - ( S1*sx1[1] ); \ + } \ + /* Set the pointers to the first indexed elements... */ \ + px1 += stdlib_ndarray_offset( x1 ); \ + px2 += stdlib_ndarray_offset( x2 ); \ + px3 += stdlib_ndarray_offset( x3 ); \ + /* Initialize the accumulator: */ \ + acc = (tout *)px2; \ + /* Iterate over the ndarray dimensions... */ \ + for ( i2 = 0; i2 < S2; i2++, px1 += d2x1 ) { \ + for ( i1 = 0; i1 < S1; i1++, px1 += d1x1 ) { \ + for ( i0 = 0; i0 < S0; i0++, px1 += d0x1 ) + +/** +* Macro containing the epilogue for nested loops which operate on elements of a three-dimensional ndarray. +* +* @param tout output type +* +* @example +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREMABLE( double ) { +* // Innermost loop body... +* } +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( tout ) \ + } \ + } \ + *(tout *)px3 = acc; + +/** +* Macro for a three-dimensional ndarray loop which inlines an expression. +* +* ## Notes +* +* - Retrieves each input ndarray element according to type `tin` via the pointer `px1` as `in1`. +* - Expects a provided expression to operate on `tin in1` and update `acc`. +* +* @param tin input type +* @param tout output type +* @param expr expression to inline +* +* @example +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_INLINE( double, double, acc += in1 ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_INLINE( tin, tout, expr ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREAMBLE( tout ) { \ + const tin in1 = *(tin *)px1; \ + expr; \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a three-dimensional ndarray loop which invokes a callback. +* +* ## Notes +* +* - Retrieves each input ndarray element according to type `tin` via the pointer `px1`. +* - Explicitly casts each function `f` invocation result to `tout`. +* +* @param tin input type +* @param tout output type +* +* @example +* // e.g., dd_d +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK( double, double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK( tin, tout ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = (tout)f( acc, x ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a three-dimensional loop which invokes a callback and does not cast the return callback's return value (e.g., a `struct`). +* +* ## Notes +* +* - Retrieves each input ndarray element according to type `tin` via a pointer `px1`. +* +* @param tin input type +* @param tout output type +* +* @example +* #include "stdlib/complex/float64/ctor.h" +* +* // e.g., zz_z +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK_RET_NOCAST( stdlib_complex128_t, stdlib_complex128_t ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK_RET_NOCAST( tin, tout ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = f( acc, x ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a three-dimensional ndarray loop which invokes a callback requiring arguments be explicitly cast to a different type. +* +* ## Notes +* +* - Retrieves each ndarray element according to type `tin` via the pointer `px1`. +* - Explicitly casts each function accumulator argument to `fin1`. +* - Explicitly casts each function element argument to `fin2`. +* - Explicitly casts each function `f` invocation result to `tout`. +* +* @param tin input type +* @param tout output type +* @param fin1 callback accumulator argument type +* @param fin2 callback element argument type +* +* @example +* // e.g., ff_f_as_dd_d +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK_ARG_CAST( float, float, double, double ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK_ARG_CAST( tin, tout, fin1, fin2 ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = (tout)f( (fin1)acc, (fin2)x ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( tout ) + +/** +* Macro for a three-dimensional ndarray loop which invokes a callback requiring arguments be cast to a different type via casting functions. +* +* ## Notes +* +* - Retrieves each ndarray element according to type `tin` via a pointer `px1`. +* - Explicitly casts each function accumulator argument via `cin1`. +* - Explicitly casts each function element argument via `cin2`. +* - Explicitly casts each function `f` invocation result via `cout`. +* +* @param tin input type +* @param tout output type +* @param cin1 input casting function for the accumulator argument +* @param cin2 input casting function for the element argument +* @param cout output casting function +* +* @example +* #include "stdlib/complex/float32/ctor.h" +* #include "stdlib/complex/float64/ctor.h" +* +* // e.g., cf_c_as_zz_z +* STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK_ARG_CAST_FCN( float, stdlib_complex64_t, stdlib_complex128_from_complex64, stdlib_complex128_from_float32, stdlib_complex128_to_complex64 ) +*/ +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_CLBK_ARG_CAST_FCN( tin, tout, cin1, cin2, cout ) \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_PREAMBLE( tout ) { \ + const tin x = *(tin *)px1; \ + acc = cout( f( cin1( acc ), cin2( x ) ) ); \ + } \ + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_EPILOGUE( tout ) + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_3D_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/constants.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/constants.h new file mode 100644 index 000000000000..344dc02e3938 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/macros/constants.h @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_CONSTANTS_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_CONSTANTS_H + +// Define a default block size in units of bytes (Note: 64b is a common cache line size. How applicable the common cache line size is here is debatable, given that, depending on the associated stride(s), the innermost loop may not iterate over adjacent elements. The primary goal is to have a block size in which all data within a block can always fit in (L1) cache, regardless of cache size (i.e., cache-oblivious). For reference, a common L1 cache size is 32kB per core. For best performance, block sizes should be tuned based on system hardware; however, such tuning is not readily available to us here. Without obvious better alternatives, 64b has some theoretical (and practical) underpinning, and it should be good enough for most inputs, especially for ndarrays with near contiguity.): +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_BLOCK_SIZE_IN_BYTES 64 + +// Define a default block size in units of elements (Note: 64 bytes / 8 bytes per element; i.e., default element size is same as a double): +#define STDLIB_NDARRAY_UNARY_ACCUMULATE_BLOCK_SIZE_IN_ELEMENTS 8 + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_MACROS_CONSTANTS_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/typedefs.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/typedefs.h new file mode 100644 index 000000000000..ad6e714760fd --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary-accumulate/typedefs.h @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_TYPEDEFS_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_TYPEDEFS_H + +#include "stdlib/ndarray/ctor.h" +#include + +/** +* Function pointer type for an ndarray accumulation function. +* +* ## Note +* +* - This must match the definition of an `ndarrayFcn` found in `@stdlib/ndarray/base/function-object`. +* +* @param arrays array containing pointers to input and output ndarrays +* @param data function "data" (e.g., a callback) +* @return status code +*/ +typedef int8_t (*ndarrayUnaryAccumulateFcn)( struct ndarray *arrays[], void *data ); + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_TYPEDEFS_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary_accumulate.h b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary_accumulate.h new file mode 100644 index 000000000000..4add9494680e --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/include/stdlib/ndarray/base/unary_accumulate.h @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/** +* Header file containing function declarations. +*/ +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_H + +#include "unary-accumulate/macros.h" +#include "unary-accumulate/typedefs.h" +#include "unary-accumulate/dispatch_object.h" +#include "unary-accumulate/dispatch.h" + +/* +* The following is auto-generated. Do not manually edit. See scripts/loops.js. +*/ + +// BEGIN LOOPS + +// END LOOPS + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/0d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/0d.js new file mode 100644 index 000000000000..63c3af94a1c3 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/0d.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a zero-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0 ] ); +* +* // Define the shape of the input array: +* var shape = []; +* +* // Define the array strides: +* var sx = [ 0 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate0d( x, 0.0, add ); +* // returns 2.0 +*/ +function accumulate0d( x, initial, clbk ) { + return clbk( initial, x.data[ x.offset ] ); +} + + +// EXPORTS // + +module.exports = accumulate0d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/0d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/0d_accessors.js new file mode 100644 index 000000000000..1b94918e9369 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/0d_accessors.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a zero-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* +* // Define the shape of the input array: +* var shape = []; +* +* // Define the array strides: +* var sx = [ 0 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate0d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 3.0 +* +* var im = imagf( v ); +* // returns 4.0 +*/ +function accumulate0d( x, initial, clbk ) { + return clbk( initial, x.accessors[ 0 ]( x.data, x.offset ) ); +} + + +// EXPORTS // + +module.exports = accumulate0d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d.js new file mode 100644 index 000000000000..de28becb46b3 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d.js @@ -0,0 +1,207 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, node/callback-return */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate10d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate10d( x, initial, clbk ) { // eslint-disable-line max-statements + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var dx9; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var S7; + var S8; + var S9; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + var i9; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 9 ]; + S1 = sh[ 8 ]; + S2 = sh[ 7 ]; + S3 = sh[ 6 ]; + S4 = sh[ 5 ]; + S5 = sh[ 4 ]; + S6 = sh[ 3 ]; + S7 = sh[ 2 ]; + S8 = sh[ 1 ]; + S9 = sh[ 0 ]; + dx0 = sx[ 9 ]; // offset increment for innermost loop + dx1 = sx[ 8 ] - ( S0*sx[9] ); + dx2 = sx[ 7 ] - ( S1*sx[8] ); + dx3 = sx[ 6 ] - ( S2*sx[7] ); + dx4 = sx[ 5 ] - ( S3*sx[6] ); + dx5 = sx[ 4 ] - ( S4*sx[5] ); + dx6 = sx[ 3 ] - ( S5*sx[4] ); + dx7 = sx[ 2 ] - ( S6*sx[3] ); + dx8 = sx[ 1 ] - ( S7*sx[2] ); + dx9 = sx[ 0 ] - ( S8*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + S7 = sh[ 7 ]; + S8 = sh[ 8 ]; + S9 = sh[ 9 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); + dx7 = sx[ 7 ] - ( S6*sx[6] ); + dx8 = sx[ 8 ] - ( S7*sx[7] ); + dx9 = sx[ 9 ] - ( S8*sx[8] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i9 = 0; i9 < S9; i9++ ) { + for ( i8 = 0; i8 < S8; i8++ ) { + for ( i7 = 0; i7 < S7; i7++ ) { + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + ix += dx9; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate10d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_accessors.js new file mode 100644 index 000000000000..735c236c5c91 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_accessors.js @@ -0,0 +1,231 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, node/callback-return */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate10d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate10d( x, initial, clbk ) { // eslint-disable-line max-statements + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var dx9; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var S7; + var S8; + var S9; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + var i9; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 9 ]; + S1 = sh[ 8 ]; + S2 = sh[ 7 ]; + S3 = sh[ 6 ]; + S4 = sh[ 5 ]; + S5 = sh[ 4 ]; + S6 = sh[ 3 ]; + S7 = sh[ 2 ]; + S8 = sh[ 1 ]; + S9 = sh[ 0 ]; + dx0 = sx[ 9 ]; // offset increment for innermost loop + dx1 = sx[ 8 ] - ( S0*sx[9] ); + dx2 = sx[ 7 ] - ( S1*sx[8] ); + dx3 = sx[ 6 ] - ( S2*sx[7] ); + dx4 = sx[ 5 ] - ( S3*sx[6] ); + dx5 = sx[ 4 ] - ( S4*sx[5] ); + dx6 = sx[ 3 ] - ( S5*sx[4] ); + dx7 = sx[ 2 ] - ( S6*sx[3] ); + dx8 = sx[ 1 ] - ( S7*sx[2] ); + dx9 = sx[ 0 ] - ( S8*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + S7 = sh[ 7 ]; + S8 = sh[ 8 ]; + S9 = sh[ 9 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); + dx7 = sx[ 7 ] - ( S6*sx[6] ); + dx8 = sx[ 8 ] - ( S7*sx[7] ); + dx9 = sx[ 9 ] - ( S8*sx[8] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i9 = 0; i9 < S9; i9++ ) { + for ( i8 = 0; i8 < S8; i8++ ) { + for ( i7 = 0; i7 < S7; i7++ ) { + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + ix += dx9; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate10d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_blocked.js new file mode 100644 index 000000000000..f71a1d58aa70 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_blocked.js @@ -0,0 +1,312 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len, node/callback-return */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate10d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate10d( x, initial, clbk ) { // eslint-disable-line max-statements, max-lines-per-function + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var dx9; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var ox7; + var ox8; + var ox9; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var s7; + var s8; + var s9; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + var i9; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var j7; + var j8; + var j9; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j9 = sh[9]; j9 > 0; ) { + if ( j9 < bsize ) { + s9 = j9; + j9 = 0; + } else { + s9 = bsize; + j9 -= bsize; + } + ox9 = ox + ( j9*sx[9] ); + for ( j8 = sh[8]; j8 > 0; ) { + if ( j8 < bsize ) { + s8 = j8; + j8 = 0; + } else { + s8 = bsize; + j8 -= bsize; + } + dx9 = sx[9] - ( s8*sx[8] ); + ox8 = ox9 + ( j8*sx[8] ); + for ( j7 = sh[7]; j7 > 0; ) { + if ( j7 < bsize ) { + s7 = j7; + j7 = 0; + } else { + s7 = bsize; + j7 -= bsize; + } + dx8 = sx[8] - ( s7*sx[7] ); + ox7 = ox8 + ( j7*sx[7] ); + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + dx7 = sx[7] - ( s6*sx[6] ); + ox6 = ox7 + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i9 = 0; i9 < s9; i9++ ) { + for ( i8 = 0; i8 < s8; i8++ ) { + for ( i7 = 0; i7 < s7; i7++ ) { + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + ix += dx9; + } + } + } + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate10d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_blocked_accessors.js new file mode 100644 index 000000000000..3f257ccf6d8d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/10d_blocked_accessors.js @@ -0,0 +1,336 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len, node/callback-return */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate10d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate10d( x, initial, clbk ) { // eslint-disable-line max-statements, max-lines-per-function + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var dx9; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var ox7; + var ox8; + var ox9; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var s7; + var s8; + var s9; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + var i9; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var j7; + var j8; + var j9; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j9 = sh[9]; j9 > 0; ) { + if ( j9 < bsize ) { + s9 = j9; + j9 = 0; + } else { + s9 = bsize; + j9 -= bsize; + } + ox9 = ox + ( j9*sx[9] ); + for ( j8 = sh[8]; j8 > 0; ) { + if ( j8 < bsize ) { + s8 = j8; + j8 = 0; + } else { + s8 = bsize; + j8 -= bsize; + } + dx9 = sx[9] - ( s8*sx[8] ); + ox8 = ox9 + ( j8*sx[8] ); + for ( j7 = sh[7]; j7 > 0; ) { + if ( j7 < bsize ) { + s7 = j7; + j7 = 0; + } else { + s7 = bsize; + j7 -= bsize; + } + dx8 = sx[8] - ( s7*sx[7] ); + ox7 = ox8 + ( j7*sx[7] ); + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + dx7 = sx[7] - ( s6*sx[6] ); + ox6 = ox7 + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i9 = 0; i9 < s9; i9++ ) { + for ( i8 = 0; i8 < s8; i8++ ) { + for ( i7 = 0; i7 < s7; i7++ ) { + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + ix += dx9; + } + } + } + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate10d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/1d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/1d.js new file mode 100644 index 000000000000..5b926ce3ff0d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/1d.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a one-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 4 ]; +* +* // Define the array strides: +* var sx = [ 2 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate1d( x, 0.0, add ); +* // returns 20.0 +*/ +function accumulate1d( x, initial, clbk ) { + var xbuf; + var dx0; + var acc; + var S0; + var ix; + var i0; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables: dimensions and loop offset (pointer) increments... + S0 = x.shape[ 0 ]; + dx0 = x.strides[ 0 ]; + + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate1d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/1d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/1d_accessors.js new file mode 100644 index 000000000000..ddeb27a3e623 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/1d_accessors.js @@ -0,0 +1,129 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a one-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 4 ]; +* +* // Define the array strides: +* var sx = [ 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate1d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate1d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var acc; + var S0; + var ix; + var i0; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables: dimensions and loop offset (pointer) increments... + S0 = x.shape[ 0 ]; + dx0 = x.strides[ 0 ]; + + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate1d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d.js new file mode 100644 index 000000000000..fb424ab68c60 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a two-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate2d( x, 0.0, add ); +* // returns 18.0 +*/ +function accumulate2d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var acc; + var sh; + var S0; + var S1; + var sx; + var ix; + var i0; + var i1; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 1 ]; + S1 = sh[ 0 ]; + dx0 = sx[ 1 ]; // offset increment for innermost loop + dx1 = sx[ 0 ] - ( S0*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate2d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_accessors.js new file mode 100644 index 000000000000..1ed5d70b593b --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_accessors.js @@ -0,0 +1,149 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a two-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate2d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate2d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var acc; + var sh; + var S0; + var S1; + var sx; + var ix; + var i0; + var i1; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 1 ]; + S1 = sh[ 0 ]; + dx0 = sx[ 1 ]; // offset increment for innermost loop + dx1 = sx[ 0 ] - ( S0*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate2d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_blocked.js new file mode 100644 index 000000000000..4e4126e008b3 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_blocked.js @@ -0,0 +1,158 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a two-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate2d( x, 0.0, add ); +* // returns 18.0 +*/ +function blockedaccumulate2d( x, initial, clbk ) { + var bsize; + var xbuf; + var dx0; + var dx1; + var ox1; + var acc; + var sh; + var s0; + var s1; + var sx; + var ox; + var ix; + var i0; + var i1; + var j0; + var j1; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + ox1 = ox + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate2d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_blocked_accessors.js new file mode 100644 index 000000000000..18cec37df53a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/2d_blocked_accessors.js @@ -0,0 +1,182 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a two-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate2d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate2d( x, initial, clbk ) { + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var ox1; + var acc; + var sh; + var s0; + var s1; + var sx; + var ox; + var ix; + var i0; + var i1; + var j0; + var j1; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + ox1 = ox + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate2d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d.js new file mode 100644 index 000000000000..7c97ec58e5b8 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d.js @@ -0,0 +1,135 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a three-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate3d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate3d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var acc; + var sh; + var S0; + var S1; + var S2; + var sx; + var ix; + var i0; + var i1; + var i2; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 2 ]; + S1 = sh[ 1 ]; + S2 = sh[ 0 ]; + dx0 = sx[ 2 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[2] ); + dx2 = sx[ 0 ] - ( S1*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate3d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_accessors.js new file mode 100644 index 000000000000..a448c51acac4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_accessors.js @@ -0,0 +1,159 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a three-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate3d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate3d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var acc; + var sh; + var S0; + var S1; + var S2; + var sx; + var ix; + var i0; + var i1; + var i2; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 2 ]; + S1 = sh[ 1 ]; + S2 = sh[ 0 ]; + dx0 = sx[ 2 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[2] ); + dx2 = sx[ 0 ] - ( S1*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate3d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_blocked.js new file mode 100644 index 000000000000..95910044f6e5 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_blocked.js @@ -0,0 +1,179 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a three-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate3d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate3d( x, initial, clbk ) { + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var ox1; + var ox2; + var acc; + var sh; + var s0; + var s1; + var s2; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var j0; + var j1; + var j2; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + ox2 = ox + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate3d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_blocked_accessors.js new file mode 100644 index 000000000000..e4403ca91714 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/3d_blocked_accessors.js @@ -0,0 +1,203 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a three-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate3d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate3d( x, initial, clbk ) { + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var ox1; + var ox2; + var acc; + var sh; + var s0; + var s1; + var s2; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var j0; + var j1; + var j2; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + ox2 = ox + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate3d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d.js new file mode 100644 index 000000000000..02b70532cb1c --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d.js @@ -0,0 +1,145 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a four-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate4d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate4d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 3 ]; + S1 = sh[ 2 ]; + S2 = sh[ 1 ]; + S3 = sh[ 0 ]; + dx0 = sx[ 3 ]; // offset increment for innermost loop + dx1 = sx[ 2 ] - ( S0*sx[3] ); + dx2 = sx[ 1 ] - ( S1*sx[2] ); + dx3 = sx[ 0 ] - ( S2*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate4d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_accessors.js new file mode 100644 index 000000000000..d422d917549f --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_accessors.js @@ -0,0 +1,169 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a four-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate4d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate4d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 3 ]; + S1 = sh[ 2 ]; + S2 = sh[ 1 ]; + S3 = sh[ 0 ]; + dx0 = sx[ 3 ]; // offset increment for innermost loop + dx1 = sx[ 2 ] - ( S0*sx[3] ); + dx2 = sx[ 1 ] - ( S1*sx[2] ); + dx3 = sx[ 0 ] - ( S2*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate4d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_blocked.js new file mode 100644 index 000000000000..5332cdfe664f --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_blocked.js @@ -0,0 +1,198 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a four-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate4d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate4d( x, initial, clbk ) { + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var ox1; + var ox2; + var ox3; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var j0; + var j1; + var j2; + var j3; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + ox3 = ox + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate4d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_blocked_accessors.js new file mode 100644 index 000000000000..b9c3acffc433 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/4d_blocked_accessors.js @@ -0,0 +1,222 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a four-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate4d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate4d( x, initial, clbk ) { + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var ox1; + var ox2; + var ox3; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var j0; + var j1; + var j2; + var j3; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + ox3 = ox + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate4d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d.js new file mode 100644 index 000000000000..4d34115f3f55 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d.js @@ -0,0 +1,155 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a five-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate5d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate5d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 4 ]; + S1 = sh[ 3 ]; + S2 = sh[ 2 ]; + S3 = sh[ 1 ]; + S4 = sh[ 0 ]; + dx0 = sx[ 4 ]; // offset increment for innermost loop + dx1 = sx[ 3 ] - ( S0*sx[4] ); + dx2 = sx[ 2 ] - ( S1*sx[3] ); + dx3 = sx[ 1 ] - ( S2*sx[2] ); + dx4 = sx[ 0 ] - ( S3*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate5d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_accessors.js new file mode 100644 index 000000000000..9076bc70a17f --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_accessors.js @@ -0,0 +1,179 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a five-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate5d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate5d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 4 ]; + S1 = sh[ 3 ]; + S2 = sh[ 2 ]; + S3 = sh[ 1 ]; + S4 = sh[ 0 ]; + dx0 = sx[ 4 ]; // offset increment for innermost loop + dx1 = sx[ 3 ] - ( S0*sx[4] ); + dx2 = sx[ 2 ] - ( S1*sx[3] ); + dx3 = sx[ 1 ] - ( S2*sx[2] ); + dx4 = sx[ 0 ] - ( S3*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate5d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_blocked.js new file mode 100644 index 000000000000..6da75954b29d --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_blocked.js @@ -0,0 +1,217 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a five-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate5d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate5d( x, initial, clbk ) { + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var ox1; + var ox2; + var ox3; + var ox4; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var j0; + var j1; + var j2; + var j3; + var j4; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + ox4 = ox + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate5d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_blocked_accessors.js new file mode 100644 index 000000000000..9da433afe91a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/5d_blocked_accessors.js @@ -0,0 +1,241 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a five-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate5d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate5d( x, initial, clbk ) { + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var ox1; + var ox2; + var ox3; + var ox4; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var j0; + var j1; + var j2; + var j3; + var j4; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + ox4 = ox + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate5d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d.js new file mode 100644 index 000000000000..f84e3ae3fa73 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d.js @@ -0,0 +1,167 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a six-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate6d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate6d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 5 ]; + S1 = sh[ 4 ]; + S2 = sh[ 3 ]; + S3 = sh[ 2 ]; + S4 = sh[ 1 ]; + S5 = sh[ 0 ]; + dx0 = sx[ 5 ]; // offset increment for innermost loop + dx1 = sx[ 4 ] - ( S0*sx[5] ); + dx2 = sx[ 3 ] - ( S1*sx[4] ); + dx3 = sx[ 2 ] - ( S2*sx[3] ); + dx4 = sx[ 1 ] - ( S3*sx[2] ); + dx5 = sx[ 0 ] - ( S4*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate6d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_accessors.js new file mode 100644 index 000000000000..4543b1c93cfb --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_accessors.js @@ -0,0 +1,191 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a six-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate6d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate6d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 5 ]; + S1 = sh[ 4 ]; + S2 = sh[ 3 ]; + S3 = sh[ 2 ]; + S4 = sh[ 1 ]; + S5 = sh[ 0 ]; + dx0 = sx[ 5 ]; // offset increment for innermost loop + dx1 = sx[ 4 ] - ( S0*sx[5] ); + dx2 = sx[ 3 ] - ( S1*sx[4] ); + dx3 = sx[ 2 ] - ( S2*sx[3] ); + dx4 = sx[ 1 ] - ( S3*sx[2] ); + dx5 = sx[ 0 ] - ( S4*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate6d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_blocked.js new file mode 100644 index 000000000000..ca6c703520cd --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_blocked.js @@ -0,0 +1,236 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a six-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate6d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate6d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + ox5 = ox + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate6d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_blocked_accessors.js new file mode 100644 index 000000000000..90138c63f8b9 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/6d_blocked_accessors.js @@ -0,0 +1,260 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a six-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate6d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate6d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + ox5 = ox + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate6d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d.js new file mode 100644 index 000000000000..4e510dc36918 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d.js @@ -0,0 +1,177 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate7d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate7d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 6 ]; + S1 = sh[ 5 ]; + S2 = sh[ 4 ]; + S3 = sh[ 3 ]; + S4 = sh[ 2 ]; + S5 = sh[ 1 ]; + S6 = sh[ 0 ]; + dx0 = sx[ 6 ]; // offset increment for innermost loop + dx1 = sx[ 5 ] - ( S0*sx[6] ); + dx2 = sx[ 4 ] - ( S1*sx[5] ); + dx3 = sx[ 3 ] - ( S2*sx[4] ); + dx4 = sx[ 2 ] - ( S3*sx[3] ); + dx5 = sx[ 1 ] - ( S4*sx[2] ); + dx6 = sx[ 0 ] - ( S5*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate7d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_accessors.js new file mode 100644 index 000000000000..63d9cc197cc2 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_accessors.js @@ -0,0 +1,201 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate7d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate7d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 6 ]; + S1 = sh[ 5 ]; + S2 = sh[ 4 ]; + S3 = sh[ 3 ]; + S4 = sh[ 2 ]; + S5 = sh[ 1 ]; + S6 = sh[ 0 ]; + dx0 = sx[ 6 ]; // offset increment for innermost loop + dx1 = sx[ 5 ] - ( S0*sx[6] ); + dx2 = sx[ 4 ] - ( S1*sx[5] ); + dx3 = sx[ 3 ] - ( S2*sx[4] ); + dx4 = sx[ 2 ] - ( S3*sx[3] ); + dx5 = sx[ 1 ] - ( S4*sx[2] ); + dx6 = sx[ 0 ] - ( S5*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate7d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_blocked.js new file mode 100644 index 000000000000..44639393acec --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_blocked.js @@ -0,0 +1,255 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate7d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate7d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + ox6 = ox + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate7d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_blocked_accessors.js new file mode 100644 index 000000000000..9b33477bc802 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/7d_blocked_accessors.js @@ -0,0 +1,279 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate7d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate7d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + ox6 = ox + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate7d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d.js new file mode 100644 index 000000000000..e0126a820d55 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d.js @@ -0,0 +1,187 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in an eight-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate8d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate8d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var S7; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 7 ]; + S1 = sh[ 6 ]; + S2 = sh[ 5 ]; + S3 = sh[ 4 ]; + S4 = sh[ 3 ]; + S5 = sh[ 2 ]; + S6 = sh[ 1 ]; + S7 = sh[ 0 ]; + dx0 = sx[ 7 ]; // offset increment for innermost loop + dx1 = sx[ 6 ] - ( S0*sx[7] ); + dx2 = sx[ 5 ] - ( S1*sx[6] ); + dx3 = sx[ 4 ] - ( S2*sx[5] ); + dx4 = sx[ 3 ] - ( S3*sx[4] ); + dx5 = sx[ 2 ] - ( S4*sx[3] ); + dx6 = sx[ 1 ] - ( S5*sx[2] ); + dx7 = sx[ 0 ] - ( S6*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + S7 = sh[ 7 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); + dx7 = sx[ 7 ] - ( S6*sx[6] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i7 = 0; i7 < S7; i7++ ) { + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate8d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_accessors.js new file mode 100644 index 000000000000..74116d6f228a --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_accessors.js @@ -0,0 +1,211 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in an eight-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate8d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate8d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var S7; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 7 ]; + S1 = sh[ 6 ]; + S2 = sh[ 5 ]; + S3 = sh[ 4 ]; + S4 = sh[ 3 ]; + S5 = sh[ 2 ]; + S6 = sh[ 1 ]; + S7 = sh[ 0 ]; + dx0 = sx[ 7 ]; // offset increment for innermost loop + dx1 = sx[ 6 ] - ( S0*sx[7] ); + dx2 = sx[ 5 ] - ( S1*sx[6] ); + dx3 = sx[ 4 ] - ( S2*sx[5] ); + dx4 = sx[ 3 ] - ( S3*sx[4] ); + dx5 = sx[ 2 ] - ( S4*sx[3] ); + dx6 = sx[ 1 ] - ( S5*sx[2] ); + dx7 = sx[ 0 ] - ( S6*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + S7 = sh[ 7 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); + dx7 = sx[ 7 ] - ( S6*sx[6] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i7 = 0; i7 < S7; i7++ ) { + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate8d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_blocked.js new file mode 100644 index 000000000000..994e9afd21b0 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_blocked.js @@ -0,0 +1,274 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in an eight-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate8d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate8d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var ox7; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var s7; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var j7; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j7 = sh[7]; j7 > 0; ) { + if ( j7 < bsize ) { + s7 = j7; + j7 = 0; + } else { + s7 = bsize; + j7 -= bsize; + } + ox7 = ox + ( j7*sx[7] ); + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + dx7 = sx[7] - ( s6*sx[6] ); + ox6 = ox7 + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i7 = 0; i7 < s7; i7++ ) { + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate8d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_blocked_accessors.js new file mode 100644 index 000000000000..0d95e3dbebda --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/8d_blocked_accessors.js @@ -0,0 +1,298 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in an eight-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate8d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate8d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var ox7; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var s7; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var j7; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j7 = sh[7]; j7 > 0; ) { + if ( j7 < bsize ) { + s7 = j7; + j7 = 0; + } else { + s7 = bsize; + j7 -= bsize; + } + ox7 = ox + ( j7*sx[7] ); + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + dx7 = sx[7] - ( s6*sx[6] ); + ox6 = ox7 + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i7 = 0; i7 < s7; i7++ ) { + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate8d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d.js new file mode 100644 index 000000000000..6dda55f7cae9 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d.js @@ -0,0 +1,197 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulate9d( x, 0.0, add ); +* // returns 39.0 +*/ +function accumulate9d( x, initial, clbk ) { + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var S7; + var S8; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 8 ]; + S1 = sh[ 7 ]; + S2 = sh[ 6 ]; + S3 = sh[ 5 ]; + S4 = sh[ 4 ]; + S5 = sh[ 3 ]; + S6 = sh[ 2 ]; + S7 = sh[ 1 ]; + S8 = sh[ 0 ]; + dx0 = sx[ 8 ]; // offset increment for innermost loop + dx1 = sx[ 7 ] - ( S0*sx[8] ); + dx2 = sx[ 6 ] - ( S1*sx[7] ); + dx3 = sx[ 5 ] - ( S2*sx[6] ); + dx4 = sx[ 4 ] - ( S3*sx[5] ); + dx5 = sx[ 3 ] - ( S4*sx[4] ); + dx6 = sx[ 2 ] - ( S5*sx[3] ); + dx7 = sx[ 1 ] - ( S6*sx[2] ); + dx8 = sx[ 0 ] - ( S7*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + S7 = sh[ 7 ]; + S8 = sh[ 8 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); + dx7 = sx[ 7 ] - ( S6*sx[6] ); + dx8 = sx[ 8 ] - ( S7*sx[7] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i8 = 0; i8 < S8; i8++ ) { + for ( i7 = 0; i7 < S7; i7++ ) { + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate9d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_accessors.js new file mode 100644 index 000000000000..0b71ef069b14 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_accessors.js @@ -0,0 +1,221 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth */ + +'use strict'; + +// MAIN // + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulate9d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulate9d( x, initial, clbk ) { + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var acc; + var sh; + var S0; + var S1; + var S2; + var S3; + var S4; + var S5; + var S6; + var S7; + var S8; + var sx; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + + // Note on variable naming convention: S#, dx#, i# where # corresponds to the loop number, with `0` being the innermost loop... + + // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... + sh = x.shape; + sx = x.strides; + if ( x.order === 'row-major' ) { + // For row-major ndarrays, the last dimensions have the fastest changing indices... + S0 = sh[ 8 ]; + S1 = sh[ 7 ]; + S2 = sh[ 6 ]; + S3 = sh[ 5 ]; + S4 = sh[ 4 ]; + S5 = sh[ 3 ]; + S6 = sh[ 2 ]; + S7 = sh[ 1 ]; + S8 = sh[ 0 ]; + dx0 = sx[ 8 ]; // offset increment for innermost loop + dx1 = sx[ 7 ] - ( S0*sx[8] ); + dx2 = sx[ 6 ] - ( S1*sx[7] ); + dx3 = sx[ 5 ] - ( S2*sx[6] ); + dx4 = sx[ 4 ] - ( S3*sx[5] ); + dx5 = sx[ 3 ] - ( S4*sx[4] ); + dx6 = sx[ 2 ] - ( S5*sx[3] ); + dx7 = sx[ 1 ] - ( S6*sx[2] ); + dx8 = sx[ 0 ] - ( S7*sx[1] ); // offset increment for outermost loop + } else { // order === 'column-major' + // For column-major ndarrays, the first dimensions have the fastest changing indices... + S0 = sh[ 0 ]; + S1 = sh[ 1 ]; + S2 = sh[ 2 ]; + S3 = sh[ 3 ]; + S4 = sh[ 4 ]; + S5 = sh[ 5 ]; + S6 = sh[ 6 ]; + S7 = sh[ 7 ]; + S8 = sh[ 8 ]; + dx0 = sx[ 0 ]; // offset increment for innermost loop + dx1 = sx[ 1 ] - ( S0*sx[0] ); + dx2 = sx[ 2 ] - ( S1*sx[1] ); + dx3 = sx[ 3 ] - ( S2*sx[2] ); + dx4 = sx[ 4 ] - ( S3*sx[3] ); + dx5 = sx[ 5 ] - ( S4*sx[4] ); + dx6 = sx[ 6 ] - ( S5*sx[5] ); + dx7 = sx[ 7 ] - ( S6*sx[6] ); + dx8 = sx[ 8 ] - ( S7*sx[7] ); // offset increment for outermost loop + } + // Set the pointer to the first indexed element: + ix = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over the ndarray dimensions... + for ( i8 = 0; i8 < S8; i8++ ) { + for ( i7 = 0; i7 < S7; i7++ ) { + for ( i6 = 0; i6 < S6; i6++ ) { + for ( i5 = 0; i5 < S5; i5++ ) { + for ( i4 = 0; i4 < S4; i4++ ) { + for ( i3 = 0; i3 < S3; i3++ ) { + for ( i2 = 0; i2 < S2; i2++ ) { + for ( i1 = 0; i1 < S1; i1++ ) { + for ( i0 = 0; i0 < S0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulate9d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_blocked.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_blocked.js new file mode 100644 index 000000000000..aae1a0ddb9c0 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_blocked.js @@ -0,0 +1,293 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 12, 12, 12, 12, 12, 12, 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = blockedaccumulate9d( x, 0.0, add ); +* // returns 39.0 +*/ +function blockedaccumulate9d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var ox7; + var ox8; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var s7; + var s8; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var j7; + var j8; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j8 = sh[8]; j8 > 0; ) { + if ( j8 < bsize ) { + s8 = j8; + j8 = 0; + } else { + s8 = bsize; + j8 -= bsize; + } + ox8 = ox + ( j8*sx[8] ); + for ( j7 = sh[7]; j7 > 0; ) { + if ( j7 < bsize ) { + s7 = j7; + j7 = 0; + } else { + s7 = bsize; + j7 -= bsize; + } + dx8 = sx[8] - ( s7*sx[7] ); + ox7 = ox8 + ( j7*sx[7] ); + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + dx7 = sx[7] - ( s6*sx[6] ); + ox6 = ox7 + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i8 = 0; i8 < s8; i8++ ) { + for ( i7 = 0; i7 < s7; i7++ ) { + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + } + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate9d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_blocked_accessors.js new file mode 100644 index 000000000000..226326601855 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/9d_blocked_accessors.js @@ -0,0 +1,317 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-depth, max-len */ + +'use strict'; + +// MODULES // + +var loopOrder = require( '@stdlib/ndarray/base/nullary-loop-interchange-order' ); +var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' ); + + +// MAIN // + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray via loop blocking. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 1, 1, 1, 1, 1, 1, 1, 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 4, 4, 4, 4, 4, 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = blockedaccumulate9d( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function blockedaccumulate9d( x, initial, clbk ) { // eslint-disable-line max-statements + var bsize; + var xbuf; + var get; + var dx0; + var dx1; + var dx2; + var dx3; + var dx4; + var dx5; + var dx6; + var dx7; + var dx8; + var ox1; + var ox2; + var ox3; + var ox4; + var ox5; + var ox6; + var ox7; + var ox8; + var acc; + var sh; + var s0; + var s1; + var s2; + var s3; + var s4; + var s5; + var s6; + var s7; + var s8; + var sx; + var ox; + var ix; + var i0; + var i1; + var i2; + var i3; + var i4; + var i5; + var i6; + var i7; + var i8; + var j0; + var j1; + var j2; + var j3; + var j4; + var j5; + var j6; + var j7; + var j8; + var o; + + // Note on variable naming convention: s#, dx#, i#, j# where # corresponds to the loop number, with `0` being the innermost loop... + + // Resolve the loop interchange order: + o = loopOrder( x.shape, x.strides ); + sh = o.sh; + sx = o.sx; + + // Determine the block size: + bsize = blockSize( x.dtype ); + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache a reference to the input ndarray buffer: + xbuf = x.data; + + // Cache the offset increment for the innermost loop: + dx0 = sx[0]; + + // Cache the accessor: + get = x.accessors[0]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over blocks... + for ( j8 = sh[8]; j8 > 0; ) { + if ( j8 < bsize ) { + s8 = j8; + j8 = 0; + } else { + s8 = bsize; + j8 -= bsize; + } + ox8 = ox + ( j8*sx[8] ); + for ( j7 = sh[7]; j7 > 0; ) { + if ( j7 < bsize ) { + s7 = j7; + j7 = 0; + } else { + s7 = bsize; + j7 -= bsize; + } + dx8 = sx[8] - ( s7*sx[7] ); + ox7 = ox8 + ( j7*sx[7] ); + for ( j6 = sh[6]; j6 > 0; ) { + if ( j6 < bsize ) { + s6 = j6; + j6 = 0; + } else { + s6 = bsize; + j6 -= bsize; + } + dx7 = sx[7] - ( s6*sx[6] ); + ox6 = ox7 + ( j6*sx[6] ); + for ( j5 = sh[5]; j5 > 0; ) { + if ( j5 < bsize ) { + s5 = j5; + j5 = 0; + } else { + s5 = bsize; + j5 -= bsize; + } + dx6 = sx[6] - ( s5*sx[5] ); + ox5 = ox6 + ( j5*sx[5] ); + for ( j4 = sh[4]; j4 > 0; ) { + if ( j4 < bsize ) { + s4 = j4; + j4 = 0; + } else { + s4 = bsize; + j4 -= bsize; + } + dx5 = sx[5] - ( s4*sx[4] ); + ox4 = ox5 + ( j4*sx[4] ); + for ( j3 = sh[3]; j3 > 0; ) { + if ( j3 < bsize ) { + s3 = j3; + j3 = 0; + } else { + s3 = bsize; + j3 -= bsize; + } + dx4 = sx[4] - ( s3*sx[3] ); + ox3 = ox4 + ( j3*sx[3] ); + for ( j2 = sh[2]; j2 > 0; ) { + if ( j2 < bsize ) { + s2 = j2; + j2 = 0; + } else { + s2 = bsize; + j2 -= bsize; + } + dx3 = sx[3] - ( s2*sx[2] ); + ox2 = ox3 + ( j2*sx[2] ); + for ( j1 = sh[1]; j1 > 0; ) { + if ( j1 < bsize ) { + s1 = j1; + j1 = 0; + } else { + s1 = bsize; + j1 -= bsize; + } + dx2 = sx[2] - ( s1*sx[1] ); + ox1 = ox2 + ( j1*sx[1] ); + for ( j0 = sh[0]; j0 > 0; ) { + if ( j0 < bsize ) { + s0 = j0; + j0 = 0; + } else { + s0 = bsize; + j0 -= bsize; + } + // Compute the index offset for the first input ndarray element in the current block: + ix = ox1 + ( j0*sx[0] ); + + // Compute the loop offset increment: + dx1 = sx[1] - ( s0*sx[0] ); + + // Iterate over the ndarray dimensions... + for ( i8 = 0; i8 < s8; i8++ ) { + for ( i7 = 0; i7 < s7; i7++ ) { + for ( i6 = 0; i6 < s6; i6++ ) { + for ( i5 = 0; i5 < s5; i5++ ) { + for ( i4 = 0; i4 < s4; i4++ ) { + for ( i3 = 0; i3 < s3; i3++ ) { + for ( i2 = 0; i2 < s2; i2++ ) { + for ( i1 = 0; i1 < s1; i1++ ) { + for ( i0 = 0; i0 < s0; i0++ ) { + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + ix += dx0; + } + ix += dx1; + } + ix += dx2; + } + ix += dx3; + } + ix += dx4; + } + ix += dx5; + } + ix += dx6; + } + ix += dx7; + } + ix += dx8; + } + } + } + } + } + } + } + } + } + } + return acc; +} + + +// EXPORTS // + +module.exports = blockedaccumulate9d; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/index.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/index.js new file mode 100644 index 000000000000..30f424fe97a4 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/index.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Perform a reduction over elements in an input ndarray. +* +* @module @stdlib/ndarray/base/unary-accumulate +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var accumulateUnary = require( '@stdlib/ndarray/base/unary-accumulate' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulateUnary( [ x ], 0.0, add ); +* // returns 39.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/main.js new file mode 100644 index 000000000000..4fb3e17191a8 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/main.js @@ -0,0 +1,298 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var iterationOrder = require( '@stdlib/ndarray/base/iteration-order' ); +var minmaxViewBufferIndex = require( '@stdlib/ndarray/base/minmax-view-buffer-index' ); +var ndarray2object = require( '@stdlib/ndarray/base/ndarraylike2object' ); +var blockedaccessorunary2d = require( './2d_blocked_accessors.js' ); +var blockedaccessorunary3d = require( './3d_blocked_accessors.js' ); +var blockedaccessorunary4d = require( './4d_blocked_accessors.js' ); +var blockedaccessorunary5d = require( './5d_blocked_accessors.js' ); +var blockedaccessorunary6d = require( './6d_blocked_accessors.js' ); +var blockedaccessorunary7d = require( './7d_blocked_accessors.js' ); +var blockedaccessorunary8d = require( './8d_blocked_accessors.js' ); +var blockedaccessorunary9d = require( './9d_blocked_accessors.js' ); +var blockedaccessorunary10d = require( './10d_blocked_accessors.js' ); +var blockedunary2d = require( './2d_blocked.js' ); +var blockedunary3d = require( './3d_blocked.js' ); +var blockedunary4d = require( './4d_blocked.js' ); +var blockedunary5d = require( './5d_blocked.js' ); +var blockedunary6d = require( './6d_blocked.js' ); +var blockedunary7d = require( './7d_blocked.js' ); +var blockedunary8d = require( './8d_blocked.js' ); +var blockedunary9d = require( './9d_blocked.js' ); +var blockedunary10d = require( './10d_blocked.js' ); +var accessorunary0d = require( './0d_accessors.js' ); +var accessorunary1d = require( './1d_accessors.js' ); +var accessorunary2d = require( './2d_accessors.js' ); +var accessorunary3d = require( './3d_accessors.js' ); +var accessorunary4d = require( './4d_accessors.js' ); +var accessorunary5d = require( './5d_accessors.js' ); +var accessorunary6d = require( './6d_accessors.js' ); +var accessorunary7d = require( './7d_accessors.js' ); +var accessorunary8d = require( './8d_accessors.js' ); +var accessorunary9d = require( './9d_accessors.js' ); +var accessorunary10d = require( './10d_accessors.js' ); +var accessorunarynd = require( './nd_accessors.js' ); +var unary0d = require( './0d.js' ); +var unary1d = require( './1d.js' ); +var unary2d = require( './2d.js' ); +var unary3d = require( './3d.js' ); +var unary4d = require( './4d.js' ); +var unary5d = require( './5d.js' ); +var unary6d = require( './6d.js' ); +var unary7d = require( './7d.js' ); +var unary8d = require( './8d.js' ); +var unary9d = require( './9d.js' ); +var unary10d = require( './10d.js' ); +var unarynd = require( './nd.js' ); + + +// VARIABLES // + +var UNARY = [ + unary0d, + unary1d, + unary2d, + unary3d, + unary4d, + unary5d, + unary6d, + unary7d, + unary8d, + unary9d, + unary10d +]; +var ACCESSOR_UNARY = [ + accessorunary0d, + accessorunary1d, + accessorunary2d, + accessorunary3d, + accessorunary4d, + accessorunary5d, + accessorunary6d, + accessorunary7d, + accessorunary8d, + accessorunary9d, + accessorunary10d +]; +var BLOCKED_UNARY = [ + blockedunary2d, // 0 + blockedunary3d, + blockedunary4d, + blockedunary5d, + blockedunary6d, + blockedunary7d, + blockedunary8d, + blockedunary9d, + blockedunary10d // 8 +]; +var BLOCKED_ACCESSOR_UNARY = [ + blockedaccessorunary2d, // 0 + blockedaccessorunary3d, + blockedaccessorunary4d, + blockedaccessorunary5d, + blockedaccessorunary6d, + blockedaccessorunary7d, + blockedaccessorunary8d, + blockedaccessorunary9d, + blockedaccessorunary10d // 8 +]; +var MAX_DIMS = UNARY.length - 1; + + +// MAIN // + +/** +* Performs a reduction over elements in an input ndarray. +* +* ## Notes +* +* - Each provided ndarray should be an `object` with the following properties: +* +* - **dtype**: data type. +* - **data**: data buffer. +* - **shape**: dimensions. +* - **strides**: stride lengths. +* - **offset**: index offset. +* - **order**: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style). +* +* @param {ArrayLikeObject} arrays - array-like object containing one input array +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulateUnary( [ x ], 0.0, add ); +* // returns 39.0 +*/ +function accumulateUnary( arrays, initial, clbk ) { + var ndims; + var xmmv; + var shx; + var iox; + var len; + var sx; + var ox; + var ns; + var x; + var d; + var i; + + // Unpack the ndarray and standardize ndarray meta data: + x = ndarray2object( arrays[ 0 ] ); + shx = x.shape; + ndims = shx.length; + + // Determine whether we can avoid iteration altogether... + if ( ndims === 0 ) { + if ( x.accessorProtocol ) { + return ACCESSOR_UNARY[ ndims ]( x, initial, clbk ); + } + return UNARY[ ndims ]( x, initial, clbk ); + } + // Determine the number of elements and the number of singleton dimensions... + len = 1; // number of elements + ns = 0; // number of singleton dimensions + for ( i = 0; i < ndims; i++ ) { + d = shx[ i ]; + + // Note that, if one of the dimensions is `0`, the length will be `0`... + len *= d; + + // Check whether the current dimension is a singleton dimension... + if ( d === 1 ) { + ns += 1; + } + } + // Check whether we were provided an empty ndarray... + if ( len === 0 ) { + return; + } + // Determine whether the ndarray is one-dimensional and thus readily translates to a one-dimensional strided array... + if ( ndims === 1 ) { + if ( x.accessorProtocol ) { + return ACCESSOR_UNARY[ ndims ]( x, initial, clbk ); + } + return UNARY[ ndims ]( x, initial, clbk ); + } + sx = x.strides; + + // Determine whether the ndarray has only **one** non-singleton dimension (e.g., ndims=4, shape=[10,1,1,1]) so that we can treat an ndarray as being equivalent to a one-dimensional strided array... + if ( ns === ndims-1 ) { + // Get the index of the non-singleton dimension... + for ( i = 0; i < ndims; i++ ) { + if ( shx[ i ] !== 1 ) { + break; + } + } + x.shape = [ shx[i] ]; + x.strides = [ sx[i] ]; + if ( x.accessorProtocol ) { + return ACCESSOR_UNARY[ 1 ]( x, initial, clbk ); + } + return UNARY[ 1 ]( x, initial, clbk ); + } + iox = iterationOrder( sx ); // +/-1 + + // Determine whether we can avoid blocked iteration... + if ( iox !== 0 ) { + // Determine the minimum and maximum linear indices which are accessible by the array view: + xmmv = minmaxViewBufferIndex( shx, sx, x.offset ); + + // Determine whether we can ignore shape (and strides) and treat the ndarray as a linear one-dimensional strided array... + if ( len === ( xmmv[1]-xmmv[0]+1 ) ) { + // Note: the above is equivalent to @stdlib/ndarray/base/assert/is-contiguous, but in-lined so we can retain computed values... + if ( iox === 1 ) { + ox = xmmv[ 0 ]; + } else { + ox = xmmv[ 1 ]; + } + x.shape = [ len ]; + x.strides = [ iox ]; + x.offset = ox; + if ( x.accessorProtocol ) { + return ACCESSOR_UNARY[ 1 ]( x, initial, clbk ); + } + return UNARY[ 1 ]( x, initial, clbk ); + } + // The ndarray is non-contiguous, so we cannot directly use one-dimensional array functionality... + + // Determine whether we can use simple nested loops... + if ( ndims <= MAX_DIMS ) { + // So long as iteration always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... + if ( x.accessorProtocol ) { + return ACCESSOR_UNARY[ ndims ]( x, initial, clbk ); + } + return UNARY[ ndims ]( x, initial, clbk ); + } + // Fall-through to blocked iteration... + } + // At this point, we're either dealing with a non-contiguous n-dimensional array or a high dimensional n-dimensional array, so our only hope is that we can still perform blocked iteration... + + // Determine whether we can perform blocked iteration... + if ( ndims <= MAX_DIMS ) { + if ( x.accessorProtocol ) { + return BLOCKED_ACCESSOR_UNARY[ ndims-2 ]( x, initial, clbk ); + } + return BLOCKED_UNARY[ ndims-2 ]( x, initial, clbk ); + } + // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... + if ( x.accessorProtocol ) { + return accessorunarynd( x, initial, clbk ); + } + return unarynd( x, initial, clbk ); +} + + +// EXPORTS // + +module.exports = accumulateUnary; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/nd.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/nd.js new file mode 100644 index 000000000000..21a190826914 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/nd.js @@ -0,0 +1,124 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numel = require( '@stdlib/ndarray/base/numel' ); +var vind2bind = require( '@stdlib/ndarray/base/vind2bind' ); + + +// VARIABLES // + +var MODE = 'throw'; + + +// MAIN // + +/** +* Performs a reduction over elements in an n-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* function add( acc, x ) { +* return acc + x; +* } +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'float64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major' +* }; +* +* // Compute the sum: +* var v = accumulatend( x, 0.0, add ); +* // returns 18.0 +*/ +function accumulatend( x, initial, clbk ) { + var xbuf; + var ordx; + var len; + var acc; + var sh; + var sx; + var ox; + var ix; + var i; + + sh = x.shape; + + // Compute the total number of elements over which to iterate: + len = numel( sh ); + + // Cache a reference to the input ndarray data buffer: + xbuf = x.data; + + // Cache a reference to the stride array: + sx = x.strides; + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache the array order: + ordx = x.order; + + // Initialize the accumulator: + acc = initial; + + // Iterate over each element based on the linear **view** index, regardless as to how the data is stored in memory... + for ( i = 0; i < len; i++ ) { + ix = vind2bind( sh, sx, ox, ordx, i, MODE ); + acc = clbk( acc, xbuf[ ix ] ); // eslint-disable-line node/callback-return + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulatend; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/nd_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/nd_accessors.js new file mode 100644 index 000000000000..60fa24550649 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/lib/nd_accessors.js @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numel = require( '@stdlib/ndarray/base/numel' ); +var vind2bind = require( '@stdlib/ndarray/base/vind2bind' ); + + +// VARIABLES // + +var MODE = 'throw'; + + +// MAIN // + +/** +* Performs a reduction over elements in an n-dimensional input ndarray. +* +* @private +* @param {Object} x - object containing input ndarray meta data +* @param {string} x.dtype - data type +* @param {Collection} x.data - data buffer +* @param {NonNegativeIntegerArray} x.shape - dimensions +* @param {IntegerArray} x.strides - stride lengths +* @param {NonNegativeInteger} x.offset - index offset +* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style) +* @param {Array} x.accessors - data buffer accessors +* @param {*} initial - initial value +* @param {Callback} clbk - callback function +* @returns {*} result +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var realf = require( '@stdlib/complex/float32/real' ); +* var imagf = require( '@stdlib/complex/float32/imag' ); +* +* function add( acc, z ) { +* return new Complex64( realf(acc)+realf(z), imagf(acc)+imagf(z) ); +* } +* +* // Create a data buffer: +* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* +* // Define the shape of the input array: +* var shape = [ 2, 2 ]; +* +* // Define the array strides: +* var sx = [ 2, 1 ]; +* +* // Define the index offset: +* var ox = 0; +* +* // Define getters and setters: +* function getter( buf, idx ) { +* return buf.get( idx ); +* } +* +* function setter( buf, idx, value ) { +* buf.set( value, idx ); +* } +* +* // Create the input ndarray-like object: +* var x = { +* 'dtype': 'complex64', +* 'data': xbuf, +* 'shape': shape, +* 'strides': sx, +* 'offset': ox, +* 'order': 'row-major', +* 'accessors': [ getter, setter ] +* }; +* +* // Compute the sum: +* var v = accumulatend( x, new Complex64( 0.0, 0.0 ), add ); +* // returns +* +* var re = realf( v ); +* // returns 16.0 +* +* var im = imagf( v ); +* // returns 20.0 +*/ +function accumulatend( x, initial, clbk ) { + var xbuf; + var ordx; + var len; + var get; + var acc; + var sh; + var sx; + var ox; + var ix; + var i; + + sh = x.shape; + + // Compute the total number of elements over which to iterate: + len = numel( sh ); + + // Cache a reference to the input ndarray data buffer: + xbuf = x.data; + + // Cache a reference to the stride array: + sx = x.strides; + + // Cache the index of the first indexed element: + ox = x.offset; + + // Cache the array order: + ordx = x.order; + + // Cache a reference to the accessor: + get = x.accessors[ 0 ]; + + // Initialize the accumulator: + acc = initial; + + // Iterate over each element based on the linear **view** index, regardless as to how the data is stored in memory... + for ( i = 0; i < len; i++ ) { + ix = vind2bind( sh, sx, ox, ordx, i, MODE ); + acc = clbk( acc, get( xbuf, ix ) ); // eslint-disable-line node/callback-return + } + return acc; +} + + +// EXPORTS // + +module.exports = accumulatend; diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/manifest.json b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/manifest.json new file mode 100644 index 000000000000..ee035e0c6267 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/manifest.json @@ -0,0 +1,50 @@ +{ + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [ + "./src/dispatch.c", + "./src/internal/permute.c", + "./src/internal/range.c", + "./src/internal/sort2ins.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/complex/float32/ctor", + "@stdlib/complex/float64/ctor", + "@stdlib/ndarray/base/bytes-per-element", + "@stdlib/ndarray/base/iteration-order", + "@stdlib/ndarray/base/vind2bind", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/package.json b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/package.json new file mode 100644 index 000000000000..5c9341bb5773 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/ndarray/base/unary-accumulate", + "version": "0.0.0", + "description": "Perform a reduction over elements in a input ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "scripts": "./scripts", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "base", + "strided", + "array", + "ndarray", + "unary", + "reduce", + "reduction", + "accumulate", + "accumulation" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/docs.txt b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/docs.txt new file mode 100644 index 000000000000..241f23805686 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/docs.txt @@ -0,0 +1,107 @@ +#### stdlib_ndarray_accumulate_{{SIGNATURE}}( \*arrays\[], \*fcn ) + +Performs a reduction over elements in an input ndarray. + +```c +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +#include +#include +#include + +// Define the ndarray data types: +enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; + +// Create underlying byte arrays: +{{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_2D}} }; +{{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_VALUES_2D}} }; +{{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_2D}} }; + +uint8_t *xbuf = (uint8_t *)xvalues; +uint8_t *ibuf = (uint8_t *)ivalues; +uint8_t *obuf = (uint8_t *)ovalues; + +// Define the number of dimensions: +int64_t ndims = 2; + +// Define the array shapes: +int64_t xsh[] = { {{NDARRAY_SHAPE_2D}} }; +int64_t ish[] = { 0 }; +int64_t osh[] = { 0 }; + +// Define the strides: +int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_2D}} }; +int64_t si[] = { 0 }; +int64_t so[] = { 0 }; + +// Define the offsets: +int64_t ox = 0; +int64_t oi = 0; +int64_t oo = 0; + +// Define the array order: +enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + +// Specify the index mode: +enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + +// Specify the subscript index modes: +int8_t submodes[] = { imode }; +int64_t nsubmodes = 1; + +// Create an input ndarray: +struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, shape, sx, ox, order, imode, nsubmodes, submodes ); +if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); +} + +// Create a zero-dimensional initial value ndarray: +struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +if ( initial == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); +} + +// Create a zero-dimensional output ndarray: +struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +if ( out == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( EXIT_FAILURE ); +} + +// Create an array containing the ndarrays: +struct ndarray *arrays[] = { x, initial, out }; + +// Define a callback: +static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { + {{CALLBACK_BODY}} +} + +// Apply the callback: +int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}( arrays, (void *)fcn ); +if ( status != 0 ) { + fprintf( stderr, "Error during computation.\n" ); + exit( EXIT_FAILURE ); +} + +// ... + +// Free allocated memory: +stdlib_ndarray_free( x ); +stdlib_ndarray_free( initial ); +stdlib_ndarray_free( out ); +``` + +The function accepts the following arguments: + +- **arrays**: `[inout] struct ndarray**` array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray. +- **fcn**: `[in] void*` a `{{CALLBACK_RETURN_DTYPE}} (*f)({{CALLBACK_PARAM_1_DTYPE}}, {{CALLBACK_PARAM_2_DTYPE}})` function to apply provided as a `void` pointer. + +```c +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}( struct ndarray *arrays[], void *fcn ); +``` diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/header.txt b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/header.txt new file mode 100644 index 000000000000..dadc439ea0c8 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/header.txt @@ -0,0 +1,150 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) {{YEAR}} {{COPYRIGHT}}. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* +* The following is auto-generated. Do not manually edit. See scripts/loops.js. +*/ + +#ifndef STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_{{INCLUDE_GUARD}}_H +#define STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_{{INCLUDE_GUARD}}_H + +#include "stdlib/ndarray/ctor.h" +#include + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Performs a reduction over elements in an input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a zero-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_0d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a one-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_1d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a two-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_2d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a two-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_2d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a three-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_3d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a three-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_3d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a four-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_4d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a four-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_4d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a five-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_5d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a five-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_5d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a six-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_6d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a six-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_6d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_7d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_7d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in an eight-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_8d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in an eight-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_8d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_9d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_9d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_10d( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_10d_blocked( struct ndarray *arrays[], void *fcn ); + +/** +* Performs a reduction over elements in an n-dimensional input ndarray. +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_nd( struct ndarray *arrays[], void *fcn ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_NDARRAY_BASE_UNARY_ACCUMULATE_{{INCLUDE_GUARD}}_H diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/source.txt b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/source.txt new file mode 100644 index 000000000000..66e1d99f1fc2 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/scripts/templates/source.txt @@ -0,0 +1,2569 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) {{YEAR}} {{COPYRIGHT}}. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* +* The following is auto-generated. Do not manually edit. See scripts/loops.js. +*/ + +#include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +#include "stdlib/ndarray/base/unary-accumulate/typedefs.h" +#include "stdlib/ndarray/base/unary-accumulate/macros.h" +#include "stdlib/ndarray/base/unary-accumulate/dispatch_object.h" +#include "stdlib/ndarray/base/unary-accumulate/dispatch.h" +#include "stdlib/ndarray/ctor.h"{{INCLUDES}} +#include + +/** +* Performs a reduction over elements in a zero-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_0D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_0D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_0D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 0; +* +* // Define the array shapes: +* int64_t xsh[] = { 0 }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { 0 }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_0d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_0d( struct ndarray *arrays[], void *fcn ) { + {{INPUT_NDARRAY_1_CTYPE}} v1; + {{OUTPUT_NDARRAY_CTYPE}} v2; + int8_t status = stdlib_ndarray_iget_{{INPUT_NDARRAY_1_DTYPE_LOWER}}( arrays[ 0 ], 0, &v1 ); + if ( status != 0 ) { + return -1; + } + status = stdlib_ndarray_iget_{{OUTPUT_NDARRAY_DTYPE_LOWER}}( arrays[ 1 ], 0, &v2 ); + if ( status != 0 ) { + return -1; + } + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + status = stdlib_ndarray_iset_{{OUTPUT_NDARRAY_DTYPE_LOWER}}( arrays[ 2 ], 0, {{CALLBACK_EXPRESSION_0D}} ); + if ( status != 0 ) { + return -1; + } + return 0; +} + +/** +* Performs a reduction over elements in a one-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_1D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_1D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_1D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 1; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_1D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_BYTES_PER_ELEMENT}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_1d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_1d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_ACCUMULATE_UNARY_1D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a two-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_2D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_2D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_2D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 2; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_2D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_2D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_2d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_2d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a two-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_2D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_2D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_2D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 2; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_2D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_2D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_2d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_2d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_2D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a three-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_3D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_3D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_3D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 3; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_3D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_3D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_3d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_3d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a three-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_3D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_3D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_3D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 3; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_3D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_3D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_3d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_3d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_3D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a four-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_4D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_4D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_4D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 4; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_4D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_4D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_4d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_4d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_4D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a four-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_4D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_4D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_4D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 4; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_4D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_4D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_4d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_4d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_4D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a five-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_5D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_5D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_5D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 5; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_5D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_5D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_5d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_5d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_5D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a five-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_5D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_5D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_5D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 5; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_5D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_5D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_5d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_5d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_5D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a six-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_6D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_6D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_6D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 6; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_6D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_6D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_6d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_6d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_6D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a six-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_6D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_6D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_6D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 6; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_6D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_6D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_6d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_6d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_6D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_7D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_7D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_7D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 7; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_7D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_7D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_7d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_7d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_7D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a seven-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_7D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_7D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_7D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 7; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_7D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_7D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_7d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_7d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_7D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Applies a unary callback to an eight-dimensional input ndarray ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_8D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_8D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_8D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 8; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_8D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_8D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_8d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_8d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_8D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Applies a unary callback to an eight-dimensional input ndarray ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_8D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_8D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_8D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 8; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_8D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_8D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_8d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_8d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_8D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_9D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_9D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_9D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 9; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_9D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_9D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_9d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_9d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_9D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a nine-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_9D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_9D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_9D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 9; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_9D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_9D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_9d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_9d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_9D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_10D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_10D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_10D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 10; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_10D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_10D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_10d( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_10d( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_10D_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Performs a reduction over elements in a ten-dimensional input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_10D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_10D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_10D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 10; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_10D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_10D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_10d_blocked( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_10d_blocked( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_10D_BLOCKED_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +/** +* Applies a unary callback to an n-dimensional input ndarray ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_3D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_3D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_3D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 3; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_3D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_3D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}_nd( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}_nd( struct ndarray *arrays[], void *fcn ) { + typedef {{CALLBACK_RETURN_DTYPE}} func_type( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ); + func_type *f = (func_type *)fcn; + STDLIB_NDARRAY_UNARY_ACCUMULATE_ND_LOOP_{{LOOP_MACRO}}( {{LOOP_MACRO_ARGUMENTS}} ) + return 0; +} + +// Define a list of unary ndarray functions: +static ndarrayUnaryFcn functions[] = { + stdlib_ndarray_accumulate_{{SIGNATURE}}_0d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_1d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_2d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_3d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_4d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_5d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_6d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_7d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_8d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_9d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_10d, + stdlib_ndarray_accumulate_{{SIGNATURE}}_nd +}; + +// Define a list of unary ndarray functions implementing loop blocking... +static ndarrayUnaryFcn blocked_functions[] = { + stdlib_ndarray_accumulate_{{SIGNATURE}}_2d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_3d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_4d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_5d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_6d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_7d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_8d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_9d_blocked, + stdlib_ndarray_accumulate_{{SIGNATURE}}_10d_blocked +}; + +// Create a function dispatch object: +static const struct ndarrayUnaryDispatchObject obj = { + // Array containing ndarray functions: + functions, + + // Number of ndarray functions: + 12, + + // Array containing ndarray functions using loop blocking: + blocked_functions, + + // Number of ndarray functions using loop blocking: + 9 +}; + +/** +* Performs a reduction over elements in an input ndarray. +* +* ## Notes +* +* - If successful, the functions returns `0`; otherwise, the function returns an error code. +* +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/{{SIGNATURE}}.h" +* #include "stdlib/ndarray/dtypes.h" +* #include "stdlib/ndarray/index_modes.h" +* #include "stdlib/ndarray/orders.h" +* #include "stdlib/ndarray/ctor.h"{{EXAMPLE_INCLUDES}} +* #include +* #include +* #include +* +* // Define the ndarray data types: +* enum STDLIB_NDARRAY_DTYPE xdtype = STDLIB_NDARRAY_{{INPUT_NDARRAY_1_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE idtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* enum STDLIB_NDARRAY_DTYPE odtype = STDLIB_NDARRAY_{{OUTPUT_NDARRAY_DTYPE_UPPER}}; +* +* // Create underlying byte arrays: +* {{INPUT_NDARRAY_1_CTYPE}} xvalues[] = { {{INPUT_NDARRAY_1_VALUES_2D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ivalues[] = { {{INITIAL_NDARRAY_BYTES_2D}} }; +* {{OUTPUT_NDARRAY_CTYPE}} ovalues[] = { {{OUTPUT_NDARRAY_VALUES_2D}} }; +* +* uint8_t *xbuf = (uint8_t *)xvalues; +* uint8_t *ibuf = (uint8_t *)ivalues; +* uint8_t *obuf = (uint8_t *)ovalues; +* +* // Define the number of dimensions: +* int64_t ndims = 2; +* +* // Define the array shapes: +* int64_t xsh[] = { {{NDARRAY_SHAPE_2D}} }; +* int64_t ish[] = { 0 }; +* int64_t osh[] = { 0 }; +* +* // Define the strides: +* int64_t sx[] = { {{INPUT_NDARRAY_1_STRIDES_2D}} }; +* int64_t si[] = { 0 }; +* int64_t so[] = { 0 }; +* +* // Define the offsets: +* int64_t ox = 0; +* int64_t oi = 0; +* int64_t oo = 0; +* +* // Define the array order: +* enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; +* +* // Specify the index mode: +* enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; +* +* // Specify the subscript index modes: +* int8_t submodes[] = { imode }; +* int64_t nsubmodes = 1; +* +* // Create an input ndarray: +* struct ndarray *x = stdlib_ndarray_allocate( xdtype, xbuf, ndims, xsh, sx, ox, order, imode, nsubmodes, submodes ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional initial value ndarray: +* struct ndarray *initial = stdlib_ndarray_allocate( idtype, ibuf, 0, ish, si, oi, order, imode, nsubmodes, submodes ); +* if ( initial == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create a zero-dimensional output ndarray: +* struct ndarray *out = stdlib_ndarray_allocate( odtype, obuf, 0, osh, so, oo, order, imode, nsubmodes, submodes ); +* if ( out == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // Create an array containing the ndarrays: +* struct ndarray *arrays[] = { x, initial, out }; +* +* // Define a callback: +* static {{CALLBACK_RETURN_DTYPE}} fcn( const {{CALLBACK_PARAM_1_DTYPE}} acc, const {{CALLBACK_PARAM_2_DTYPE}} x ) { +* {{CALLBACK_BODY}} +* } +* +* // Apply the callback: +* int8_t status = stdlib_ndarray_accumulate_{{SIGNATURE}}( arrays, (void *)fcn ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Free allocated memory: +* stdlib_ndarray_free( x ); +* stdlib_ndarray_free( initial ); +* stdlib_ndarray_free( out ); +*/ +int8_t stdlib_ndarray_accumulate_{{SIGNATURE}}( struct ndarray *arrays[], void *fcn ) { + return stdlib_ndarray_unary_accumulate_dispatch( &obj, arrays, fcn ); +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/README.md b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/README.md new file mode 100644 index 000000000000..8676737268ac --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/README.md @@ -0,0 +1,28 @@ + + +# Unary + +> ndarray functions for accumulation callbacks. + +## Notes + +- Each file contains a set of related ndarray functions. The file name matches the ndarray function name suffix for input and output ndarray dtypes. +- The implemented functions which perform conversions are **not** exhaustive and that is intentional. Namely, functions which would perform "unsafe" callback argument and return value conversions are generally not included (e.g., converting `double` to `int32`). If users want to perform "unsafe" conversions, that should be a conscious decision. All the machinery (e.g., macros, typedefs, etc) is available for implementing ndarray functions which perform "unsafe" conversions, but we should not make this overly easy or be proactive in promoting "unsafe" conversion use. diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c new file mode 100644 index 000000000000..e0ec04c456d9 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/dispatch.c @@ -0,0 +1,344 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ndarray/base/unary-accumulate/dispatch_object.h" +#include "stdlib/ndarray/base/unary-accumulate/typedefs.h" +#include "stdlib/ndarray/base/iteration_order.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include "stdlib/ndarray/ctor.h" +#include +#include + +/** +* Performs a reduction over elements in n-dimensional input ndarray having `ndims-1` singleton dimensions. +* +* ## Notes +* +* - If able to successfully perform a reduction, the function returns `0`; otherwise, the function returns an error code. +* +* @param f ndarray function +* @param x1 input ndarray +* @param x2 initial value ndarray +* @param x3 output ndarray +* @param i index of the non-singleton dimension +* @param fcn callback +* @return status code +*/ +static int8_t stdlib_ndarray_unary_accumulate_1d_squeeze( const ndarrayUnaryAccumulateFcn f, struct ndarray *x1, struct ndarray *x2, struct ndarray *x3, const int64_t i, void *fcn ) { + int64_t sh[] = { stdlib_ndarray_shape( x1 )[ i ] }; + + // Shallow copy and reshape the array... + int64_t sx1[] = { stdlib_ndarray_strides( x1 )[ i ] }; + struct ndarray *x1c = stdlib_ndarray_allocate( + stdlib_ndarray_dtype( x1 ), + stdlib_ndarray_data( x1 ), + 1, + sh, + sx1, + stdlib_ndarray_offset( x1 ), + stdlib_ndarray_order( x1 ), + stdlib_ndarray_index_mode( x1 ), + stdlib_ndarray_nsubmodes( x1 ), + stdlib_ndarray_submodes( x1 ) + ); + if ( x1c == NULL ) { + return -1; + } + // Perform the reduction: + struct ndarray *arrays[] = { x1c, x2, x3 }; + int8_t status = f( arrays, fcn ); + + // Free allocated memory: + stdlib_ndarray_free( x1c ); + + return status; +} + +/** +* Performs a reduction over elements in a flattened n-dimensional input ndarray. +* +* ## Notes +* +* - If able to successfully perform a reduction, the function returns `0`; otherwise, the function returns an error code. +* +* @param f ndarray function +* @param N number of elements +* @param x1 input ndarray +* @param s1 input ndarray stride length +* @param x2 initial value ndarray +* @param x3 output ndarray +* @param fcn callback +* @return status code +*/ +static int8_t stdlib_ndarray_unary_accumulate_1d_flatten( const ndarrayUnaryAccumulateFcn f, const int64_t N, struct ndarray *x1, const int64_t s1, struct ndarray *x2, struct ndarray *x3, void *fcn ) { + // Define the (flattened) strided array shape: + int64_t sh[] = { N }; + + // Shallow copy and reshape the array... + int64_t sx1[] = { s1 }; + struct ndarray *x1c = stdlib_ndarray_allocate( + stdlib_ndarray_dtype( x1 ), + stdlib_ndarray_data( x1 ), + 1, + sh, + sx1, + stdlib_ndarray_offset( x1 ), + stdlib_ndarray_order( x1 ), + stdlib_ndarray_index_mode( x1 ), + stdlib_ndarray_nsubmodes( x1 ), + stdlib_ndarray_submodes( x1 ) + ); + if ( x1c == NULL ) { + return -1; + } + // Perform the reduction: + struct ndarray *arrays[] = { x1c, x2, x3 }; + int8_t status = f( arrays, fcn ); + + // Free allocated memory: + stdlib_ndarray_free( x1c ); + + return status; +} + +/** +* Dispatches to an ndarray function according to the dimensionality of provided ndarray arguments. +* +* ## Notes +* +* - If able to successfully dispatch, the function returns `0`; otherwise, the function returns an error code. +* +* @param obj object comprised of dispatch tables containing ndarray functions +* @param arrays array whose first element is a pointer to an input ndarray, second element is a pointer to a zero-dimensional initial value ndarray, and last element is a pointer to a zero-dimensional output ndarray +* @param fcn callback +* @return status code +* +* @example +* #include "stdlib/ndarray/base/unary-accumulate/dispatch.h" +* #include "stdlib/ndarray/base/unary-accumulate/dispatch_object.h" +* #include "stdlib/ndarray/base/unary-accumulate/typedefs.h" +* #include "stdlib/ndarray/base/unary-accumulate/bb_b.h" +* #include "stdlib/ndarray/ctor.h" +* #include +* #include +* #include +* +* // Define a list of ndarray functions: +* ndarrayUnaryAccumulateFcn functions[] = { +* stdlib_ndarray_accumulate_bb_b_0d, +* stdlib_ndarray_accumulate_bb_b_1d, +* stdlib_ndarray_accumulate_bb_b_2d, +* stdlib_ndarray_accumulate_bb_b_3d, +* stdlib_ndarray_accumulate_bb_b_4d, +* stdlib_ndarray_accumulate_bb_b_5d, +* stdlib_ndarray_accumulate_bb_b_6d, +* stdlib_ndarray_accumulate_bb_b_7d, +* stdlib_ndarray_accumulate_bb_b_8d, +* stdlib_ndarray_accumulate_bb_b_9d, +* stdlib_ndarray_accumulate_bb_b_10d +* stdlib_ndarray_accumulate_bb_b_nd +* }; +* +* // Define a list of ndarray functions using loop blocking: +* ndarrayUnaryAccumulateFcn blocked_functions[] = { +* stdlib_ndarray_accumulate_bb_b_2d_blocked, +* stdlib_ndarray_accumulate_bb_b_3d_blocked, +* stdlib_ndarray_accumulate_bb_b_4d_blocked, +* stdlib_ndarray_accumulate_bb_b_5d_blocked, +* stdlib_ndarray_accumulate_bb_b_6d_blocked, +* stdlib_ndarray_accumulate_bb_b_7d_blocked, +* stdlib_ndarray_accumulate_bb_b_8d_blocked, +* stdlib_ndarray_accumulate_bb_b_9d_blocked, +* stdlib_ndarray_accumulate_bb_b_10d_blocked +* }; +* +* // Create a function dispatch object: +* struct ndarrayUnaryAccumulateDispatchObject obj = { +* // Array containing ndarray functions: +* functions, +* +* // Number of ndarray functions: +* 12, +* +* // Array containing ndarray functions using loop blocking: +* blocked_functions, +* +* // Number of ndarray functions using loop blocking: +* 9 +* } +* +* // Define a function which performs dispatch: +* int8_t stdlib_ndarray_accumulate_bb_b( struct ndarray *arrays[], void *fcn ) { +* return stdlib_ndarray_unary_accumulate_dispatch( &obj, arrays, fcn ); +* } +* +* // ... +* +* // Create ndarrays... +* struct ndarray *x = stdlib_ndarray_allocate( ... ); +* if ( x == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* struct ndarray *initial = stdlib_ndarray_allocate( ... ); +* if ( y == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* struct ndarray *out = stdlib_ndarray_allocate( ... ); +* if ( y == NULL ) { +* fprintf( stderr, "Error allocating memory.\n" ); +* exit( EXIT_FAILURE ); +* } +* +* // ... +* +* // Define a callback: +* uint8_t add( const uint8_t acc, const uint8_t x ) { +* return acc + x; +* } +* +* // Apply the callback: +* struct ndarray *arrays[] = { x, initial, out }; +* int8_t status = stdlib_ndarray_accumulate_bb_b( arrays, (void *)add ); +* if ( status != 0 ) { +* fprintf( stderr, "Error during computation.\n" ); +* exit( EXIT_FAILURE ); +* } +*/ +int8_t stdlib_ndarray_unary_accumulate_dispatch( const struct ndarrayUnaryAccumulateDispatchObject *obj, struct ndarray *arrays[], void *fcn ) { + const int64_t *sh1; + struct ndarray *x1; + struct ndarray *x2; + struct ndarray *x3; + int8_t status; + int64_t ndims; + int64_t mab1; + int64_t mib1; + int64_t *s1; + int64_t len; + int64_t bp1; + int8_t io1; + int64_t ns; + int64_t s; + int64_t d; + int64_t i; + + // Unpack the arrays: + x1 = arrays[ 0 ]; + x2 = arrays[ 1 ]; + x3 = arrays[ 3 ]; + + ndims = stdlib_ndarray_ndims( x1 ); + + // Determine whether we can avoid iteration altogether... + if ( ndims == 0 ) { + obj->functions[ 0 ]( arrays, fcn ); + return 0; + } + sh1 = stdlib_ndarray_shape( x1 ); + + // Determine the number of elements and the number of singleton dimensions... + len = 1; // number of elements + ns = 0; // number of singleton dimensions + for ( i = 0; i < ndims; i++ ) { + d = sh1[ i ]; + + // Note that, if one of the dimensions is `0`, the length will be `0`... + len *= d; + + // Check whether the current dimension is a singleton dimension... + if ( d == 1 ) { + ns += 1; + } + } + // Check whether we were provided an empty ndarray... + if ( len == 0 ) { + return 0; + } + // Determine whether the ndarray is one-dimensional and thus readily translates to a one-dimensional strided array... + if ( ndims == 1 ) { + obj->functions[ 1 ]( arrays, fcn ); + return 0; + } + // Determine whether the ndarray has only **one** non-singleton dimension (e.g., ndims=4, shape=[10,1,1,1]) so that we can treat an ndarray as being equivalent to a one-dimensional strided array... + if ( ns == ndims-1 ) { + // Get the index of the non-singleton dimension... + for ( i = 0; i < ndims; i++ ) { + if ( sh1[ i ] != 1 ) { + break; + } + } + // Remove the singleton dimensions and apply the callback function... + status = stdlib_ndarray_unary_accumulate_1d_squeeze( obj->functions[ 1 ], x1, x2, x3, i, fcn ); + if ( status == 0 ) { + return 0; + } + // If we failed, this is probably due to failed memory allocation, so fall through and try again... + } + s1 = stdlib_ndarray_strides( x1 ); + io1 = stdlib_ndarray_iteration_order( ndims, s1 ); // +/-1 + + // Determine whether we can avoid blocked iteration... + if ( io1 != 0 ) { + // Determine the minimum and maximum linear byte indices which are accessible by the array view: + mib1 = stdlib_ndarray_offset( x1 ); // byte offset + mab1 = mib1; + for ( i = 0; i < ndims; i++ ) { + s = s1[ i ]; // units: bytes + if ( s > 0 ) { + mab1 += s * ( sh1[i]-1 ); + } else if ( s < 0 ) { + mib1 += s * ( sh1[i]-1 ); // decrements + } + } + bp1 = stdlib_ndarray_bytes_per_element( stdlib_ndarray_dtype( x1 ) ); + + // Determine whether we can ignore shape (and strides) and treat the ndarray as a linear one-dimensional strided array... + if ( ( len*bp1 ) == ( mab1-mib1+bp1 ) ) { + // Note: the above is equivalent to @stdlib/ndarray/base/assert/is-contiguous, but in-lined so we can retain computed values... + status = stdlib_ndarray_unary_accumulate_1d_flatten( obj->functions[ 1 ], len, x1, io1*bp1, x2, x3, fcn ); + if ( status == 0 ) { + return 0; + } + // If we failed, this is probably due to failed memory allocation, so fall through and try again... + } + // The ndarray is non-contiguous, so we cannot directly use one-dimensional array functionality... + + // Determine whether we can use simple nested loops... + if ( ndims < (obj->nfunctions) ) { + // So long as iteration always moves in the same direction (i.e., no mixed sign strides), we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... + obj->functions[ ndims ]( arrays, fcn ); + return 0; + } + // Fall-through to blocked iteration... + } + // At this point, we're either dealing with a non-contiguous n-dimensional array or a high dimensional n-dimensional array, so our only hope is that we can still perform blocked iteration... + + // Determine whether we can perform blocked iteration... + if ( ndims <= (obj->nblockedfunctions)+1 ) { + obj->blocked_functions[ ndims-2 ]( arrays, fcn ); + return 0; + } + // Fall-through to linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... + obj->functions[ (obj->nfunctions)-1 ]( arrays, fcn ); + + return 0; +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/permute.c b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/permute.c new file mode 100644 index 000000000000..885681278bda --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/permute.c @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ndarray/base/unary-accumulate/internal/permute.h" +#include + +/** +* Permutes an input array according to a provided index array. +* +* @param n number of elements to permute +* @param arr input array +* @param idx permutation indices +* @param out output array +*/ +void stdlib_ndarray_base_unary_accumulate_internal_permute( const int64_t n, const int64_t *arr, const int64_t *idx, int64_t *out ) { + int64_t i; + for ( i = 0; i < n; i++ ) { + out[ i ] = arr[ idx[i] ]; + } +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/range.c b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/range.c new file mode 100644 index 000000000000..74a74cdedcb1 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/range.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ndarray/base/unary-accumulate/internal/range.h" +#include + +/** +* Writes `n` evenly spaced values from `0` to `n-1` to an output array. +* +* @param n number of values to write +* @param out output array +*/ +void stdlib_ndarray_base_unary_accumulate_internal_range( const int64_t n, int64_t *out ) { + int64_t i; + for ( i = 0; i < n; i++ ) { + out[ i ] = i; + } +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/sort2ins.c b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/sort2ins.c new file mode 100644 index 000000000000..ab01c8d2d7bf --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/src/internal/sort2ins.c @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ndarray/base/unary-accumulate/internal/sort2ins.h" +#include + +/** +* Simultaneously sorts two arrays based on the sort order of the first array using insertion sort. +* +* ## Notes +* +* - The first array is sorted in increasing order according to absolute value. +* - The algorithm has space complexity `O(1)` and worst case time complexity `O(N^2)`. +* - The algorithm is efficient for small arrays (typically `N <= 20``) and is particularly efficient for sorting arrays which are already substantially sorted. +* - The algorithm is **stable**, meaning that the algorithm does **not** change the order of array elements which are equal or equivalent. +* - The input arrays are sorted in-place (i.e., the input arrays are mutated). +* +* @param n number of elements +* @param x first array +* @param y second array +*/ +void stdlib_ndarray_base_unary_accumulate_internal_sort2ins( const int64_t n, int64_t *x, int64_t *y ) { + int64_t avx; + int64_t aux; + int64_t ix; + int64_t iy; + int64_t jx; + int64_t jy; + int64_t vx; + int64_t vy; + int64_t ux; + int64_t i; + + ix = 1; + iy = 1; + + // Sort in increasing order... + for ( i = 1; i < n; i++ ) { + vx = x[ ix ]; + avx = ( vx < 0 ) ? -vx : vx; + + vy = y[ iy ]; + + jx = ix - 1; + jy = iy - 1; + + // Shift all larger values to the left of the current element to the right... + while ( jx >= 0 ) { + ux = x[ jx ]; + aux = ( ux < 0 ) ? -ux : ux; + if ( aux <= avx ) { + break; + } + x[ jx+1 ] = ux; + y[ jy+1 ] = y[ jy ]; + jx -= 1; + jy -= 1; + } + x[ jx+1 ] = vx; + y[ jy+1 ] = vy; + ix += 1; + iy += 1; + } +} diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/test/test.js b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/test/test.js new file mode 100644 index 000000000000..3fea05a50627 --- /dev/null +++ b/lib/node_modules/@stdlib/ndarray/base/unary-accumulate/test/test.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var accumulateUnary = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof accumulateUnary, 'function', 'main export is a function' ); + t.end(); +}); + +// FIXME: add tests diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-by/lib/9d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary-by/lib/9d_blocked_accessors.js index 906f9a8d2448..6e20391d9559 100644 --- a/lib/node_modules/@stdlib/ndarray/base/unary-by/lib/9d_blocked_accessors.js +++ b/lib/node_modules/@stdlib/ndarray/base/unary-by/lib/9d_blocked_accessors.js @@ -47,7 +47,7 @@ var blockSize = require( '@stdlib/ndarray/base/unary-tiling-block-size' ); * @param {IntegerArray} y.strides - stride lengths * @param {NonNegativeInteger} y.offset - index offset * @param {string} y.order - specifies whether `y` is row-major (C-style) or column-major (Fortran-style) -* @param {Array} x.accessors - data buffer accessors +* @param {Array} y.accessors - data buffer accessors * @param {Function} fcn - unary function to apply to callback return values * @param {Callback} clbk - callback * @param {*} [thisArg] - callback execution context diff --git a/lib/node_modules/@stdlib/ndarray/base/unary/lib/9d_blocked_accessors.js b/lib/node_modules/@stdlib/ndarray/base/unary/lib/9d_blocked_accessors.js index 11f002d58696..1e40a9019a59 100644 --- a/lib/node_modules/@stdlib/ndarray/base/unary/lib/9d_blocked_accessors.js +++ b/lib/node_modules/@stdlib/ndarray/base/unary/lib/9d_blocked_accessors.js @@ -47,7 +47,7 @@ var blockSize = require( '@stdlib/ndarray/base/unary-tiling-block-size' ); * @param {IntegerArray} y.strides - stride lengths * @param {NonNegativeInteger} y.offset - index offset * @param {string} y.order - specifies whether `y` is row-major (C-style) or column-major (Fortran-style) -* @param {Array} x.accessors - data buffer accessors +* @param {Array} y.accessors - data buffer accessors * @param {Callback} fcn - unary callback * * @example diff --git a/lib/node_modules/@stdlib/ndarray/base/unary/src/dispatch.c b/lib/node_modules/@stdlib/ndarray/base/unary/src/dispatch.c index ffc76d2a5c05..2b2a601669f3 100644 --- a/lib/node_modules/@stdlib/ndarray/base/unary/src/dispatch.c +++ b/lib/node_modules/@stdlib/ndarray/base/unary/src/dispatch.c @@ -107,7 +107,7 @@ static int8_t stdlib_ndarray_unary_1d_flatten( const ndarrayUnaryFcn f, const in int64_t sh[] = { N }; // Shallow copy and reshape the arrays... - int64_t sx1[] = { s2 }; + int64_t sx1[] = { s1 }; struct ndarray *x1c = stdlib_ndarray_allocate( stdlib_ndarray_dtype( x1 ), stdlib_ndarray_data( x1 ), @@ -253,6 +253,8 @@ static int8_t stdlib_ndarray_unary_1d_flatten( const ndarrayUnaryFcn f, const in * } */ int8_t stdlib_ndarray_unary_dispatch( const struct ndarrayUnaryDispatchObject *obj, struct ndarray *arrays[], void *fcn ) { + const int64_t *sh1; + const int64_t *sh2; struct ndarray *x1; struct ndarray *x2; int8_t status; @@ -261,8 +263,6 @@ int8_t stdlib_ndarray_unary_dispatch( const struct ndarrayUnaryDispatchObject *o int64_t mab2; int64_t mib1; int64_t mib2; - int64_t *sh1; - int64_t *sh2; int64_t *s1; int64_t *s2; int64_t len; diff --git a/lib/node_modules/@stdlib/ndarray/filter/README.md b/lib/node_modules/@stdlib/ndarray/filter/README.md index a70f162ce634..f107e329148a 100644 --- a/lib/node_modules/@stdlib/ndarray/filter/README.md +++ b/lib/node_modules/@stdlib/ndarray/filter/README.md @@ -204,6 +204,15 @@ console.log( ndarray2array( y ) );
+* * * + +## See Also + +- [`@stdlib/ndarray/filter-map`][@stdlib/ndarray/filter-map]: filter and map elements in an input ndarray to elements in a new output ndarray according to a callback function. +- [`@stdlib/ndarray/map`][@stdlib/ndarray/map]: apply a callback to elements in an input ndarray and assign results to elements in a new output ndarray. +- [`@stdlib/ndarray/reject`][@stdlib/ndarray/reject]: return a shallow copy of an ndarray containing only those elements which fail a test implemented by a predicate function. +- [`@stdlib/ndarray/slice`][@stdlib/ndarray/slice]: return a read-only view of an input ndarray. +
@@ -218,6 +227,14 @@ console.log( ndarray2array( y ) ); +[@stdlib/ndarray/filter-map]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/filter-map + +[@stdlib/ndarray/map]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/map + +[@stdlib/ndarray/reject]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/reject + +[@stdlib/ndarray/slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/slice + diff --git a/lib/node_modules/@stdlib/ndarray/index/README.md b/lib/node_modules/@stdlib/ndarray/index/README.md index 42ee4f39ad1c..dc2617679c60 100644 --- a/lib/node_modules/@stdlib/ndarray/index/README.md +++ b/lib/node_modules/@stdlib/ndarray/index/README.md @@ -474,7 +474,7 @@ var o = idx.toJSON(); } ``` - will leak memory as `idx` is only consumed within an `if` block which never evaluates. In such scenarios, one should either refactor to avoid inadvertently holding onto memory or explicitly free the `ndindex`. + will leak memory as `idx` is only consumed within an `if` block which never evaluates. In such scenarios, one should either refactor to avoid inadvertently holding onto memory or explicitly free the `ndindex`. ```javascript var array = require( '@stdlib/ndarray/array' ); @@ -574,6 +574,16 @@ console.log( 'Type: %s. Data type: %s.', o.type, o.dtype );
+* * * + +## See Also + +- [`@stdlib/ndarray/array`][@stdlib/ndarray/array]: multidimensional arrays. +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +- [`@stdlib/ndarray/fancy`][@stdlib/ndarray/fancy]: fancy multidimensional array constructor. +- [`@stdlib/ndarray/slice`][@stdlib/ndarray/slice]: return a read-only view of an input ndarray. +- [`@stdlib/ndarray/to-fancy`][@stdlib/ndarray/to-fancy]: convert an ndarray to an object supporting fancy indexing. +
@@ -594,6 +604,16 @@ console.log( 'Type: %s. Data type: %s.', o.type, o.dtype ); [@stdlib/ndarray/to-fancy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/to-fancy + + +[@stdlib/ndarray/array]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/array + +[@stdlib/ndarray/fancy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/fancy + +[@stdlib/ndarray/slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/slice + + + diff --git a/lib/node_modules/@stdlib/ndarray/iter/subarrays/README.md b/lib/node_modules/@stdlib/ndarray/iter/subarrays/README.md index c93a63e6e6e4..64944d4f38af 100644 --- a/lib/node_modules/@stdlib/ndarray/iter/subarrays/README.md +++ b/lib/node_modules/@stdlib/ndarray/iter/subarrays/README.md @@ -170,6 +170,16 @@ while ( true ) {
+* * * + +## See Also + +- [`@stdlib/ndarray/iter/columns`][@stdlib/ndarray/iter/columns]: create an iterator which iterates over each column in a matrix (or stack of matrices). +- [`@stdlib/ndarray/iter/matrices`][@stdlib/ndarray/iter/matrices]: create an iterator which iterates over each matrix in a stack of matrices. +- [`@stdlib/ndarray/iter/rows`][@stdlib/ndarray/iter/rows]: create an iterator which iterates over each row in a matrix (or stack of matrices). +- [`@stdlib/ndarray/iter/stacks`][@stdlib/ndarray/iter/stacks]: create an iterator which iterates over each subarray in a stack of subarrays according to a list of specified stack dimensions. +- [`@stdlib/ndarray/slice`][@stdlib/ndarray/slice]: return a read-only view of an input ndarray. +
@@ -184,6 +194,18 @@ while ( true ) { [@stdlib/ndarray/slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/slice + + +[@stdlib/ndarray/iter/columns]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/iter/columns + +[@stdlib/ndarray/iter/matrices]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/iter/matrices + +[@stdlib/ndarray/iter/rows]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/iter/rows + +[@stdlib/ndarray/iter/stacks]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/iter/stacks + + + diff --git a/lib/node_modules/@stdlib/ndarray/to-fancy/README.md b/lib/node_modules/@stdlib/ndarray/to-fancy/README.md index aa55e17be1c8..b8f781fded91 100644 --- a/lib/node_modules/@stdlib/ndarray/to-fancy/README.md +++ b/lib/node_modules/@stdlib/ndarray/to-fancy/README.md @@ -307,6 +307,15 @@ console.log( toArray( y4 ) );
+* * * + +## See Also + +- [`@stdlib/array/to-fancy`][@stdlib/array/to-fancy]: convert an array to an object supporting fancy indexing. +- [`@stdlib/ndarray/array`][@stdlib/ndarray/array]: multidimensional arrays. +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +- [`@stdlib/ndarray/fancy`][@stdlib/ndarray/fancy]: fancy multidimensional array constructor. +
@@ -331,6 +340,16 @@ console.log( toArray( y4 ) ); [@stdlib/slice/seq2multislice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/seq2multislice + + +[@stdlib/array/to-fancy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/to-fancy + +[@stdlib/ndarray/array]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/array + +[@stdlib/ndarray/fancy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/fancy + + + diff --git a/lib/node_modules/@stdlib/number/float32/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/float32/base/docs/types/index.d.ts index 75c14f8a58b9..3396af9bedf8 100644 --- a/lib/node_modules/@stdlib/number/float32/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/number/float32/base/docs/types/index.d.ts @@ -162,11 +162,13 @@ interface Namespace { * * @example * var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); + * * var bool = ns.signbitf( toFloat32( 4.0 ) ); * // returns false * * @example * var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); + * * var bool = ns.signbitf( toFloat32( -9.14e-34 ) ); * // returns true * diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/README.md b/lib/node_modules/@stdlib/number/float32/base/signbit/README.md index 0f70925481c0..0176e61d0c06 100644 --- a/lib/node_modules/@stdlib/number/float32/base/signbit/README.md +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# signbit +# signbitf > Return a boolean indicating if the sign bit for a [single-precision floating-point number][ieee754] is on (true) or off (false). @@ -32,7 +32,7 @@ var signbitf = require( '@stdlib/number/float32/base/signbit' ); #### signbitf( x ) -Returns a `boolean` indicating if the sign bit for a [single-precision floating-point number][ieee754] is on (`true`) or off (`false`). +Returns a boolean indicating if the sign bit for a [single-precision floating-point number][ieee754] is on (`true`) or off (`false`). ```javascript var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); @@ -82,6 +82,88 @@ for ( i = 0; i < 100; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/number/float32/base/signbit.h" +``` + +#### stdlib_base_float32_signbit( x ) + +Returns an integer indicating whether the sign bit for a single-precision floating-point number is on (`1`) or off (`0`). + +```c +#include + +int8_t out = stdlib_base_float32_signbit( 3.14f ); +``` + +The function accepts the following arguments: + +- **x**: `[in] float` input value. + +```c +int8_t stdlib_base_float32_signbit( const float x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/number/float32/base/signbit.h" +#include +#include +#include + +int main( void ) { + float x[] = { 3.14f, -3.14f, 0.0f, -0.0f, 4.0f, 1.0f, -1.0f, 1.0e38f, -1.0e38f }; + + int8_t out; + int i; + for ( i = 0; i < 9; i++ ) { + stdlib_base_float32_signbit( x[ i ], &out ); + printf( "%f => signbit: %" PRId8 "\n", x[ i ], out ); + } +} +``` + +
+
diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e3e1c6d25512 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/benchmark.native.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var signbitf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( signbitf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var x; + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x = ( randu()*1.0e7 ) - 5.0e6; + y = signbitf( toFloat32( x ) ); + if ( typeof y !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( y ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/c/Makefile b/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/c/benchmark.c new file mode 100644 index 000000000000..b552e4c7f17e --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/benchmark/c/benchmark.c @@ -0,0 +1,133 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/number/float32/base/signbit.h" +#include +#include +#include +#include +#include +#include + +#define NAME "float32_signbit" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int8_t out; + double t; + float x; + int i; + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + x = ( rand_float()*200.0f ) - 100.0f; + out = stdlib_base_float32_signbit( x ); + if ( out != 0 && out != 1 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out != 0 && out != 1 ) { + printf( "unexpected result\n" ); + } + return elapsed; +} +/** +* Main execution sequence. +*/ +int main ( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/binding.gyp b/lib/node_modules/@stdlib/number/float32/base/signbit/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/float32/base/signbit/docs/types/index.d.ts index 2cfdd95ea020..7a058cb953bc 100644 --- a/lib/node_modules/@stdlib/number/float32/base/signbit/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/docs/types/index.d.ts @@ -26,11 +26,13 @@ * * @example * var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +* * var bool = signbitf( toFloat32( 4.0 ) ); * // returns false * * @example * var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +* * var bool = signbitf( toFloat32( -9.14e-34 ) ); * // returns true * diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/examples/c/Makefile b/lib/node_modules/@stdlib/number/float32/base/signbit/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/examples/c/example.c b/lib/node_modules/@stdlib/number/float32/base/signbit/examples/c/example.c new file mode 100644 index 000000000000..e8abf81d68d8 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/examples/c/example.c @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/number/float32/base/signbit.h" +#include +#include +#include + +int main( void ) { + const float x[] = { 3.14f, -3.14f, 0.0f, -0.0f, 4.0f, 1.0f, -1.0f, 1.0e38f, -1.0e38f }; + + int8_t out; + int i; + for ( i = 0; i < 9; i++ ) { + out = stdlib_base_float32_signbit( x[ i ] ); + printf( "%f => signbit: %" PRId8 "\n", x[ i ], out ); + } +} + diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/include.gypi b/lib/node_modules/@stdlib/number/float32/base/signbit/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns an integer indicating whether the sign bit for a single-precision floating-point number is on (`1`) or off (`0`). +*/ +int8_t stdlib_base_float32_signbit( const float x ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_NUMBER_FLOAT32_BASE_SIGNBIT_H diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/lib/main.js b/lib/node_modules/@stdlib/number/float32/base/signbit/lib/main.js index c15c9f873ae2..f6c782738b4b 100644 --- a/lib/node_modules/@stdlib/number/float32/base/signbit/lib/main.js +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/lib/main.js @@ -33,11 +33,13 @@ var toWord = require( '@stdlib/number/float32/base/to-word' ); * * @example * var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +* * var bool = signbitf( toFloat32( 4.0 ) ); * // returns false * * @example * var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +* * var bool = signbitf( toFloat32( -9.14e-34 ) ); * // returns true * diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/lib/native.js b/lib/node_modules/@stdlib/number/float32/base/signbit/lib/native.js new file mode 100644 index 000000000000..85ca2ebfe839 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/lib/native.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var Boolean = require( '@stdlib/boolean/ctor' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns a boolean indicating if the sign bit is on (true) or off (false). +* +* @private +* @param {number} x - input value +* @returns {boolean} - boolean indicating if sign bit is on or off +* +* @example +* var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +* +* var bool = signbitf( toFloat32( 4.0 ) ); +* // returns false +* +* @example +* var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +* +* var bool = signbitf( toFloat32( -9.14e-34 ) ); +* // returns true +* +* @example +* var bool = signbitf( 0.0 ); +* // returns false +* +* @example +* var bool = signbitf( -0.0 ); +* // returns true +*/ +function signbitf( x ) { + return Boolean( addon( x ) ); +} + + +// EXPORTS // + +module.exports = signbitf; diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/manifest.json b/lib/node_modules/@stdlib/number/float32/base/signbit/manifest.json new file mode 100644 index 000000000000..3c5a142c55e3 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/manifest.json @@ -0,0 +1,75 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/number/float32/base/to-word" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/number/float32/base/to-word" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/number/float32/base/to-word" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/package.json b/lib/node_modules/@stdlib/number/float32/base/signbit/package.json index 0b5a8f15dbf9..1f40f6e351d2 100644 --- a/lib/node_modules/@stdlib/number/float32/base/signbit/package.json +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/src/Makefile b/lib/node_modules/@stdlib/number/float32/base/signbit/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/src/addon.c b/lib/node_modules/@stdlib/number/float32/base/signbit/src/addon.c new file mode 100644 index 000000000000..5b83478f9739 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/src/addon.c @@ -0,0 +1,89 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/number/float32/base/signbit.h" +#include +#include +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + napi_status status; + + // Get callback arguments: + size_t argc = 1; + napi_value argv[ 1 ]; + status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL ); + assert( status == napi_ok ); + + // Check whether we were provided the correct number of arguments: + if ( argc < 1 ) { + status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." ); + assert( status == napi_ok ); + return NULL; + } + if ( argc > 1 ) { + status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." ); + assert( status == napi_ok ); + return NULL; + } + + napi_valuetype vtype0; + status = napi_typeof( env, argv[ 0 ], &vtype0 ); + assert( status == napi_ok ); + if ( vtype0 != napi_number ) { + status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." ); + assert( status == napi_ok ); + return NULL; + } + + double value; + status = napi_get_value_double( env, argv[ 0 ], &value ); + assert( status == napi_ok ); + + int8_t out = stdlib_base_float32_signbit( (float)value ); + + napi_value v; + status = napi_create_int32( env, (int8_t)out, &v ); + assert( status == napi_ok ); + + return v; +} + +/** +* Initializes a Node-API module. +* +* @param env environment under which the function is invoked +* @param exports exports object +* @return main export +*/ +static napi_value init( napi_env env, napi_value exports ) { + napi_value fcn; + napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn ); + assert( status == napi_ok ); + return fcn; +} + +NAPI_MODULE( NODE_GYP_MODULE_NAME, init ) diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/src/main.c b/lib/node_modules/@stdlib/number/float32/base/signbit/src/main.c new file mode 100644 index 000000000000..cc78a34d3c8a --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/src/main.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/number/float32/base/signbit.h" +#include "stdlib/number/float32/base/to_word.h" +#include + +/** +* Returns an integer indicating whether the sign bit for a single-precision floating-point number is on (`1`) or off (`0`). +* +* @param x input value +* @return result +* +* @example +* #include +* +* int8_t out = stdlib_base_float32_signbit( 3.14f ); +*/ +int8_t stdlib_base_float32_signbit( const float x ) { + uint32_t w; + + // Convert the floating-point value to a word (unsigned 32-bit integer) containing the exponent and sign: + stdlib_base_float32_to_word( x, &w ); + + // Shift off all bits which are not the sign bit and check if the sign bit is on: + return (int8_t)( w >> 31 ); +} diff --git a/lib/node_modules/@stdlib/number/float32/base/signbit/test/test.native.js b/lib/node_modules/@stdlib/number/float32/base/signbit/test/test.native.js new file mode 100644 index 000000000000..7f0fe3434f78 --- /dev/null +++ b/lib/node_modules/@stdlib/number/float32/base/signbit/test/test.native.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var toFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var signbitf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( signbitf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.equal( typeof signbitf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a boolean', opts, function test( t ) { + t.equal( typeof signbitf(5.0), 'boolean', 'returns a boolean' ); + t.end(); +}); + +tape( 'the function returns a boolean indicating if a sign bit is on (true) or off (false)', opts, function test( t ) { + var bool; + var sign; + var frac; + var exp; + var x; + var i; + + for ( i = 0; i < 5000; i++ ) { + if ( randu() < 0.5 ) { + sign = -1.0; + } else { + sign = 1.0; + } + frac = randu() * 10.0; + exp = round( randu()*44.0 ) - 22; + x = sign * frac * pow( 10.0, exp ); + x = toFloat32( x ); + bool = signbitf( x ); + if ( sign < 0.0 ) { + t.equal( bool, true, 'returns true for ' + x ); + } else { + t.equal( bool, false, 'returns false for ' + x ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/plot/components/svg/rug/README.md b/lib/node_modules/@stdlib/plot/components/svg/rug/README.md index 88adfdb93117..7f0ff357befd 100644 --- a/lib/node_modules/@stdlib/plot/components/svg/rug/README.md +++ b/lib/node_modules/@stdlib/plot/components/svg/rug/README.md @@ -146,8 +146,8 @@ var data = node.data; **Writable** property whose value is a predicate `function` which indicates whether a datum is defined and thus determines how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { @@ -181,8 +181,8 @@ var label = node.label; When retrieved, the returned value is always an accessor which accepts two parameters: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. @@ -201,8 +201,8 @@ var opacity = node.opacity; When retrieved, the returned value is always an accessor which accepts two parameters: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. diff --git a/lib/node_modules/@stdlib/plot/sparklines/base/ctor/README.md b/lib/node_modules/@stdlib/plot/sparklines/base/ctor/README.md index adcd9d3caef6..0572a3a7e2ec 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/base/ctor/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/base/ctor/README.md @@ -142,8 +142,8 @@ var desc = sparkline.description; An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/plot/sparklines/unicode/README.md b/lib/node_modules/@stdlib/plot/sparklines/unicode/README.md index f65b1ecff270..a4b80f0cd20f 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/unicode/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/unicode/README.md @@ -170,8 +170,8 @@ var str = chart.render(); An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/plot/sparklines/unicode/column/README.md b/lib/node_modules/@stdlib/plot/sparklines/unicode/column/README.md index fe23713e9ade..254ae0d28a49 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/unicode/column/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/unicode/column/README.md @@ -169,8 +169,8 @@ var str = chart.render(); An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/plot/sparklines/unicode/line/README.md b/lib/node_modules/@stdlib/plot/sparklines/unicode/line/README.md index bf476f0dd54f..438bea1c5e90 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/unicode/line/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/unicode/line/README.md @@ -169,8 +169,8 @@ var str = chart.render(); An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/plot/sparklines/unicode/tristate/README.md b/lib/node_modules/@stdlib/plot/sparklines/unicode/tristate/README.md index 3948886a9072..1e2b9c56f362 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/unicode/tristate/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/unicode/tristate/README.md @@ -141,8 +141,8 @@ var desc = chart.description; An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/plot/sparklines/unicode/up-down/README.md b/lib/node_modules/@stdlib/plot/sparklines/unicode/up-down/README.md index e64cc41bf3f7..73cf4fd22a93 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/unicode/up-down/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/unicode/up-down/README.md @@ -141,8 +141,8 @@ var desc = chart.description; An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/plot/sparklines/unicode/win-loss/README.md b/lib/node_modules/@stdlib/plot/sparklines/unicode/win-loss/README.md index d4e8792eaff0..569efc9ff25c 100644 --- a/lib/node_modules/@stdlib/plot/sparklines/unicode/win-loss/README.md +++ b/lib/node_modules/@stdlib/plot/sparklines/unicode/win-loss/README.md @@ -141,8 +141,8 @@ var desc = chart.description; An accessor `function` which defines whether a datum is defined. This accessor is used to define how missing values are encoded. When invoked, the function is provided two arguments: -- **d**: datum -- **i**: datum index +- **d**: datum. +- **i**: datum index. ```javascript function isDefined( d ) { diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c index 88d82b7da1d6..128f111ad035 100644 --- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c @@ -16,14 +16,14 @@ * limitations under the License. */ +#include "stdlib/random/base/minstd_shuffle.h" +#include "stdlib/random/base/shared.h" #include #include #include #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/minstd_shuffle.h" #define NAME "base/minstd-shuffle" #define ITERATIONS 1000000 diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c index 549dc2cd2c35..95bfda7ebdf1 100644 --- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c +++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c @@ -17,7 +17,7 @@ */ #include "stdlib/random/base/minstd_shuffle.h" -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" #include #include #include diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h b/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h index e54c6aeb4fc4..c9b804743f4a 100644 --- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h +++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h @@ -19,9 +19,8 @@ #ifndef STDLIB_RANDOM_BASE_MINSTD_SHUFFLE_H #define STDLIB_RANDOM_BASE_MINSTD_SHUFFLE_H -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/shared.h" #include -#include "stdlib/random/base.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c index 62cf8ae78740..d46bba61ed31 100644 --- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c +++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c @@ -16,13 +16,12 @@ * limitations under the License. */ -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/minstd_shuffle.h" +#include "stdlib/random/base/minstd.h" +#include "stdlib/random/base/shared.h" #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/minstd.h" -#include "stdlib/random/base/minstd_shuffle.h" // Forward declarations: static inline int8_t next( struct BasePRNGObject *obj, uint64_t *out ); @@ -183,11 +182,11 @@ static inline int8_t create_table( struct BasePRNGObject *obj, uint32_t *table ) * @return pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/minstd_shuffle.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd_shuffle.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 ); @@ -274,11 +273,11 @@ struct BasePRNGObject * stdlib_base_random_minstd_shuffle_allocate( const int32_ * @param obj PRNG object * * @example +* #include "stdlib/random/base/minstd_shuffle.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd_shuffle.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 ); @@ -326,11 +325,11 @@ void stdlib_base_random_minstd_shuffle_free( struct BasePRNGObject *obj ) { * @return status code * * @example +* #include "stdlib/random/base/minstd_shuffle.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd_shuffle.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 ); @@ -375,11 +374,11 @@ int8_t stdlib_base_random_minstd_shuffle_seed( const struct BasePRNGObject *obj, * @return pointer to a copy of the PRNG's internal state or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/minstd_shuffle.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd_shuffle.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 ); @@ -424,11 +423,11 @@ void * stdlib_base_random_minstd_shuffle_state( const struct BasePRNGObject *obj * @return status code * * @example +* #include "stdlib/random/base/minstd_shuffle.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd_shuffle.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 ); diff --git a/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c index d2194c37c3cc..95854406f4e0 100644 --- a/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c @@ -16,14 +16,14 @@ * limitations under the License. */ +#include "stdlib/random/base/minstd.h" +#include "stdlib/random/base/shared.h" #include #include #include #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/minstd.h" #define NAME "base/minstd" #define ITERATIONS 1000000 diff --git a/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c b/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c index 5e1520c62e71..9a6aa701aced 100644 --- a/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c +++ b/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c @@ -17,7 +17,7 @@ */ #include "stdlib/random/base/minstd.h" -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" #include #include #include diff --git a/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h b/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h index 324e7ab02e19..d17ac50471d8 100644 --- a/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h +++ b/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h @@ -19,9 +19,8 @@ #ifndef STDLIB_RANDOM_BASE_MINSTD_H #define STDLIB_RANDOM_BASE_MINSTD_H -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/shared.h" #include -#include "stdlib/random/base.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. diff --git a/lib/node_modules/@stdlib/random/base/minstd/src/main.c b/lib/node_modules/@stdlib/random/base/minstd/src/main.c index 6ae0f84e65e7..59c1acf5fbe5 100644 --- a/lib/node_modules/@stdlib/random/base/minstd/src/main.c +++ b/lib/node_modules/@stdlib/random/base/minstd/src/main.c @@ -16,12 +16,11 @@ * limitations under the License. */ -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/minstd.h" +#include "stdlib/random/base/shared.h" #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/minstd.h" // Forward declarations: static inline int8_t next( struct BasePRNGObject *obj, uint64_t *out ); @@ -134,11 +133,11 @@ static inline void minstd_free( struct BasePRNGObject *obj ) { * @return pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/minstd.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 ); @@ -204,11 +203,11 @@ struct BasePRNGObject * stdlib_base_random_minstd_allocate( const int32_t seed ) * @param obj PRNG object * * @example +* #include "stdlib/random/base/minstd.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 ); @@ -256,11 +255,11 @@ void stdlib_base_random_minstd_free( struct BasePRNGObject *obj ) { * @return status code * * @example +* #include "stdlib/random/base/minstd.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 ); @@ -305,11 +304,11 @@ int8_t stdlib_base_random_minstd_seed( const struct BasePRNGObject *obj, int32_t * @return pointer to a copy of the PRNG's internal state or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/minstd.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 ); @@ -354,11 +353,11 @@ void * stdlib_base_random_minstd_state( const struct BasePRNGObject *obj ) { * @return status code * * @example +* #include "stdlib/random/base/minstd.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/minstd.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 ); diff --git a/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c index 93312b8106a4..559955e7889c 100644 --- a/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c @@ -16,14 +16,14 @@ * limitations under the License. */ +#include "stdlib/random/base/mt19937.h" +#include "stdlib/random/base/shared.h" #include #include #include #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/mt19937.h" #define NAME "base/mt19937" #define ITERATIONS 1000000 diff --git a/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c b/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c index 8292539debca..dc00d7046215 100644 --- a/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c +++ b/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c @@ -17,7 +17,7 @@ */ #include "stdlib/random/base/mt19937.h" -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" #include #include #include diff --git a/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h b/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h index 274b04a341c6..a9e8381a1e23 100644 --- a/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h +++ b/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h @@ -19,9 +19,8 @@ #ifndef STDLIB_RANDOM_BASE_MT19937_H #define STDLIB_RANDOM_BASE_MT19937_H -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/shared.h" #include -#include "stdlib/random/base.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. diff --git a/lib/node_modules/@stdlib/random/base/mt19937/src/main.c b/lib/node_modules/@stdlib/random/base/mt19937/src/main.c index 61d605b8c303..2e5afe98a572 100644 --- a/lib/node_modules/@stdlib/random/base/mt19937/src/main.c +++ b/lib/node_modules/@stdlib/random/base/mt19937/src/main.c @@ -55,12 +55,11 @@ * [mt19937]: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/CODES/mt19937ar.c */ -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/mt19937.h" +#include "stdlib/random/base/shared.h" #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/mt19937.h" // Forward declarations: static inline int8_t next( struct BasePRNGObject *obj, uint64_t *out ); @@ -392,11 +391,11 @@ static inline void twist( uint32_t *state, const int32_t N ) { * @return pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/mt19937.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/mt19937.h" * * // Define a PRNG seed: * uint32_t seed[] = { 12345 }; @@ -472,11 +471,11 @@ struct BasePRNGObject * stdlib_base_random_mt19937_allocate( const uint32_t *see * @param obj PRNG object * * @example +* #include "stdlib/random/base/mt19937.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/mt19937.h" * * // Define a PRNG seed: * uint32_t seed[] = { 12345 }; @@ -527,11 +526,11 @@ void stdlib_base_random_mt19937_free( struct BasePRNGObject *obj ) { * @return status code * * @example +* #include "stdlib/random/base/mt19937.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/mt19937.h" * * // Define a PRNG seed: * uint32_t seed1[] = { 12345 }; @@ -596,11 +595,11 @@ int8_t stdlib_base_random_mt19937_seed_length( const struct BasePRNGObject *obj, * @return status code * * @example +* #include "stdlib/random/base/mt19937.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/mt19937.h" * * // Define a PRNG seed: * uint32_t seed1[] = { 12345 }; @@ -664,11 +663,11 @@ int8_t stdlib_base_random_mt19937_seed( const struct BasePRNGObject *obj, uint32 * @return pointer to a copy of the PRNG's internal state or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/mt19937.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/mt19937.h" * * // Define a PRNG seed: * uint32_t seed[] = { 12345 }; @@ -695,8 +694,8 @@ int8_t stdlib_base_random_mt19937_seed( const struct BasePRNGObject *obj, uint32 * free( state ); */ void * stdlib_base_random_mt19937_state( const struct BasePRNGObject *obj ) { + const stdlib_base_random_mt19937_state_t *so; stdlib_base_random_mt19937_state_t *state; - stdlib_base_random_mt19937_state_t *so; uint64_t nbytes; uint32_t *seed; if ( obj == NULL || obj->prng != &mt19937_prng ) { @@ -735,11 +734,11 @@ void * stdlib_base_random_mt19937_state( const struct BasePRNGObject *obj ) { * @return status code * * @example +* #include "stdlib/random/base/mt19937.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/mt19937.h" * * // Define a PRNG seed: * uint32_t seed[] = { 12345 }; diff --git a/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c index 1bde620faee6..7d78157bdce7 100644 --- a/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c @@ -17,7 +17,7 @@ */ #include "stdlib/random/base/randi.h" -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" #include #include #include diff --git a/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c b/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c index b2171d1dc6f8..3e12bab097d8 100644 --- a/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c +++ b/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c @@ -17,7 +17,7 @@ */ #include "stdlib/random/base/randi.h" -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" #include #include #include diff --git a/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h b/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h index 574b15078f52..703a1dca8f76 100644 --- a/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h +++ b/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h @@ -19,9 +19,8 @@ #ifndef STDLIB_RANDOM_BASE_RANDI_H #define STDLIB_RANDOM_BASE_RANDI_H -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/shared.h" #include -#include "stdlib/random/base.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. diff --git a/lib/node_modules/@stdlib/random/base/randi/src/main.c b/lib/node_modules/@stdlib/random/base/randi/src/main.c index 4d1112156c42..a6ffceb2ea94 100644 --- a/lib/node_modules/@stdlib/random/base/randi/src/main.c +++ b/lib/node_modules/@stdlib/random/base/randi/src/main.c @@ -16,15 +16,14 @@ * limitations under the License. */ -// Note: keep project includes in alphabetical order... -#include -#include -#include -#include "stdlib/random/base.h" +#include "stdlib/random/base/randi.h" +#include "stdlib/random/base/shared.h" #include "stdlib/random/base/minstd.h" #include "stdlib/random/base/minstd_shuffle.h" #include "stdlib/random/base/mt19937.h" -#include "stdlib/random/base/randi.h" +#include +#include +#include // Define the default PRNG: static const enum STDLIB_BASE_RANDOM_RANDI_PRNG STDLIB_BASE_RANDOM_RANDI_DEFAULT = STDLIB_BASE_RANDOM_RANDI_MT19937; @@ -43,11 +42,11 @@ static const enum STDLIB_BASE_RANDOM_RANDI_PRNG STDLIB_BASE_RANDOM_RANDI_DEFAULT * @return pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/randi.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randi.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_randi_allocate( 0 ); @@ -73,11 +72,9 @@ static const enum STDLIB_BASE_RANDOM_RANDI_PRNG STDLIB_BASE_RANDOM_RANDI_DEFAULT */ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ... ) { enum STDLIB_BASE_RANDOM_RANDI_PRNG prng; - struct BasePRNGObject *obj; - va_list args; - va_start( args, nargs ); + va_start( args, nargs ); if ( nargs < 1 ) { prng = STDLIB_BASE_RANDOM_RANDI_DEFAULT; } else { @@ -90,20 +87,25 @@ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ... } else { seed = rand(); } - obj = stdlib_base_random_minstd_allocate( seed ); - } else if ( prng == STDLIB_BASE_RANDOM_RANDI_MINSTD_SHUFFLE ) { + va_end( args ); + return stdlib_base_random_minstd_allocate( seed ); + } + if ( prng == STDLIB_BASE_RANDOM_RANDI_MINSTD_SHUFFLE ) { int32_t seed; if ( nargs > 1 ) { seed = va_arg( args, int32_t ); } else { seed = rand(); } - obj = stdlib_base_random_minstd_shuffle_allocate( seed ); - } else if ( prng == STDLIB_BASE_RANDOM_RANDI_MT19937 ) { + va_end( args ); + return stdlib_base_random_minstd_shuffle_allocate( seed ); + } + if ( prng == STDLIB_BASE_RANDOM_RANDI_MT19937 ) { + const uint32_t *seed; int64_t seed_length; - uint32_t *seed; + uint32_t tseed[ 1 ]; if ( nargs < 2 ) { - uint32_t tseed[] = { (uint32_t)rand() }; + tseed[ 0 ] = (uint32_t)rand(); seed = tseed; seed_length = 1; } else if ( nargs == 3 ) { @@ -114,13 +116,12 @@ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ... va_end( args ); return NULL; } - obj = stdlib_base_random_mt19937_allocate( seed, seed_length ); - } else { - // How did we get here? A non-implemented PRNG? - obj = NULL; + va_end( args ); + return stdlib_base_random_mt19937_allocate( seed, seed_length ); } + // How did we get here? A non-implemented PRNG? va_end( args ); - return obj; + return NULL; } /** @@ -134,11 +135,11 @@ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ... * @return pseudorandom integer * * @example +* #include "stdlib/random/base/randi.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randi.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_randi_allocate( 0 ); @@ -172,11 +173,11 @@ uint64_t stdlib_base_random_randi( struct BasePRNGObject *obj ) { * @param obj PRNG object * * @example +* #include "stdlib/random/base/randi.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randi.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_randi_allocate( 0 ); diff --git a/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c index 6ad496fa3696..c5e6f11bf4af 100644 --- a/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c @@ -17,7 +17,7 @@ */ #include "stdlib/random/base/randu.h" -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" #include #include #include diff --git a/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c b/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c index e8aae23828e1..7c4f178fb790 100644 --- a/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c +++ b/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c @@ -16,10 +16,10 @@ * limitations under the License. */ +#include "stdlib/random/base/shared.h" +#include "stdlib/random/base/randu.h" #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/randu.h" int main( void ) { int32_t i; diff --git a/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h b/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h index 3b4670f0263a..56c451003553 100644 --- a/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h +++ b/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h @@ -19,9 +19,8 @@ #ifndef STDLIB_RANDOM_BASE_RANDU_H #define STDLIB_RANDOM_BASE_RANDU_H -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/shared.h" #include -#include "stdlib/random/base.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. diff --git a/lib/node_modules/@stdlib/random/base/randu/src/main.c b/lib/node_modules/@stdlib/random/base/randu/src/main.c index 4609e45c1ec5..1fa15690f338 100644 --- a/lib/node_modules/@stdlib/random/base/randu/src/main.c +++ b/lib/node_modules/@stdlib/random/base/randu/src/main.c @@ -16,15 +16,14 @@ * limitations under the License. */ -// Note: keep project includes in alphabetical order... -#include -#include -#include -#include "stdlib/random/base.h" +#include "stdlib/random/base/randu.h" +#include "stdlib/random/base/shared.h" #include "stdlib/random/base/minstd.h" #include "stdlib/random/base/minstd_shuffle.h" #include "stdlib/random/base/mt19937.h" -#include "stdlib/random/base/randu.h" +#include +#include +#include // Define the default PRNG: static const enum STDLIB_BASE_RANDOM_RANDU_PRNG STDLIB_BASE_RANDOM_RANDU_DEFAULT = STDLIB_BASE_RANDOM_RANDU_MT19937; @@ -43,11 +42,11 @@ static const enum STDLIB_BASE_RANDOM_RANDU_PRNG STDLIB_BASE_RANDOM_RANDU_DEFAULT * @return pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer * * @example +* #include "stdlib/random/base/randu.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randu.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 ); @@ -73,11 +72,9 @@ static const enum STDLIB_BASE_RANDOM_RANDU_PRNG STDLIB_BASE_RANDOM_RANDU_DEFAULT */ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ... ) { enum STDLIB_BASE_RANDOM_RANDU_PRNG prng; - struct BasePRNGObject *obj; - va_list args; - va_start( args, nargs ); + va_start( args, nargs ); if ( nargs < 1 ) { prng = STDLIB_BASE_RANDOM_RANDU_DEFAULT; } else { @@ -90,20 +87,25 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ... } else { seed = rand(); } - obj = stdlib_base_random_minstd_allocate( seed ); - } else if ( prng == STDLIB_BASE_RANDOM_RANDU_MINSTD_SHUFFLE ) { + va_end( args ); + return stdlib_base_random_minstd_allocate( seed ); + } + if ( prng == STDLIB_BASE_RANDOM_RANDU_MINSTD_SHUFFLE ) { int32_t seed; if ( nargs > 1 ) { seed = va_arg( args, int32_t ); } else { seed = rand(); } - obj = stdlib_base_random_minstd_shuffle_allocate( seed ); - } else if ( prng == STDLIB_BASE_RANDOM_RANDU_MT19937 ) { + va_end( args ); + return stdlib_base_random_minstd_shuffle_allocate( seed ); + } + if ( prng == STDLIB_BASE_RANDOM_RANDU_MT19937 ) { + const uint32_t *seed; int64_t seed_length; - uint32_t *seed; + uint32_t tseed[ 1 ]; if ( nargs < 2 ) { - uint32_t tseed[] = { (uint32_t)rand() }; + tseed[ 0 ] = (uint32_t)rand(); seed = tseed; seed_length = 1; } else if ( nargs == 3 ) { @@ -114,13 +116,12 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ... va_end( args ); return NULL; } - obj = stdlib_base_random_mt19937_allocate( seed, seed_length ); - } else { - // How did we get here? A non-implemented PRNG? - obj = NULL; + va_end( args ); + return stdlib_base_random_mt19937_allocate( seed, seed_length ); } + // How did we get here? A non-implemented PRNG? va_end( args ); - return obj; + return NULL; } /** @@ -128,17 +129,17 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ... * * ## Notes * -* - The function returns `NAN` if provided a `NULL` pointer. +* - The function returns `NaN` if provided a `NULL` pointer. * * @param obj PRNG object * @return pseudorandom number * * @example +* #include "stdlib/random/base/randu.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randu.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 ); @@ -172,11 +173,11 @@ double stdlib_base_random_randu( struct BasePRNGObject *obj ) { * @param obj PRNG object * * @example +* #include "stdlib/random/base/randu.h" +* #include "stdlib/random/base/shared.h" * #include * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randu.h" * * // Create a PRNG: * struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 ); diff --git a/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c index a36dcf4a8b91..152eec0f3d34 100644 --- a/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c @@ -16,13 +16,13 @@ * limitations under the License. */ +#include "stdlib/random/base/shared.h" #include #include #include #include #include #include -#include "stdlib/random/base/shared.h" #define NAME "random/base/shared" #define ITERATIONS 1000000 diff --git a/lib/node_modules/@stdlib/random/base/shared/src/main.c b/lib/node_modules/@stdlib/random/base/shared/src/main.c index 2b22fcfbb173..fb81eaf24cdb 100644 --- a/lib/node_modules/@stdlib/random/base/shared/src/main.c +++ b/lib/node_modules/@stdlib/random/base/shared/src/main.c @@ -16,12 +16,10 @@ * limitations under the License. */ -// Note: keep project includes in alphabetical order... +#include "stdlib/random/base/shared.h" #include #include #include -#include -#include "stdlib/random/base/shared.h" /** * Frees a PRNG's allocated memory. @@ -59,14 +57,14 @@ uint64_t stdlib_base_prng_next( struct BasePRNGObject *obj ) { * * ## Notes * -* - The function returns `NAN` if provided a `NULL` pointer. +* - The function returns `NaN` if provided a `NULL` pointer. * * @param obj PRNG object * @return pseudorandom number */ double stdlib_base_prng_normalized( struct BasePRNGObject *obj ) { if ( obj == NULL ) { - return NAN; + return 0.0 / 0.0; // NaN } double v; obj->prng->normalized( obj, &v ); diff --git a/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c index b3299dbb67a0..608941cf9cee 100644 --- a/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c @@ -16,15 +16,15 @@ * limitations under the License. */ +#include "stdlib/random/base/uniform.h" +#include "stdlib/random/base/randu.h" +#include "stdlib/random/base/shared.h" #include #include #include #include #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/randu.h" -#include "stdlib/random/base/uniform.h" #define NAME "base/uniform" #define ITERATIONS 1000000 diff --git a/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c b/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c index 7e1a92256f85..05d304230d55 100644 --- a/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c +++ b/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c @@ -16,11 +16,11 @@ * limitations under the License. */ +#include "stdlib/random/base/uniform.h" +#include "stdlib/random/base/randu.h" +#include "stdlib/random/base/shared.h" #include #include -#include "stdlib/random/base.h" -#include "stdlib/random/base/randu.h" -#include "stdlib/random/base/uniform.h" int main( void ) { int32_t i; diff --git a/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h b/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h index 3b2ea5551765..ef6711c26d2c 100644 --- a/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h +++ b/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h @@ -19,9 +19,7 @@ #ifndef STDLIB_RANDOM_BASE_UNIFORM_H #define STDLIB_RANDOM_BASE_UNIFORM_H -// Note: keep project includes in alphabetical order... -#include -#include "stdlib/random/base.h" +#include "stdlib/random/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. diff --git a/lib/node_modules/@stdlib/random/base/uniform/src/main.c b/lib/node_modules/@stdlib/random/base/uniform/src/main.c index ad6067c9a29e..a60cdea01ce1 100644 --- a/lib/node_modules/@stdlib/random/base/uniform/src/main.c +++ b/lib/node_modules/@stdlib/random/base/uniform/src/main.c @@ -16,18 +16,16 @@ * limitations under the License. */ -// Note: keep project includes in alphabetical order... -#include -#include -#include "stdlib/random/base.h" #include "stdlib/random/base/uniform.h" +#include "stdlib/random/base/shared.h" +#include /** * Returns a pseudorandom number drawn from a continuous uniform distribution with parameters `a` (minimum support; inclusive) and `b` (maximum support; exclusive). * * ## Notes * -* - The function returns `NAN` if provided a `NULL` pointer. +* - The function returns `NaN` if provided a `NULL` pointer. * * @param randu PRNG object which generates uniformly distributed pseudorandom numbers on the interval `[0,1)` * @param a minimum support (inclusive) @@ -35,11 +33,11 @@ * @return pseudorandom number * * @example +* #include "stdlib/random/base/uniform.h" +* #include "stdlib/random/base/randu.h" +* #include "stdlib/random/base/shared.h" * #include * #include -* #include "stdlib/random/base.h" -* #include "stdlib/random/base/randu.h" -* #include "stdlib/random/base/uniform.h" * * // Create a PRNG: * struct BasePRNGObject *randu = stdlib_base_random_randu_allocate( 0 ); @@ -64,10 +62,10 @@ * stdlib_base_random_randu_free( randu, -10.0, 10.0 ); */ double stdlib_base_random_uniform( struct BasePRNGObject *randu, const double a, const double b ) { + double r; if ( randu == NULL ) { - return NAN; + return 0.0 / 0.0; // NaN } - double r; randu->prng->normalized( randu, &r ); return ( b*r ) + ( (1.0-r)*a ); } diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv index 92c14dd130dd..9ae6ff13f91f 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv @@ -244,6 +244,8 @@ base.cinv,"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\n base.clamp,"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n" base.clampf,"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n" base.cmul,"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n" +base.cmul.assign,"var out = new Float64Array( 2 );\nbase.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n" +base.cmul.strided,"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n" base.cmulf,"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n" base.cneg,"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n" base.cnegf,"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n" @@ -1700,10 +1702,10 @@ base.strided.dcopy,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nva base.strided.dcopy.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" base.strided.dcumax,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n" base.strided.dcumax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.dcumaxabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumaxabs( N, x1, 2, y1, 1 )\ny0\n" -base.strided.dcumaxabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.dcumin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumin( N, x1, 2, y1, 1 )\ny0\n" -base.strided.dcumin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.dcumaxabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n" +base.strided.dcumaxabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.dcumin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n" +base.strided.dcumin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" base.strided.dcuminabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n" base.strided.dcuminabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" base.strided.dcusum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n" @@ -1734,26 +1736,26 @@ base.strided.dmax,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided base.strided.dmax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n" base.strided.dmaxabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n" base.strided.dmaxabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n" -base.strided.dmaxabssorted,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabssorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabssorted( N, x1, stride )\n" -base.strided.dmaxabssorted.ndarray,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n" -base.strided.dmaxsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxsorted( N, x1, stride )\n" -base.strided.dmaxsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n" +base.strided.dmaxabssorted,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n" +base.strided.dmaxabssorted.ndarray,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n" +base.strided.dmaxsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n" +base.strided.dmaxsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n" base.strided.dmean,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n" base.strided.dmean.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n" -base.strided.dmeankbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n" -base.strided.dmeankbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n" -base.strided.dmeankbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n" -base.strided.dmeankbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n" -base.strided.dmeanli,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n" -base.strided.dmeanli.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n" +base.strided.dmeankbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn( 3, x1, 2 )\n" +base.strided.dmeankbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n" +base.strided.dmeankbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn2( 3, x1, 2 )\n" +base.strided.dmeankbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n" +base.strided.dmeanli,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanli( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanli( 3, x1, 2 )\n" +base.strided.dmeanli.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanli.ndarray( 3, x, 2, 1 )\n" base.strided.dmeanlipw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n" base.strided.dmeanlipw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n" -base.strided.dmeanors,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n" -base.strided.dmeanors.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n" +base.strided.dmeanors,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanors( 3, x1, 2 )\n" +base.strided.dmeanors.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanors.ndarray( 3, x, 2, 1 )\n" base.strided.dmeanpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n" base.strided.dmeanpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n" -base.strided.dmeanpw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n" -base.strided.dmeanpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n" +base.strided.dmeanpw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpw( 3, x1, 2 )\n" +base.strided.dmeanpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n" base.strided.dmeanstdev,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n" base.strided.dmeanstdev.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n" base.strided.dmeanstdevpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n" @@ -1762,18 +1764,18 @@ base.strided.dmeanvar,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out base.strided.dmeanvar.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n" base.strided.dmeanvarpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n" base.strided.dmeanvarpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n" -base.strided.dmeanwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n" -base.strided.dmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n" -base.strided.dmediansorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmediansorted( N, x1, 2 )\n" -base.strided.dmediansorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted.ndarray( N, x, 2, 1 )\n" +base.strided.dmeanwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n" +base.strided.dmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n" +base.strided.dmediansorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n" +base.strided.dmediansorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n" base.strided.dmidrange,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n" base.strided.dmidrange.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n" base.strided.dmin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n" base.strided.dmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n" base.strided.dminabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n" base.strided.dminabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n" -base.strided.dminsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminsorted( N, x1, stride )\n" -base.strided.dminsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminsorted.ndarray( N, x, 2, 1 )\n" +base.strided.dminsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n" +base.strided.dminsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n" base.strided.dmskabs,"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" base.strided.dmskabs.ndarray,"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n" base.strided.dmskabs2,"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" @@ -1792,10 +1794,10 @@ base.strided.dmskmap,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m base.strided.dmskmap.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n" base.strided.dmskmap2,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n" base.strided.dmskmap2.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n" -base.strided.dmskmax,"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmax( N, x1, 2, mask1, 2 )\n" -base.strided.dmskmax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n" -base.strided.dmskmin,"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmin( N, x1, 2, mask1, 2 )\n" -base.strided.dmskmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n" +base.strided.dmskmax,"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n" +base.strided.dmskmax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n" +base.strided.dmskmin,"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n" +base.strided.dmskmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n" base.strided.dmskramp,"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" base.strided.dmskramp.ndarray,"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n" base.strided.dmskrange,"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n" @@ -1820,10 +1822,10 @@ base.strided.dnanmeanors,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n base.strided.dnanmeanors.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n" base.strided.dnanmeanpn,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n" base.strided.dnanmeanpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n" -base.strided.dnanmeanpw,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n" -base.strided.dnanmeanpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n" -base.strided.dnanmeanwd,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n" -base.strided.dnanmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n" +base.strided.dnanmeanpw,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpw( 4, x1, 2 )\n" +base.strided.dnanmeanpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n" +base.strided.dnanmeanwd,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 3, x1, 2 )\n" +base.strided.dnanmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n" base.strided.dnanmin,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n" base.strided.dnanmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n" base.strided.dnanminabs,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n" @@ -1900,26 +1902,26 @@ base.strided.dsdot,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n base.strided.dsdot.ndarray,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n" base.strided.dsem,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n" base.strided.dsem.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dsemch,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n" -base.strided.dsemch.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n" +base.strided.dsemch,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemch( 3, 1, x1, 2 )\n" +base.strided.dsemch.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n" base.strided.dsempn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n" base.strided.dsempn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dsemtk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n" -base.strided.dsemtk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dsemwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n" -base.strided.dsemwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dsemyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n" -base.strided.dsemyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n" +base.strided.dsemtk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemtk( 3, 1, x1, 2 )\n" +base.strided.dsemtk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n" +base.strided.dsemwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemwd( 3, 1, x1, 2 )\n" +base.strided.dsemwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n" +base.strided.dsemyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemyc( 3, 1, x1, 2 )\n" +base.strided.dsemyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n" base.strided.dsmean,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n" base.strided.dsmean.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n" -base.strided.dsmeanors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n" -base.strided.dsmeanors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n" -base.strided.dsmeanpn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n" -base.strided.dsmeanpn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n" -base.strided.dsmeanpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n" -base.strided.dsmeanpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n" -base.strided.dsmeanwd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n" -base.strided.dsmeanwd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n" +base.strided.dsmeanors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanors( 3, x1, 2 )\n" +base.strided.dsmeanors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n" +base.strided.dsmeanpn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpn( 3, x1, 2 )\n" +base.strided.dsmeanpn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n" +base.strided.dsmeanpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpw( 3, x1, 2 )\n" +base.strided.dsmeanpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n" +base.strided.dsmeanwd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanwd( 3, x1, 2 )\n" +base.strided.dsmeanwd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n" base.strided.dsnanmean,"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n" base.strided.dsnanmean.ndarray,"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n" base.strided.dsnanmeanors,"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n" @@ -1958,22 +1960,22 @@ base.strided.dssumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.stri base.strided.dssumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n" base.strided.dstdev,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n" base.strided.dstdev.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dstdevch,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n" -base.strided.dstdevch.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n" +base.strided.dstdevch,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevch( 3, 1, x1, 2 )\n" +base.strided.dstdevch.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n" base.strided.dstdevpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n" base.strided.dstdevpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dstdevtk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n" -base.strided.dstdevtk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dstdevwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n" -base.strided.dstdevwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dstdevyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n" -base.strided.dstdevyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n" +base.strided.dstdevtk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevtk( 3, 1, x1, 2 )\n" +base.strided.dstdevtk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n" +base.strided.dstdevwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevwd( 3, 1, x1, 2 )\n" +base.strided.dstdevwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n" +base.strided.dstdevyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevyc( 3, 1.0, x1, 2 )\n" +base.strided.dstdevyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n" base.strided.dsum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n" base.strided.dsum.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n" base.strided.dsumkbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n" base.strided.dsumkbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n" -base.strided.dsumkbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n" -base.strided.dsumkbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n" +base.strided.dsumkbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n" +base.strided.dsumkbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n" base.strided.dsumors,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n" base.strided.dsumors.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n" base.strided.dsumpw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n" @@ -1992,74 +1994,74 @@ base.strided.dtypeResolveStr,"var out = base.strided.dtypeResolveStr( 'float64' base.strided.dtypeStr2Enum,"var out = base.strided.dtypeStr2Enum( 'float64' )\n" base.strided.dvariance,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n" base.strided.dvariance.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dvariancech,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n" -base.strided.dvariancech.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n" +base.strided.dvariancech,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancech( 3, 1, x1, 2 )\n" +base.strided.dvariancech.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n" base.strided.dvariancepn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n" base.strided.dvariancepn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dvariancetk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n" -base.strided.dvariancetk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dvariancewd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n" -base.strided.dvariancewd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n" -base.strided.dvarianceyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n" -base.strided.dvarianceyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n" +base.strided.dvariancetk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancetk( 3, 1, x1, 2 )\n" +base.strided.dvariancetk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n" +base.strided.dvariancewd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancewd( 3, 1, x1, 2 )\n" +base.strided.dvariancewd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n" +base.strided.dvarianceyc,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarianceyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarianceyc( 3, 1, x1, 2 )\n" +base.strided.dvarianceyc.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n" base.strided.dvarm,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n" base.strided.dvarm.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n" base.strided.dvarmpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n" base.strided.dvarmpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n" -base.strided.dvarmtk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n" -base.strided.dvarmtk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n" -base.strided.gapx,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n" -base.strided.gapx.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n" -base.strided.gapxsum,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n" -base.strided.gapxsum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.gapxsumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x1, stride )\n" -base.strided.gapxsumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.gapxsumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n" -base.strided.gapxsumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.gapxsumors,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n" -base.strided.gapxsumors.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.gapxsumpw,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n" -base.strided.gapxsumpw.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n" +base.strided.dvarmtk,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmtk( 3, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmtk( 3, 1.0/3.0, 1, x1, 2 )\n" +base.strided.dvarmtk.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmtk.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )\n" +base.strided.gapx,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( 4, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapx( 3, 5.0, x1, 2 )\nx0\n" +base.strided.gapx.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.gapxsum,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsum( 3, 5.0, x1, 2 )\n" +base.strided.gapxsum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.gapxsumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n" +base.strided.gapxsumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.gapxsumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n" +base.strided.gapxsumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.gapxsumors,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumors( 3, 5.0, x1, 2 )\n" +base.strided.gapxsumors.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.gapxsumpw,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumpw( 3, 5.0, x1, 2 )\n" +base.strided.gapxsumpw.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n" base.strided.gasum,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n" base.strided.gasum.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n" -base.strided.gasumpw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n" -base.strided.gasumpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n" +base.strided.gasumpw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.gasumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gasumpw( 3, x1, 2 )\n" +base.strided.gasumpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.gasumpw.ndarray( 3, x, 2, 1 )\n" base.strided.gaxpy,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n" base.strided.gaxpy.ndarray,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n" base.strided.gcopy,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n" base.strided.gcopy.ndarray,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.gcusum,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.gcusum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.gcusumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.gcusumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.gcusumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.gcusumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.gcusumors,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.gcusumors.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.gcusumpw,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n" -base.strided.gcusumpw.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.gcusum,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.gcusum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.gcusumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.gcusumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.gcusumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.gcusumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.gcusumors,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.gcusumors.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.gcusumpw,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.gcusumpw.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" base.strided.gdot,"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n" base.strided.gdot.ndarray,"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n" -base.strided.gfill,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n" -base.strided.gfill.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.gfillBy,"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n" -base.strided.gfillBy.ndarray,"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n" -base.strided.gnannsumkbn,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n" -base.strided.gnannsumkbn.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n" -base.strided.gnansum,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n" -base.strided.gnansum.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n" -base.strided.gnansumkbn,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n" -base.strided.gnansumkbn.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n" -base.strided.gnansumkbn2,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n" -base.strided.gnansumkbn2.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n" -base.strided.gnansumors,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n" -base.strided.gnansumors.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n" -base.strided.gnansumpw,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n" -base.strided.gnansumpw.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n" +base.strided.gfill,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfill( 3, 5.0, x1, 2 )\nx0\n" +base.strided.gfill.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.gfillBy,"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( 3, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfillBy( 3, x1, 2, fill )\nx0\n" +base.strided.gfillBy.ndarray,"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n" +base.strided.gnannsumkbn,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n" +base.strided.gnannsumkbn.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n" +base.strided.gnansum,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansum( 4, x1, 2 )\n" +base.strided.gnansum.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansum.ndarray( 4, x, 2, 1 )\n" +base.strided.gnansumkbn,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn( 4, x1, 2 )\n" +base.strided.gnansumkbn.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n" +base.strided.gnansumkbn2,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn2( 4, x1, 2 )\n" +base.strided.gnansumkbn2.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n" +base.strided.gnansumors,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumors( 4, x1, 2 )\n" +base.strided.gnansumors.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors.ndarray( 4, x, 2, 1 )\n" +base.strided.gnansumpw,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumpw( 4, x1, 2 )\n" +base.strided.gnansumpw.ndarray,"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n" base.strided.gnrm2,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n" base.strided.gnrm2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n" -base.strided.grev,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n" -base.strided.grev.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n" +base.strided.grev,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.grev( 3, x1, 2 )\nx0\n" +base.strided.grev.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.grev.ndarray( 3, x, 2, 1 )\n" base.strided.gscal,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n" base.strided.gscal.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n" base.strided.gsort2hp,"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n" @@ -2076,14 +2078,14 @@ base.strided.gsortsh,"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x base.strided.gsortsh.ndarray,"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n" base.strided.gsum,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n" base.strided.gsum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n" -base.strided.gsumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n" -base.strided.gsumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n" -base.strided.gsumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n" -base.strided.gsumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n" -base.strided.gsumors,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n" -base.strided.gsumors.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n" -base.strided.gsumpw,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n" -base.strided.gsumpw.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n" +base.strided.gsumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn( 3, x1, 2 )\n" +base.strided.gsumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n" +base.strided.gsumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn2( 3, x1, 2 )\n" +base.strided.gsumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n" +base.strided.gsumors,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumors( 3, x1, 2 )\n" +base.strided.gsumors.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumors.ndarray( 3, x, 2, 1 )\n" +base.strided.gsumpw,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumpw( 3, x1, 2 )\n" +base.strided.gsumpw.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumpw.ndarray( 3, x, 2, 1 )\n" base.strided.gswap,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n" base.strided.gswap.ndarray,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" base.strided.mapBy,"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n" @@ -2215,9 +2217,9 @@ base.strided.sapxsumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.s base.strided.sapxsumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n" base.strided.sapxsumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n" base.strided.sapxsumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n" -base.strided.sapxsumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n" -base.strided.sapxsumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n" -base.strided.sapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n" +base.strided.sapxsumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumors( 3, 5.0, x1, 2 )\n" +base.strided.sapxsumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n" +base.strided.sapxsumpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumpw( 3, 5.0, x1, 2 )\n" base.strided.sapxsumpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n" base.strided.sasum,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n" base.strided.sasum.ndarray,"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n" @@ -2233,17 +2235,17 @@ base.strided.scopy,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nva base.strided.scopy.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" base.strided.scumax,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n" base.strided.scumax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scumaxabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n" -base.strided.scumaxabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scumin,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n" -base.strided.scumin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scuminabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n" -base.strided.scuminabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scumaxabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumaxabs( 3, x1, 2, y1, 1 )\ny0\n" +base.strided.scumaxabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scumin,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumin( 3, x1, 2, y1, 1 )\ny0\n" +base.strided.scumin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" +base.strided.scuminabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scuminabs( 3, x1, 2, y1, 1 )\ny0\n" +base.strided.scuminabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n" base.strided.scusum,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n" base.strided.scusum.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusumkbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n" base.strided.scusumkbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" -base.strided.scusumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n" +base.strided.scusumkbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n" base.strided.scusumkbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" base.strided.scusumors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n" base.strided.scusumors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n" @@ -2261,8 +2263,8 @@ base.strided.sdsdot,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\ base.strided.sdsdot.ndarray,"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n" base.strided.sdsmean,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n" base.strided.sdsmean.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n" -base.strided.sdsmeanors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n" -base.strided.sdsmeanors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n" +base.strided.sdsmeanors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmeanors( 3, x1, 2 )\n" +base.strided.sdsmeanors.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n" base.strided.sdsnanmean,"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n" base.strided.sdsnanmean.ndarray,"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n" base.strided.sdsnanmeanors,"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n" @@ -2289,18 +2291,18 @@ base.strided.smax,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided base.strided.smax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n" base.strided.smaxabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n" base.strided.smaxabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n" -base.strided.smaxabssorted,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabssorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabssorted( N, x1, stride )\n" -base.strided.smaxabssorted.ndarray,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n" -base.strided.smaxsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxsorted( N, x1, stride )\n" -base.strided.smaxsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxsorted.ndarray( N, x, 2, 1 )\n" +base.strided.smaxabssorted,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n" +base.strided.smaxabssorted.ndarray,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n" +base.strided.smaxsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n" +base.strided.smaxsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n" base.strided.smean,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n" base.strided.smean.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n" base.strided.smeankbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n" base.strided.smeankbn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n" base.strided.smeankbn2,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n" base.strided.smeankbn2.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n" -base.strided.smeanli,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n" -base.strided.smeanli.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n" +base.strided.smeanli,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanli( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanli( 3, x1, 2 )\n" +base.strided.smeanli.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanli.ndarray( 3, x, 2, 1 )\n" base.strided.smeanlipw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n" base.strided.smeanlipw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n" base.strided.smeanors,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n" @@ -2309,18 +2311,18 @@ base.strided.smeanpn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.stri base.strided.smeanpn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n" base.strided.smeanpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n" base.strided.smeanpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n" -base.strided.smeanwd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n" -base.strided.smeanwd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n" -base.strided.smediansorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n" -base.strided.smediansorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n" +base.strided.smeanwd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanwd( 3, x1, 2 )\n" +base.strided.smeanwd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanwd.ndarray( 3, x, 2, 1 )\n" +base.strided.smediansorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n" +base.strided.smediansorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n" base.strided.smidrange,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n" base.strided.smidrange.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n" base.strided.smin,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n" base.strided.smin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n" base.strided.sminabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n" base.strided.sminabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n" -base.strided.sminsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n" -base.strided.sminsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n" +base.strided.sminsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n" +base.strided.sminsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n" base.strided.smskabs,"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" base.strided.smskabs.ndarray,"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n" base.strided.smskabs2,"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" @@ -2339,14 +2341,14 @@ base.strided.smskmap,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m base.strided.smskmap.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n" base.strided.smskmap2,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n" base.strided.smskmap2.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n" -base.strided.smskmax,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmax( N, x1, 2, mask1, 2 )\n" -base.strided.smskmax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n" -base.strided.smskmin,"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmin( N, x1, 2, mask1, 2 )\n" -base.strided.smskmin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n" +base.strided.smskmax,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n" +base.strided.smskmax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n" +base.strided.smskmin,"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n" +base.strided.smskmin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n" base.strided.smskramp,"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" base.strided.smskramp.ndarray,"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n" -base.strided.smskrange,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskrange( N, x1, 2, mask1, 2 )\n" -base.strided.smskrange.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n" +base.strided.smskrange,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n" +base.strided.smskrange.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n" base.strided.smskrsqrt,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" base.strided.smskrsqrt.ndarray,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n" base.strided.smsksqrt,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n" @@ -2439,12 +2441,12 @@ base.strided.ssqrt,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y base.strided.ssqrt.ndarray,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" base.strided.sstdev,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n" base.strided.sstdev.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n" -base.strided.sstdevch,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n" -base.strided.sstdevch.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n" +base.strided.sstdevch,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevch( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevch( 3, 1, x1, 2 )\n" +base.strided.sstdevch.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n" base.strided.sstdevpn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n" base.strided.sstdevpn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n" -base.strided.sstdevtk,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n" -base.strided.sstdevtk.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n" +base.strided.sstdevtk,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevtk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevtk( 3, 1, x1, 2 )\n" +base.strided.sstdevtk.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n" base.strided.sstdevwd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n" base.strided.sstdevwd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n" base.strided.sstdevyc,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n" @@ -2477,16 +2479,16 @@ base.strided.strunc,"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y base.strided.strunc.ndarray,"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n" base.strided.svariance,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n" base.strided.svariance.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n" -base.strided.svariancech,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n" -base.strided.svariancech.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n" +base.strided.svariancech,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancech( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancech( 3, 1, x1, 2 )\n" +base.strided.svariancech.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n" base.strided.svariancepn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n" base.strided.svariancepn.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n" -base.strided.svariancetk,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n" -base.strided.svariancetk.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n" +base.strided.svariancetk,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancetk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancetk( 3, 1, x1, 2 )\n" +base.strided.svariancetk.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n" base.strided.svariancewd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n" base.strided.svariancewd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n" -base.strided.svarianceyc,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n" -base.strided.svarianceyc.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n" +base.strided.svarianceyc,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svarianceyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svarianceyc( 3, 1, x1, 2 )\n" +base.strided.svarianceyc.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n" base.strided.ternary,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n" base.strided.ternary.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n" base.strided.unary,"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n" diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json index f1917dabbef2..f12b6ae6c436 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json @@ -1 +1 @@ -{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], 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);\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.azeros":"var out = base.azeros( 3 )\n","base.azeros2d":"var out = base.azeros2d( [ 1, 3 ] )\n","base.azeros3d":"var out = base.azeros3d( [ 1, 1, 3 ] )\n","base.azeros4d":"var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n","base.azeros5d":"var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dotcase":"var out = base.dotcase( 'Hello World!' )\nout = base.dotcase( 'I am a tiny little teapot' )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 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0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = 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base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = 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base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 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base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.cdf.factory":"var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logcdf.factory":"var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf.factory":"var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 11.0 )\n","base.dists.levy.mean":"var y = base.dists.levy.mean( 0.0, 1.0 )\ny = base.dists.levy.mean( 4.0, 3.0 )\ny = base.dists.levy.mean( NaN, 1.0 )\ny = base.dists.levy.mean( 0.0, NaN )\ny = base.dists.levy.mean( 0.0, 0.0 )\n","base.dists.levy.median":"var y = base.dists.levy.median( 0.0, 1.0 )\ny = base.dists.levy.median( 4.0, 3.0 )\ny = base.dists.levy.median( NaN, 1.0 )\ny = base.dists.levy.median( 0.0, NaN )\ny = base.dists.levy.median( 0.0, 0.0 )\n","base.dists.levy.mode":"var y = base.dists.levy.mode( 0.0, 1.0 )\ny = base.dists.levy.mode( 4.0, 3.0 )\ny = base.dists.levy.mode( NaN, 1.0 )\ny = base.dists.levy.mode( 0.0, NaN )\ny = base.dists.levy.mode( 0.0, 0.0 )\n","base.dists.levy.pdf":"var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.pdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.pdf( 0.0, 0.0, NaN )\ny = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.pdf.factory":"var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 11.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.quantile.factory":"var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.levy.stdev":"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n","base.dists.levy.variance":"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n","base.dists.logistic.cdf":"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n","base.dists.logistic.cdf.factory":"var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.0 )\n","base.dists.logistic.entropy":"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n","base.dists.logistic.kurtosis":"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n ~1.791\ny = myQuantile( 0.8 )\n ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 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base.random.poisson( 7.9 );\n","base.random.poisson.factory":"var rand = base.random.poisson.factory();\nvar r = rand( 4.0 );\nr = rand( 3.14 );\nrand = base.random.poisson.factory( 10.0 );\nr = rand();\nr = rand();\n","base.random.poisson.NAME":"var str = base.random.poisson.NAME\n","base.random.poisson.PRNG":"var prng = base.random.poisson.PRNG;\n","base.random.poisson.seed":"var seed = base.random.poisson.seed;\n","base.random.poisson.seedLength":"var len = base.random.poisson.seedLength;\n","base.random.poisson.state":"var r = base.random.poisson( 10.0 )\nr = base.random.poisson( 10.0 )\nr = base.random.poisson( 10.0 )\nvar state = base.random.poisson.state\nr = base.random.poisson( 10.0 )\nr = base.random.poisson( 10.0 )\nbase.random.poisson.state = state;\nr = base.random.poisson( 10.0 )\nr = base.random.poisson( 10.0 )\n","base.random.poisson.stateLength":"var len = base.random.poisson.stateLength;\n","base.random.poisson.byteLength":"var sz = base.random.poisson.byteLength;\n","base.random.poisson.toJSON":"var o = base.random.poisson.toJSON()\n","base.random.randi":"var r = base.random.randi();\n","base.random.randi.factory":"var randi = base.random.randi.factory();\nvar r = randi();\nr = randi();\nrandi = base.random.randi.factory({ 'name': 'minstd' });\nr = randi();\nr = randi();\n","base.random.randi.NAME":"var str = base.random.randi.NAME\n","base.random.randi.PRNG":"var prng = base.random.randi.PRNG;\n","base.random.randi.MIN":"var v = base.random.randi.MIN;\n","base.random.randi.MAX":"var v = base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = base.random.randn.toJSON()\n","base.random.randu":"var r = base.random.randu();\n","base.random.randu.factory":"var rand = base.random.randu.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randu.factory({ 'name': 'minstd' });\nr = rand();\nr = rand();\n","base.random.randu.NAME":"var str = base.random.randu.NAME\n","base.random.randu.PRNG":"var prng = base.random.randu.PRNG;\n","base.random.randu.MIN":"var v = base.random.randu.MIN;\n","base.random.randu.MAX":"var v = base.random.randu.MAX;\n","base.random.randu.seed":"var seed = base.random.randu.seed;\n","base.random.randu.seedLength":"var len = base.random.randu.seedLength;\n","base.random.randu.state":"var r = base.random.randu()\nr = base.random.randu()\nr = base.random.randu()\nvar state = base.random.randu.state;\nr = base.random.randu()\nr = base.random.randu()\nbase.random.randu.state = state;\nr = base.random.randu()\nr = base.random.randu()\n","base.random.randu.stateLength":"var len = base.random.randu.stateLength;\n","base.random.randu.byteLength":"var sz = base.random.randu.byteLength;\n","base.random.randu.toJSON":"var o = base.random.randu.toJSON()\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.rayleigh.factory":"var rand = base.random.rayleigh.factory();\nvar r = rand( 5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabssorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabssorted( N, x1, stride )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxsorted( N, x1, stride )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmediansorted( N, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted.ndarray( N, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminsorted( N, x1, stride )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.sdsnansum( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdsnansum( 4, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssum( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssum( 3, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssumpw( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssumpw( 3, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabssorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabssorted( N, x1, stride )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxsorted( N, x1, stride )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmax( N, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmin( N, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskrange( N, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn( 4, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn2( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn2( 4, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\nz.get()\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isSameDateObject( d1, d2 )\nvar d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nvar bool = isSameDateObject( d1, d2 )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","ltrimN":"var out = ltrimN( ' abc ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f );\nndarray2array( y )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noneOwnBy":"function isUnderage( v ) { return ( v < 18 ); };\nvar obj = { 'a': 11, 'b': 12, 'c': 22 };\nvar bool = noneOwnBy( obj, isUnderage )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","rtrimN":"var out = rtrimN( ' abc ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} +{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.azeros":"var out = base.azeros( 3 )\n","base.azeros2d":"var out = base.azeros2d( [ 1, 3 ] )\n","base.azeros3d":"var out = base.azeros3d( [ 1, 1, 3 ] )\n","base.azeros4d":"var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n","base.azeros5d":"var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmul.assign":"var out = new Float64Array( 2 );\nbase.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmul.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dotcase":"var out = base.dotcase( 'Hello World!' )\nout = base.dotcase( 'I am a tiny little teapot' )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 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1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = 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base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var 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)\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = 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base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 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base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n ~1.791\ny = myQuantile( 0.8 )\n ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = 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rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = base.random.randn.toJSON()\n","base.random.randu":"var r = base.random.randu();\n","base.random.randu.factory":"var rand = base.random.randu.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randu.factory({ 'name': 'minstd' });\nr = rand();\nr = rand();\n","base.random.randu.NAME":"var str = base.random.randu.NAME\n","base.random.randu.PRNG":"var prng = base.random.randu.PRNG;\n","base.random.randu.MIN":"var v = base.random.randu.MIN;\n","base.random.randu.MAX":"var v = base.random.randu.MAX;\n","base.random.randu.seed":"var seed = base.random.randu.seed;\n","base.random.randu.seedLength":"var len = base.random.randu.seedLength;\n","base.random.randu.state":"var r = base.random.randu()\nr = base.random.randu()\nr = base.random.randu()\nvar state = base.random.randu.state;\nr = base.random.randu()\nr = base.random.randu()\nbase.random.randu.state = state;\nr = base.random.randu()\nr = base.random.randu()\n","base.random.randu.stateLength":"var len = base.random.randu.stateLength;\n","base.random.randu.byteLength":"var sz = base.random.randu.byteLength;\n","base.random.randu.toJSON":"var o = base.random.randu.toJSON()\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.rayleigh.factory":"var rand = base.random.rayleigh.factory();\nvar r = rand( 5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn( 3, x1, 2 )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn2( 3, x1, 2 )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanli( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanli( 3, x1, 2 )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanli.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanors( 3, x1, 2 )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpw( 3, x1, 2 )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpw( 4, x1, 2 )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 3, x1, 2 )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemch( 3, 1, x1, 2 )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemtk( 3, 1, x1, 2 )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemwd( 3, 1, x1, 2 )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemyc( 3, 1, x1, 2 )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanors( 3, x1, 2 )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpn( 3, x1, 2 )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpw( 3, x1, 2 )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanwd( 3, x1, 2 )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevch( 3, 1, x1, 2 )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevtk( 3, 1, x1, 2 )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevwd( 3, 1, x1, 2 )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevyc( 3, 1.0, x1, 2 )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancech( 3, 1, x1, 2 )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancetk( 3, 1, x1, 2 )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancewd( 3, 1, x1, 2 )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarianceyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarianceyc( 3, 1, x1, 2 )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmtk( 3, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmtk( 3, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmtk.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( 4, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsum( 3, 5.0, x1, 2 )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumors( 3, 5.0, x1, 2 )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.gasumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gasumpw( 3, x1, 2 )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.gasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( 3, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfillBy( 3, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansum( 4, x1, 2 )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansum.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn( 4, x1, 2 )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn2( 4, x1, 2 )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumors( 4, x1, 2 )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumpw( 4, x1, 2 )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.grev( 3, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.grev.ndarray( 3, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn( 3, x1, 2 )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn2( 3, x1, 2 )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumors( 3, x1, 2 )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumors.ndarray( 3, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumpw( 3, x1, 2 )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumors( 3, 5.0, x1, 2 )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmeanors( 3, x1, 2 )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.sdsnansum( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdsnansum( 4, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssum( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssum( 3, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssumpw( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssumpw( 3, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanli( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanli( 3, x1, 2 )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanli.ndarray( 3, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanwd( 3, x1, 2 )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn( 4, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn2( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn2( 4, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevch( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevch( 3, 1, x1, 2 )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevtk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevtk( 3, 1, x1, 2 )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancech( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancech( 3, 1, x1, 2 )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancetk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancetk( 3, 1, x1, 2 )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svarianceyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svarianceyc( 3, 1, x1, 2 )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\nz.get()\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isSameDateObject( d1, d2 )\nvar d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nvar bool = isSameDateObject( d1, d2 )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","ltrimN":"var out = ltrimN( ' abc ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f );\nndarray2array( y )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noneOwnBy":"function isUnderage( v ) { return ( v < 18 ); };\nvar obj = { 'a': 11, 'b': 12, 'c': 22 };\nvar bool = noneOwnBy( obj, isUnderage )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","rtrimN":"var out = rtrimN( ' abc ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} diff --git a/lib/node_modules/@stdlib/repl/data/contributor.json b/lib/node_modules/@stdlib/repl/data/contributor.json index 59638900290e..ef329d786b14 100644 --- a/lib/node_modules/@stdlib/repl/data/contributor.json +++ b/lib/node_modules/@stdlib/repl/data/contributor.json @@ -1 +1 @@ -["Aadish Jain","Aayush Khanna","Abhijit Raut","Adarsh Palaskar","Aditya Sapra","Ahmed Atwa","Ahmed Kashkoush","Ahmed Khaled","Aleksandr","Ali Salesi","Aman Bhansali","Amit Jimiwal","Anudeep Sanapala","Athan Reines","Ayaka","Brendan Graetz","Bruno Fenzl","Bryan Elee","Chinmay Joshi","Christopher Dambamuromo","Dan Rose","Daniel Killenberger","Daniel Yu","Debashis Maharana","Desh Deepak Kant","Divyansh Seth","Dominic Lim","Dominik Moritz","Dorrin Sotoudeh","EuniceSim142","Frank Kovacs","Golden Kumar","Gunj Joshi","Gururaj Gurram","HarshaNP","Harshita Kalani","Hridyanshu","Jaimin Godhani","James Gelok","Jaysukh Makvana","Jenish Thapa","Jithin KS","Joel Mathew Koshy","Joey Reed","Jordan Gallivan","Joris Labie","Justin Dennison","Karthik Prakash","Kohantika Nath","Krishnendu Das","Kshitij-Dale","Lovelin Dhoni J B","Manik Sharma","Manvith M","Marcus Fantham","Matt Cochrane","Mihir Pandit","Milan Raj","Mohammad Kaif","Momtchil Momtchev","Muhammad Haris","Naresh Jagadeesan","Naveen Kumar","Neeraj Pathak","Nishant Shinde","Nithin Katta","Nourhan Hasan","Ognjen Jevremović","Oneday12323","Ori Miles","Philipp Burckhardt","Prajwal Kulkarni","Pranav Goswami","Pranjal Jha","Prashant Kumar Yadav","Pratik Singh","Pratyush Kumar Chouhan","Priyansh Prajapati","Priyanshu Agarwal","Pushpendra Chandravanshi","Raunak Kumar Gupta","Rejoan Sardar","Ricky Reusser","Ridam Garg","Rishav","Robert Gislason","Roman Stetsyk","Rutam Kathale","Ruthwik Chikoti","Ryan Seal","Rylan Yang","Sai Srikar Dumpeti","Sarthak Paandey","Saurabh Singh","Seyyed Parsa Neshaei","Shashank Shekhar Singh","Shivam Ahir","Shraddheya Shendre","Shubh Mehta","Shubham Mishra","Sivam Das","Snehil Shah","Soumajit Chatterjee","Spandan Barve","Stephannie Jiménez Gacha","Suraj Kumar","Tirtadwipa Manunggal","Tudor Pagu","Tufailahmed Bargir","Utkarsh","Utkarsh Raj","UtkershBasnet","Vaibhav Patel","Varad Gupta","Vinit Pandit","Vivek maurya","Xiaochuan Ye","Yaswanth Kosuru","Yernar Yergaziyev","olenkabilonizhka","rainn","rei2hu"] +["Aadish Jain","Aayush Khanna","Abhijit Raut","Adarsh Palaskar","Aditya Sapra","Ahmed Atwa","Ahmed Kashkoush","Ahmed Khaled","Aleksandr","Ali Salesi","Aman Bhansali","Amit Jimiwal","Anudeep Sanapala","Athan Reines","Ayaka","Brendan Graetz","Bruno Fenzl","Bryan Elee","Chinmay Joshi","Christopher Dambamuromo","Dan Rose","Daniel Killenberger","Daniel Yu","Debashis Maharana","Desh Deepak Kant","Dev Goel","Dhruv Arvind Singh","Divyansh Seth","Dominic Lim","Dominik Moritz","Dorrin Sotoudeh","EuniceSim142","Frank Kovacs","Golden Kumar","Gunj Joshi","Gururaj Gurram","HarshaNP","Harshita Kalani","Hridyanshu","Jaimin Godhani","James Gelok","Jaysukh Makvana","Jenish Thapa","Jithin KS","Joel Mathew Koshy","Joey Reed","Jordan Gallivan","Joris Labie","Justin Dennison","Karan Anand","Karthik Prakash","Kohantika Nath","Krishnendu Das","Kshitij-Dale","Lovelin Dhoni J B","Manik Sharma","Manvith M","Marcus Fantham","Matt Cochrane","Mihir Pandit","Milan Raj","Mohammad Kaif","Momtchil Momtchev","Muhammad Haris","Naresh Jagadeesan","Naveen Kumar","Neeraj Pathak","Nishant Shinde","Nithin Katta","Nourhan Hasan","Ognjen Jevremović","Oneday12323","Ori Miles","Philipp Burckhardt","Prajwal Kulkarni","Pranav Goswami","Pranjal Jha","Prashant Kumar Yadav","Pratik Singh","Pratyush Kumar Chouhan","Priyansh Prajapati","Priyanshu Agarwal","Pushpendra Chandravanshi","Raunak Kumar Gupta","Rejoan Sardar","Ricky Reusser","Ridam Garg","Rishav","Robert Gislason","Roman Stetsyk","Rutam Kathale","Ruthwik Chikoti","Ryan Seal","Rylan Yang","Sai Srikar Dumpeti","Sarthak Paandey","Saurabh Singh","Seyyed Parsa Neshaei","Shashank Shekhar Singh","Shivam Ahir","Shraddheya Shendre","Shubh Mehta","Shubham Mishra","Sivam Das","Snehil Shah","Soumajit Chatterjee","Spandan Barve","Stephannie Jiménez Gacha","Suraj Kumar","Tirtadwipa Manunggal","Tudor Pagu","Tufailahmed Bargir","Utkarsh","Utkarsh Raj","UtkershBasnet","Vaibhav Patel","Varad Gupta","Vinit Pandit","Vivek Maurya","Xiaochuan Ye","Yaswanth Kosuru","Yernar Yergaziyev","olenkabilonizhka","rainn","rei2hu"] diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv index 106f2252260e..977e70d6cd0e 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.csv +++ b/lib/node_modules/@stdlib/repl/help/data/data.csv @@ -243,7 +243,9 @@ base.cidentityf,"\nbase.cidentityf( z )\n Evaluates the identity function for base.cinv,"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n \n > var re = real( v )\n 0.1\n > var im = imag( v )\n -0.2\n\n See Also\n --------\n base.cdiv\n" base.clamp,"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n" base.clampf,"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n" -base.cmul,"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n" +base.cmul,"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n" +base.cmul.assign,"\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]" +base.cmul.strided,"\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub" base.cmulf,"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n" base.cneg,"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n" base.cnegf,"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n" @@ -691,7 +693,7 @@ base.dists.laplace.stdev,"\nbase.dists.laplace.stdev( μ, b )\n Returns the s base.dists.laplace.variance,"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n" base.dists.levy.cdf,"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n" base.dists.levy.cdf.factory,"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0" -base.dists.levy.entropy,"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.entropy,"\nbase.dists.levy.entropy( μ, c )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n" base.dists.levy.Levy,"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n" base.dists.levy.logcdf,"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n" base.dists.levy.logcdf.factory,"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity" @@ -708,7 +710,7 @@ base.dists.levy.stdev,"\nbase.dists.levy.stdev( μ, c )\n Returns the standar base.dists.levy.variance,"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n" base.dists.logistic.cdf,"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n" base.dists.logistic.cdf.factory,"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209" -base.dists.logistic.entropy,"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.entropy,"\nbase.dists.logistic.entropy( μ, s )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n" base.dists.logistic.kurtosis,"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n" base.dists.logistic.logcdf,"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n" base.dists.logistic.logcdf.factory,"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567" @@ -1698,14 +1700,14 @@ base.strided.dceil,"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Round base.strided.dceil.ndarray,"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil" base.strided.dcopy,"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n" base.strided.dcopy.ndarray,"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy" -base.strided.dcumax,"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n" -base.strided.dcumax.ndarray,"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax" -base.strided.dcumaxabs,"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n" -base.strided.dcumaxabs.ndarray,"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs" -base.strided.dcumin,"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n" -base.strided.dcumin.ndarray,"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin" -base.strided.dcuminabs,"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n" -base.strided.dcuminabs.ndarray,"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs" +base.strided.dcumax,"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n" +base.strided.dcumax.ndarray,"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax" +base.strided.dcumaxabs,"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n" +base.strided.dcumaxabs.ndarray,"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs" +base.strided.dcumin,"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n" +base.strided.dcumin.ndarray,"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin" +base.strided.dcuminabs,"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n" +base.strided.dcuminabs.ndarray,"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs" base.strided.dcusum,"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n" base.strided.dcusum.ndarray,"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum" base.strided.dcusumkbn,"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n" @@ -1732,28 +1734,28 @@ base.strided.dmap2,"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n App base.strided.dmap2.ndarray,"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary" base.strided.dmax,"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n" base.strided.dmax.ndarray,"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax" -base.strided.dmaxabs,"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n" -base.strided.dmaxabs.ndarray,"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs" -base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n" -base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted" -base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N, x, stride )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n" -base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted" +base.strided.dmaxabs,"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n" +base.strided.dmaxabs.ndarray,"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs" +base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n" +base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted" +base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N, x, strideX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n" +base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted" base.strided.dmean,"\nbase.strided.dmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n" base.strided.dmean.ndarray,"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean" -base.strided.dmeankbn,"\nbase.strided.dmeankbn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n" -base.strided.dmeankbn.ndarray,"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn" -base.strided.dmeankbn2,"\nbase.strided.dmeankbn2( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n" -base.strided.dmeankbn2.ndarray,"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2" -base.strided.dmeanli,"\nbase.strided.dmeanli( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n" -base.strided.dmeanli.ndarray,"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli" +base.strided.dmeankbn,"\nbase.strided.dmeankbn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n" +base.strided.dmeankbn.ndarray,"\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn" +base.strided.dmeankbn2,"\nbase.strided.dmeankbn2( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n" +base.strided.dmeankbn2.ndarray,"\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2" +base.strided.dmeanli,"\nbase.strided.dmeanli( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n" +base.strided.dmeanli.ndarray,"\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli" base.strided.dmeanlipw,"\nbase.strided.dmeanlipw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n" base.strided.dmeanlipw.ndarray,"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw" -base.strided.dmeanors,"\nbase.strided.dmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n" -base.strided.dmeanors.ndarray,"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors" +base.strided.dmeanors,"\nbase.strided.dmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n" +base.strided.dmeanors.ndarray,"\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors" base.strided.dmeanpn,"\nbase.strided.dmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n" base.strided.dmeanpn.ndarray,"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn" -base.strided.dmeanpw,"\nbase.strided.dmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n" -base.strided.dmeanpw.ndarray,"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw" +base.strided.dmeanpw,"\nbase.strided.dmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n" +base.strided.dmeanpw.ndarray,"\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw" base.strided.dmeanstdev,"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n" base.strided.dmeanstdev.ndarray,"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev" base.strided.dmeanstdevpn,"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n" @@ -1762,18 +1764,18 @@ base.strided.dmeanvar,"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut base.strided.dmeanvar.ndarray,"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance" base.strided.dmeanvarpn,"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n" base.strided.dmeanvarpn.ndarray,"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn" -base.strided.dmeanwd,"\nbase.strided.dmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n" -base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd" -base.strided.dmediansorted,"\nbase.strided.dmediansorted( N, x, stride )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n" -base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted" -base.strided.dmidrange,"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n" -base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange" -base.strided.dmin,"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n" -base.strided.dmin.ndarray,"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin" -base.strided.dminabs,"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n" -base.strided.dminabs.ndarray,"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs" -base.strided.dminsorted,"\nbase.strided.dminsorted( N, x, stride )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dminsorted( N, x1, stride )\n -2.0\n\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n" -base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted" +base.strided.dmeanwd,"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n" +base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd" +base.strided.dmediansorted,"\nbase.strided.dmediansorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n" +base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted" +base.strided.dmidrange,"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n" +base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange" +base.strided.dmin,"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n" +base.strided.dmin.ndarray,"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin" +base.strided.dminabs,"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n" +base.strided.dminabs.ndarray,"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs" +base.strided.dminsorted,"\nbase.strided.dminsorted( N, x, strideX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n" +base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted" base.strided.dmskabs,"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n" base.strided.dmskabs.ndarray,"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs" base.strided.dmskabs2,"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n" @@ -1792,14 +1794,14 @@ base.strided.dmskmap,"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n base.strided.dmskmap.ndarray,"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap" base.strided.dmskmap2,"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n" base.strided.dmskmap2.ndarray,"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2" -base.strided.dmskmax,"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n" -base.strided.dmskmax.ndarray,"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax" -base.strided.dmskmin,"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n" -base.strided.dmskmin.ndarray,"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin" +base.strided.dmskmax,"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n" +base.strided.dmskmax.ndarray,"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax" +base.strided.dmskmin,"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n" +base.strided.dmskmin.ndarray,"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin" base.strided.dmskramp,"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n" base.strided.dmskramp.ndarray,"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp" -base.strided.dmskrange,"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride Length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride Length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n" -base.strided.dmskrange.ndarray,"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride Length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange" +base.strided.dmskrange,"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n" +base.strided.dmskrange.ndarray,"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange" base.strided.dmskrsqrt,"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n" base.strided.dmskrsqrt.ndarray,"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt" base.strided.dmsksqrt,"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n" @@ -1810,24 +1812,24 @@ base.strided.dnanasum,"\nbase.strided.dnanasum( N, x, strideX )\n Computes th base.strided.dnanasum.ndarray,"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw" base.strided.dnanasumors,"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasumors( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasumors( N, x1, stride )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n" base.strided.dnanasumors.ndarray,"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum" -base.strided.dnanmax,"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n" -base.strided.dnanmax.ndarray,"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax" -base.strided.dnanmaxabs,"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n" -base.strided.dnanmaxabs.ndarray,"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs" +base.strided.dnanmax,"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n" +base.strided.dnanmax.ndarray,"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax" +base.strided.dnanmaxabs,"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n" +base.strided.dnanmaxabs.ndarray,"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs" base.strided.dnanmean,"\nbase.strided.dnanmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n" base.strided.dnanmean.ndarray,"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean" base.strided.dnanmeanors,"\nbase.strided.dnanmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n" base.strided.dnanmeanors.ndarray,"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors" base.strided.dnanmeanpn,"\nbase.strided.dnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n" base.strided.dnanmeanpn.ndarray,"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn" -base.strided.dnanmeanpw,"\nbase.strided.dnanmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n" -base.strided.dnanmeanpw.ndarray,"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean" -base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n" -base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd" -base.strided.dnanmin,"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n" -base.strided.dnanmin.ndarray,"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin" -base.strided.dnanminabs,"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n" -base.strided.dnanminabs.ndarray,"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs" +base.strided.dnanmeanpw,"\nbase.strided.dnanmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanpw( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpw( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n" +base.strided.dnanmeanpw.ndarray,"\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean" +base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n" +base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd" +base.strided.dnanmin,"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n" +base.strided.dnanmin.ndarray,"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin" +base.strided.dnanminabs,"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n" +base.strided.dnanminabs.ndarray,"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs" base.strided.dnanmskmax,"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n" base.strided.dnanmskmax.ndarray,"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax" base.strided.dnanmskmin,"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n" @@ -1844,8 +1846,8 @@ base.strided.dnannsumors,"\nbase.strided.dnannsumors( N, x, strideX, out, stride base.strided.dnannsumors.ndarray,"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors" base.strided.dnannsumpw,"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for the strided array.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n" base.strided.dnannsumpw.ndarray,"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for the strided array.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw" -base.strided.dnanrange,"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n" -base.strided.dnanrange.ndarray,"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange" +base.strided.dnanrange,"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n" +base.strided.dnanrange.ndarray,"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange" base.strided.dnanstdev,"\nbase.strided.dnanstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n" base.strided.dnanstdev.ndarray,"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev" base.strided.dnanstdevch,"\nbase.strided.dnanstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n" @@ -1884,8 +1886,8 @@ base.strided.dnrm2,"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-no base.strided.dnrm2.ndarray,"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2" base.strided.dramp,"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n" base.strided.dramp.ndarray,"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp" -base.strided.drange,"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n" -base.strided.drange.ndarray,"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange" +base.strided.drange,"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n" +base.strided.drange.ndarray,"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange" base.strided.drev,"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n" base.strided.drev.ndarray,"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev" base.strided.drsqrt,"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n" @@ -1900,26 +1902,26 @@ base.strided.dsdot,"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Compu base.strided.dsdot.ndarray,"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot" base.strided.dsem,"\nbase.strided.dsem( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsem( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsem( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n" base.strided.dsem.ndarray,"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev" -base.strided.dsemch,"\nbase.strided.dsemch( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemch( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemch( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n" -base.strided.dsemch.ndarray,"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch" +base.strided.dsemch,"\nbase.strided.dsemch( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemch( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemch( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n" +base.strided.dsemch.ndarray,"\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch" base.strided.dsempn,"\nbase.strided.dsempn( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsempn( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsempn( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n" base.strided.dsempn.ndarray,"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn" -base.strided.dsemtk,"\nbase.strided.dsemtk( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemtk( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemtk( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n" -base.strided.dsemtk.ndarray,"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk" -base.strided.dsemwd,"\nbase.strided.dsemwd( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemwd( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemwd( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n" -base.strided.dsemwd.ndarray,"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd" -base.strided.dsemyc,"\nbase.strided.dsemyc( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemyc( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemyc( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n" -base.strided.dsemyc.ndarray,"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc" +base.strided.dsemtk,"\nbase.strided.dsemtk( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemtk( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemtk( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n" +base.strided.dsemtk.ndarray,"\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk" +base.strided.dsemwd,"\nbase.strided.dsemwd( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemwd( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemwd( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n" +base.strided.dsemwd.ndarray,"\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd" +base.strided.dsemyc,"\nbase.strided.dsemyc( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemyc( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemyc( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n" +base.strided.dsemyc.ndarray,"\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc" base.strided.dsmean,"\nbase.strided.dsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n" base.strided.dsmean.ndarray,"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean" -base.strided.dsmeanors,"\nbase.strided.dsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n" -base.strided.dsmeanors.ndarray,"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors" -base.strided.dsmeanpn,"\nbase.strided.dsmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n" -base.strided.dsmeanpn.ndarray,"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn" -base.strided.dsmeanpw,"\nbase.strided.dsmeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n" -base.strided.dsmeanpw.ndarray,"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw" -base.strided.dsmeanwd,"\nbase.strided.dsmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n" -base.strided.dsmeanwd.ndarray,"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd" +base.strided.dsmeanors,"\nbase.strided.dsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n" +base.strided.dsmeanors.ndarray,"\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors" +base.strided.dsmeanpn,"\nbase.strided.dsmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n" +base.strided.dsmeanpn.ndarray,"\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn" +base.strided.dsmeanpw,"\nbase.strided.dsmeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n" +base.strided.dsmeanpw.ndarray,"\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw" +base.strided.dsmeanwd,"\nbase.strided.dsmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed.\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n" +base.strided.dsmeanwd.ndarray,"\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd" base.strided.dsnanmean,"\nbase.strided.dsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n" base.strided.dsnanmean.ndarray,"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean" base.strided.dsnanmeanors,"\nbase.strided.dsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n" @@ -1958,26 +1960,26 @@ base.strided.dssumpw,"\nbase.strided.dssumpw( N, x, strideX )\n Computes the base.strided.dssumpw.ndarray,"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw" base.strided.dstdev,"\nbase.strided.dstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n" base.strided.dstdev.ndarray,"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev" -base.strided.dstdevch,"\nbase.strided.dstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n" -base.strided.dstdevch.ndarray,"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch" +base.strided.dstdevch,"\nbase.strided.dstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n" +base.strided.dstdevch.ndarray,"\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch" base.strided.dstdevpn,"\nbase.strided.dstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n" base.strided.dstdevpn.ndarray,"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn" -base.strided.dstdevtk,"\nbase.strided.dstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n" -base.strided.dstdevtk.ndarray,"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk" -base.strided.dstdevwd,"\nbase.strided.dstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n" -base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd" -base.strided.dstdevyc,"\nbase.strided.dstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n" -base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc" -base.strided.dsum,"\nbase.strided.dsum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n" -base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum" +base.strided.dstdevtk,"\nbase.strided.dstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n" +base.strided.dstdevtk.ndarray,"\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk" +base.strided.dstdevwd,"\nbase.strided.dstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n" +base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd" +base.strided.dstdevyc,"\nbase.strided.dstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1.0, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevyc( 3, 1.0, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevyc( 3, 1.0, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n" +base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc" +base.strided.dsum,"\nbase.strided.dsum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n" +base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum" base.strided.dsumkbn,"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n" base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn" -base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n" -base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2" -base.strided.dsumors,"\nbase.strided.dsumors( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in \n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n" -base.strided.dsumors.ndarray,"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors" -base.strided.dsumpw,"\nbase.strided.dsumpw( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n" -base.strided.dsumpw.ndarray,"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw" +base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n" +base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2" +base.strided.dsumors,"\nbase.strided.dsumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n" +base.strided.dsumors.ndarray,"\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors" +base.strided.dsumpw,"\nbase.strided.dsumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n" +base.strided.dsumpw.ndarray,"\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw" base.strided.dsvariance,"\nbase.strided.dsvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n" base.strided.dsvariance.ndarray,"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance" base.strided.dsvariancepn,"\nbase.strided.dsvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n" @@ -1992,74 +1994,74 @@ base.strided.dtypeResolveStr,"\nbase.strided.dtypeResolveStr( dtype )\n Retur base.strided.dtypeStr2Enum,"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n" base.strided.dvariance,"\nbase.strided.dvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n" base.strided.dvariance.ndarray,"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance" -base.strided.dvariancech,"\nbase.strided.dvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n" -base.strided.dvariancech.ndarray,"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech" +base.strided.dvariancech,"\nbase.strided.dvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n" +base.strided.dvariancech.ndarray,"\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech" base.strided.dvariancepn,"\nbase.strided.dvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n" base.strided.dvariancepn.ndarray,"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn" -base.strided.dvariancetk,"\nbase.strided.dvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n" -base.strided.dvariancetk.ndarray,"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk" -base.strided.dvariancewd,"\nbase.strided.dvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n" -base.strided.dvariancewd.ndarray,"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd" -base.strided.dvarianceyc,"\nbase.strided.dvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n" -base.strided.dvarianceyc.ndarray,"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc" +base.strided.dvariancetk,"\nbase.strided.dvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n" +base.strided.dvariancetk.ndarray,"\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk" +base.strided.dvariancewd,"\nbase.strided.dvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n" +base.strided.dvariancewd.ndarray,"\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd" +base.strided.dvarianceyc,"\nbase.strided.dvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n" +base.strided.dvarianceyc.ndarray,"\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc" base.strided.dvarm,"\nbase.strided.dvarm( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n" base.strided.dvarm.ndarray,"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance" base.strided.dvarmpn,"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n" base.strided.dvarmpn.ndarray,"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm" -base.strided.dvarmtk,"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n" -base.strided.dvarmtk.ndarray,"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm" -base.strided.gapx,"\nbase.strided.gapx( N, alpha, x, stride )\n Adds a constant to each element in a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.gapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n" -base.strided.gapx.ndarray,"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx" -base.strided.gapxsum,"\nbase.strided.gapxsum( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n" -base.strided.gapxsum.ndarray,"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum" -base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n" -base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn" -base.strided.gapxsumkbn2,"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n" -base.strided.gapxsumkbn2.ndarray,"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2" -base.strided.gapxsumors,"\nbase.strided.gapxsumors( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n" -base.strided.gapxsumors.ndarray,"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors" -base.strided.gapxsumpw,"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n" -base.strided.gapxsumpw.ndarray,"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw" +base.strided.dvarmtk,"\nbase.strided.dvarmtk( N, mean, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmtk( 3, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmtk( 3, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n" +base.strided.dvarmtk.ndarray,"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm" +base.strided.gapx,"\nbase.strided.gapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( 4, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n" +base.strided.gapx.ndarray,"\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx" +base.strided.gapxsum,"\nbase.strided.gapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n" +base.strided.gapxsum.ndarray,"\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum" +base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n" +base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn" +base.strided.gapxsumkbn2,"\nbase.strided.gapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n" +base.strided.gapxsumkbn2.ndarray,"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2" +base.strided.gapxsumors,"\nbase.strided.gapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n" +base.strided.gapxsumors.ndarray,"\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors" +base.strided.gapxsumpw,"\nbase.strided.gapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n" +base.strided.gapxsumpw.ndarray,"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw" base.strided.gasum,"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n" base.strided.gasum.ndarray,"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum" -base.strided.gasumpw,"\nbase.strided.gasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gasumpw( N, x1, stride )\n 5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n" -base.strided.gasumpw.ndarray,"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw" +base.strided.gasumpw,"\nbase.strided.gasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.gasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n" +base.strided.gasumpw.ndarray,"\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw" base.strided.gaxpy,"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n" base.strided.gaxpy.ndarray,"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy" base.strided.gcopy,"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n" base.strided.gcopy.ndarray,"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy" -base.strided.gcusum,"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n" -base.strided.gcusum.ndarray,"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum" -base.strided.gcusumkbn,"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n" -base.strided.gcusumkbn.ndarray,"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn" -base.strided.gcusumkbn2,"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n" -base.strided.gcusumkbn2.ndarray,"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2" -base.strided.gcusumors,"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n" -base.strided.gcusumors.ndarray,"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors" -base.strided.gcusumpw,"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n" -base.strided.gcusumpw.ndarray,"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw" +base.strided.gcusum,"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n" +base.strided.gcusum.ndarray,"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum" +base.strided.gcusumkbn,"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n" +base.strided.gcusumkbn.ndarray,"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn" +base.strided.gcusumkbn2,"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n" +base.strided.gcusumkbn2.ndarray,"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2" +base.strided.gcusumors,"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n" +base.strided.gcusumors.ndarray,"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors" +base.strided.gcusumpw,"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n" +base.strided.gcusumpw.ndarray,"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw" base.strided.gdot,"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n" base.strided.gdot.ndarray,"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot" -base.strided.gfill,"\nbase.strided.gfill( N, alpha, x, stride )\n Fills a strided array with a specified scalar value.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill( N, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfill( N, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n" -base.strided.gfill.ndarray,"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill" -base.strided.gfillBy,"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy( N, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfillBy( N, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n" -base.strided.gfillBy.ndarray,"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill" -base.strided.gnannsumkbn,"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n" -base.strided.gnannsumkbn.ndarray,"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn" -base.strided.gnansum,"\nbase.strided.gnansum( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansum( N, x1, stride )\n -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n" -base.strided.gnansum.ndarray,"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean" -base.strided.gnansumkbn,"\nbase.strided.gnansumkbn( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n" -base.strided.gnansumkbn.ndarray,"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn" -base.strided.gnansumkbn2,"\nbase.strided.gnansumkbn2( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n" -base.strided.gnansumkbn2.ndarray,"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2" -base.strided.gnansumors,"\nbase.strided.gnansumors( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumors( N, x1, stride )\n -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n" -base.strided.gnansumors.ndarray,"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors" -base.strided.gnansumpw,"\nbase.strided.gnansumpw( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n" -base.strided.gnansumpw.ndarray,"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw" +base.strided.gfill,"\nbase.strided.gfill( N, alpha, x, strideX )\n Fills a strided array with a specified scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n" +base.strided.gfill.ndarray,"\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill" +base.strided.gfillBy,"\nbase.strided.gfillBy( N, x, strideX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: current array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( 3, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfillBy( 3, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n" +base.strided.gfillBy.ndarray,"\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill" +base.strided.gnannsumkbn,"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n" +base.strided.gnannsumkbn.ndarray,"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn" +base.strided.gnansum,"\nbase.strided.gnansum( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n" +base.strided.gnansum.ndarray,"\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean" +base.strided.gnansumkbn,"\nbase.strided.gnansumkbn( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n" +base.strided.gnansumkbn.ndarray,"\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn" +base.strided.gnansumkbn2,"\nbase.strided.gnansumkbn2( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n" +base.strided.gnansumkbn2.ndarray,"\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2" +base.strided.gnansumors,"\nbase.strided.gnansumors( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n" +base.strided.gnansumors.ndarray,"\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors" +base.strided.gnansumpw,"\nbase.strided.gnansumpw( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n" +base.strided.gnansumpw.ndarray,"\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw" base.strided.gnrm2,"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n" base.strided.gnrm2.ndarray,"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2" -base.strided.grev,"\nbase.strided.grev( N, x, stride )\n Reverses a strided array in-place.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev( N, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.grev( N, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n" -base.strided.grev.ndarray,"\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev" +base.strided.grev,"\nbase.strided.grev( N, x, strideX )\n Reverses a strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.grev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n" +base.strided.grev.ndarray,"\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev" base.strided.gscal,"\nbase.strided.gscal( N, alpha, x, stride )\n Multiplies a vector `x` by a constant `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gscal( x.length, alpha, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n" base.strided.gscal.ndarray,"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal" base.strided.gsort2hp,"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n" @@ -2076,14 +2078,14 @@ base.strided.gsortsh,"\nbase.strided.gsortsh( N, order, x, stride )\n Sorts a base.strided.gsortsh.ndarray,"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh" base.strided.gsum,"\nbase.strided.gsum( N, x, stride )\n Computes the sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsum( N, x1, stride )\n -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n" base.strided.gsum.ndarray,"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean" -base.strided.gsumkbn,"\nbase.strided.gsumkbn( N, x, stride )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n" -base.strided.gsumkbn.ndarray,"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn" -base.strided.gsumkbn2,"\nbase.strided.gsumkbn2( N, x, stride )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n" -base.strided.gsumkbn2.ndarray,"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2" -base.strided.gsumors,"\nbase.strided.gsumors( N, x, stride )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumors( N, x1, stride )\n -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n" -base.strided.gsumors.ndarray,"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors" -base.strided.gsumpw,"\nbase.strided.gsumpw( N, x, stride )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumpw( N, x1, stride )\n -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n" -base.strided.gsumpw.ndarray,"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw" +base.strided.gsumkbn,"\nbase.strided.gsumkbn( N, x, strideX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n" +base.strided.gsumkbn.ndarray,"\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn" +base.strided.gsumkbn2,"\nbase.strided.gsumkbn2( N, x, strideX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n" +base.strided.gsumkbn2.ndarray,"\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2" +base.strided.gsumors,"\nbase.strided.gsumors( N, x, strideX )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n" +base.strided.gsumors.ndarray,"\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors" +base.strided.gsumpw,"\nbase.strided.gsumpw( N, x, strideX )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n" +base.strided.gsumpw.ndarray,"\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw" base.strided.gswap,"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n" base.strided.gswap.ndarray,"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap" base.strided.mapBy,"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n" @@ -2207,22 +2209,22 @@ base.strided.sabs,"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Compute base.strided.sabs.ndarray,"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2" base.strided.sabs2,"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n" base.strided.sabs2.ndarray,"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs" -base.strided.sapx,"\nbase.strided.sapx( N, alpha, x, stride )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n" -base.strided.sapx.ndarray,"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx" -base.strided.sapxsum,"\nbase.strided.sapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n" -base.strided.sapxsum.ndarray,"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum" -base.strided.sapxsumkbn,"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n" -base.strided.sapxsumkbn.ndarray,"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn" -base.strided.sapxsumkbn2,"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in the \n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n" -base.strided.sapxsumkbn2.ndarray,"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2" -base.strided.sapxsumors,"\nbase.strided.sapxsumors( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumors( N, 5.0, x1, stride )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n" -base.strided.sapxsumors.ndarray,"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors" -base.strided.sapxsumpw,"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n" -base.strided.sapxsumpw.ndarray,"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw" +base.strided.sapx,"\nbase.strided.sapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n" +base.strided.sapx.ndarray,"\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx" +base.strided.sapxsum,"\nbase.strided.sapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n" +base.strided.sapxsum.ndarray,"\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum" +base.strided.sapxsumkbn,"\nbase.strided.sapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n" +base.strided.sapxsumkbn.ndarray,"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn" +base.strided.sapxsumkbn2,"\nbase.strided.sapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n" +base.strided.sapxsumkbn2.ndarray,"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2" +base.strided.sapxsumors,"\nbase.strided.sapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n" +base.strided.sapxsumors.ndarray,"\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors" +base.strided.sapxsumpw,"\nbase.strided.sapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n" +base.strided.sapxsumpw.ndarray,"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw" base.strided.sasum,"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n" base.strided.sasum.ndarray,"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum" -base.strided.sasumpw,"\nbase.strided.sasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided \n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n" -base.strided.sasumpw.ndarray,"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw" +base.strided.sasumpw,"\nbase.strided.sasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n" +base.strided.sasumpw.ndarray,"\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw" base.strided.saxpy,"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n" base.strided.saxpy.ndarray,"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy" base.strided.scbrt,"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n" @@ -2231,24 +2233,24 @@ base.strided.sceil,"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Round base.strided.sceil.ndarray,"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc" base.strided.scopy,"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n" base.strided.scopy.ndarray,"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap" -base.strided.scumax,"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n" -base.strided.scumax.ndarray,"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin" -base.strided.scumaxabs,"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n" -base.strided.scumaxabs.ndarray,"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs" -base.strided.scumin,"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n" -base.strided.scumin.ndarray,"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax" -base.strided.scuminabs,"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n" -base.strided.scuminabs.ndarray,"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin" -base.strided.scusum,"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n" -base.strided.scusum.ndarray,"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw" -base.strided.scusumkbn,"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n" -base.strided.scusumkbn.ndarray,"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2" -base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use \n a typed array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n" -base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn" -base.strided.scusumors,"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n" -base.strided.scusumors.ndarray,"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum" -base.strided.scusumpw,"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n" -base.strided.scusumpw.ndarray,"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum" +base.strided.scumax,"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n" +base.strided.scumax.ndarray,"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin" +base.strided.scumaxabs,"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n" +base.strided.scumaxabs.ndarray,"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs" +base.strided.scumin,"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n" +base.strided.scumin.ndarray,"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax" +base.strided.scuminabs,"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n" +base.strided.scuminabs.ndarray,"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin" +base.strided.scusum,"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n" +base.strided.scusum.ndarray,"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw" +base.strided.scusumkbn,"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n" +base.strided.scusumkbn.ndarray,"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2" +base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n" +base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn" +base.strided.scusumors,"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n" +base.strided.scusumors.ndarray,"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum" +base.strided.scusumpw,"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n" +base.strided.scusumpw.ndarray,"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum" base.strided.sdeg2rad,"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n" base.strided.sdeg2rad.ndarray,"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad" base.strided.sdot,"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n" @@ -2261,8 +2263,8 @@ base.strided.sdsdot,"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\ base.strided.sdsdot.ndarray,"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot" base.strided.sdsmean,"\nbase.strided.sdsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n" base.strided.sdsmean.ndarray,"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean" -base.strided.sdsmeanors,"\nbase.strided.sdsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n" -base.strided.sdsmeanors.ndarray,"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors" +base.strided.sdsmeanors,"\nbase.strided.sdsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n" +base.strided.sdsmeanors.ndarray,"\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors" base.strided.sdsnanmean,"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n" base.strided.sdsnanmean.ndarray,"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean" base.strided.sdsnanmeanors,"\nbase.strided.sdsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n" @@ -2285,22 +2287,22 @@ base.strided.smap,"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Ap base.strided.smap.ndarray,"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary" base.strided.smap2,"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n" base.strided.smap2.ndarray,"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary" -base.strided.smax,"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n" -base.strided.smax.ndarray,"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax" -base.strided.smaxabs,"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n" -base.strided.smaxabs.ndarray,"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs" -base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n" -base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted" -base.strided.smaxsorted,"\nbase.strided.smaxsorted( N, x, stride )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n" -base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted" +base.strided.smax,"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n" +base.strided.smax.ndarray,"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax" +base.strided.smaxabs,"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n" +base.strided.smaxabs.ndarray,"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs" +base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n" +base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted" +base.strided.smaxsorted,"\nbase.strided.smaxsorted( N, x, strideX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n" +base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted" base.strided.smean,"\nbase.strided.smean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smean( N, x1, stride )\n ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n" base.strided.smean.ndarray,"\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean" base.strided.smeankbn,"\nbase.strided.smeankbn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n" base.strided.smeankbn.ndarray,"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean" base.strided.smeankbn2,"\nbase.strided.smeankbn2( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n" base.strided.smeankbn2.ndarray,"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean" -base.strided.smeanli,"\nbase.strided.smeanli( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n" -base.strided.smeanli.ndarray,"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw" +base.strided.smeanli,"\nbase.strided.smeanli( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n" +base.strided.smeanli.ndarray,"\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw" base.strided.smeanlipw,"\nbase.strided.smeanlipw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n" base.strided.smeanlipw.ndarray,"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli" base.strided.smeanors,"\nbase.strided.smeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n" @@ -2309,18 +2311,18 @@ base.strided.smeanpn,"\nbase.strided.smeanpn( N, x, stride )\n Computes the a base.strided.smeanpn.ndarray,"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn" base.strided.smeanpw,"\nbase.strided.smeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n" base.strided.smeanpw.ndarray,"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean" -base.strided.smeanwd,"\nbase.strided.smeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n" -base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd" -base.strided.smediansorted,"\nbase.strided.smediansorted( N, x, stride )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n" -base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean" -base.strided.smidrange,"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n" -base.strided.smidrange.ndarray,"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange" -base.strided.smin,"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n" -base.strided.smin.ndarray,"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin" -base.strided.sminabs,"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n" -base.strided.sminabs.ndarray,"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs" -base.strided.sminsorted,"\nbase.strided.sminsorted( N, x, stride )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sminsorted( N, x1, stride )\n -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n" -base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin" +base.strided.smeanwd,"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n" +base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd" +base.strided.smediansorted,"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n" +base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean" +base.strided.smidrange,"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n" +base.strided.smidrange.ndarray,"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange" +base.strided.smin,"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n" +base.strided.smin.ndarray,"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin" +base.strided.sminabs,"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n" +base.strided.sminabs.ndarray,"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs" +base.strided.sminsorted,"\nbase.strided.sminsorted( N, x, strideX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n" +base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin" base.strided.smskabs,"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n" base.strided.smskabs.ndarray,"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2" base.strided.smskabs2,"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n" @@ -2339,24 +2341,24 @@ base.strided.smskmap,"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n base.strided.smskmap.ndarray,"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2" base.strided.smskmap2,"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n" base.strided.smskmap2.ndarray,"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap" -base.strided.smskmax,"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n" -base.strided.smskmax.ndarray,"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax" -base.strided.smskmin,"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n" -base.strided.smskmin.ndarray,"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin" +base.strided.smskmax,"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n" +base.strided.smskmax.ndarray,"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax" +base.strided.smskmin,"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n" +base.strided.smskmin.ndarray,"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin" base.strided.smskramp,"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n" base.strided.smskramp.ndarray,"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp" -base.strided.smskrange,"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n" -base.strided.smskrange.ndarray,"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange" +base.strided.smskrange,"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n" +base.strided.smskrange.ndarray,"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange" base.strided.smskrsqrt,"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n" base.strided.smskrsqrt.ndarray,"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt" base.strided.smsksqrt,"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n" base.strided.smsksqrt.ndarray,"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt" base.strided.smsktrunc,"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n" base.strided.smsktrunc.ndarray,"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc" -base.strided.snanmax,"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n" -base.strided.snanmax.ndarray,"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin" -base.strided.snanmaxabs,"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n" -base.strided.snanmaxabs.ndarray,"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs" +base.strided.snanmax,"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n" +base.strided.snanmax.ndarray,"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin" +base.strided.snanmaxabs,"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n" +base.strided.snanmaxabs.ndarray,"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs" base.strided.snanmean,"\nbase.strided.snanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n" base.strided.snanmean.ndarray,"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean" base.strided.snanmeanors,"\nbase.strided.snanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n" @@ -2365,18 +2367,18 @@ base.strided.snanmeanpn,"\nbase.strided.snanmeanpn( N, x, stride )\n Computes base.strided.snanmeanpn.ndarray,"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean" base.strided.snanmeanwd,"\nbase.strided.snanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n" base.strided.snanmeanwd.ndarray,"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean" -base.strided.snanmin,"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n" -base.strided.snanmin.ndarray,"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax" -base.strided.snanminabs,"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n" -base.strided.snanminabs.ndarray,"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin" +base.strided.snanmin,"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n" +base.strided.snanmin.ndarray,"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax" +base.strided.snanminabs,"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n" +base.strided.snanminabs.ndarray,"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin" base.strided.snanmskmax,"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n" base.strided.snanmskmax.ndarray,"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin" base.strided.snanmskmin,"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n" base.strided.snanmskmin.ndarray,"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax" base.strided.snanmskrange,"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n" base.strided.snanmskrange.ndarray,"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin" -base.strided.snanrange,"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n" -base.strided.snanrange.ndarray,"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange" +base.strided.snanrange,"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n" +base.strided.snanrange.ndarray,"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange" base.strided.snanstdev,"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n" base.strided.snanstdev.ndarray,"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev" base.strided.snanstdevch,"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n" @@ -2415,8 +2417,8 @@ base.strided.snrm2,"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-no base.strided.snrm2.ndarray,"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2" base.strided.sramp,"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n" base.strided.sramp.ndarray,"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp" -base.strided.srange,"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n" -base.strided.srange.ndarray,"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range" +base.strided.srange,"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n" +base.strided.srange.ndarray,"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range" base.strided.srev,"\nbase.strided.srev( N, x, stride )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n" base.strided.srev.ndarray,"\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev" base.strided.srsqrt,"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n" @@ -2439,12 +2441,12 @@ base.strided.ssqrt,"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Compu base.strided.ssqrt.ndarray,"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt" base.strided.sstdev,"\nbase.strided.sstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n" base.strided.sstdev.ndarray,"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance" -base.strided.sstdevch,"\nbase.strided.sstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n" -base.strided.sstdevch.ndarray,"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech" +base.strided.sstdevch,"\nbase.strided.sstdevch( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n" +base.strided.sstdevch.ndarray,"\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech" base.strided.sstdevpn,"\nbase.strided.sstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n" base.strided.sstdevpn.ndarray,"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn" -base.strided.sstdevtk,"\nbase.strided.sstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n" -base.strided.sstdevtk.ndarray,"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk" +base.strided.sstdevtk,"\nbase.strided.sstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n" +base.strided.sstdevtk.ndarray,"\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk" base.strided.sstdevwd,"\nbase.strided.sstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n" base.strided.sstdevwd.ndarray,"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd" base.strided.sstdevyc,"\nbase.strided.sstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n" @@ -2477,16 +2479,16 @@ base.strided.strunc,"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rou base.strided.strunc.ndarray,"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc" base.strided.svariance,"\nbase.strided.svariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n" base.strided.svariance.ndarray,"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance" -base.strided.svariancech,"\nbase.strided.svariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n" -base.strided.svariancech.ndarray,"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech" +base.strided.svariancech,"\nbase.strided.svariancech( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n" +base.strided.svariancech.ndarray,"\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech" base.strided.svariancepn,"\nbase.strided.svariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n" base.strided.svariancepn.ndarray,"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn" -base.strided.svariancetk,"\nbase.strided.svariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n" -base.strided.svariancetk.ndarray,"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk" +base.strided.svariancetk,"\nbase.strided.svariancetk( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n" +base.strided.svariancetk.ndarray,"\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk" base.strided.svariancewd,"\nbase.strided.svariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n" base.strided.svariancewd.ndarray,"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd" -base.strided.svarianceyc,"\nbase.strided.svarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n" -base.strided.svarianceyc.ndarray,"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc" +base.strided.svarianceyc,"\nbase.strided.svarianceyc( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc" +base.strided.svarianceyc.ndarray,"\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc" base.strided.ternary,"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n" base.strided.ternary.ndarray,"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary" base.strided.unary,"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n" @@ -3488,7 +3490,7 @@ isDateObject,"\nisDateObject( value )\n Tests if a value is a Date object.\n\ isDateObjectArray,"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n" isDigitString,"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n" isDomainName,"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n" -isDurationString,"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a non-negative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n" +isDurationString,"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n" isEmailAddress,"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n" isEmptyArray,"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n" isEmptyArrayLikeObject,"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n" diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json index 7ca5d0d2d500..569f41165edb 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.json +++ b/lib/node_modules/@stdlib/repl/help/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x[, options] )\n Computes the absolute value.\n\n If provided a number, the function returns a number.\n\n If provided an ndarray or array-like object, the function performs element-\n wise computation.\n\n If provided an array-like object, the function returns an array-like object\n having the same length and data type as `x`.\n\n If provided an ndarray, the function returns an ndarray having the same\n shape and data type as `x`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject|number\n Input value.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Output array order (either row-major (C-style) or column-major (Fortran-\n style)). Only applicable when the input array is an ndarray. By default,\n the output array order is inferred from the input array.\n\n options.dtype: string (optional)\n Output array data type. Only applicable when the input array is either\n an ndarray or array-like object. By default, the output array data type\n is inferred from the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject|number\n Results.\n\n Examples\n --------\n // Provide a number:\n > var y = abs( -1.0 )\n 1.0\n\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n > x = [ -1.0, -2.0 ];\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = abs( x )\n \n > y.get( 0, 1 )\n 2.0\n\n\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of falsy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of falsy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is falsy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of falsy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of falsy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of falsy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: the value of the current property being processed in the object\n - key: the key of the current property being processed in the object\n - object: the input object\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate. It must be non-null.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any value; otherwise, it returns `false`.\n\n Examples\n --------\n > function isNegative(value) { return value < 0 }\n > var obj = { a: 1, b: -2, c: 3, d: 4 }\n > var result = anyInBy(obj, isNegative)\n true\n\n See Also\n --------\n anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return\n value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for one own property; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n > var bool = anyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of truthy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of truthy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is truthy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of truthy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of truthy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of truthy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","aput":"\naput( x, indices, values[, options] )\n Replaces specified elements of an array with provided values.\n\n The function supports broadcasting a `values` array containing a single\n element against an `indices` array containing one or more elements.\n\n The function mutates the input array.\n\n Because each index is only validated at the time of replacing a particular\n element, mutation may occur even when one or more indices are out-of-bounds,\n including when the index mode indicates to raise an exception.\n\n If `indices` is an empty array, the function returns the input array\n unchanged.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n values: ArrayLikeObject\n Values to set. When `indices` contains one or more elements, `values`\n must be broadcast compatible with `indices` (i.e., must have either one\n element or the same number of elements as `indices`).\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aplace, atake\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: \"typed\" data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n \n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n \n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n ","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n ","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = base.acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianSquare( x )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosd( 0.0 )\n 90.0\n > y = base.acosd( PI/6.0 )\n ~58.43\n > y = base.acosd( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asind, base.atand\n","base.acosf":"\nbase.acosf( x )\n Computes the arccosine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosf( 1.0 )\n 0.0\n > y = base.acosf( 0.707 )\n ~0.7855\n > y = base.acosf( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotd( 0.0 )\n 90.0\n > y = base.acotd( PI/6.0 )\n ~62.36\n > y = base.acotd( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atand, base.cotd\n","base.acotf":"\nbase.acotf( x )\n Computes the inverse cotangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acotf( 2.0 )\n ~0.4636\n > y = base.acotf( 0.0 )\n ~1.5708\n > y = base.acotf( 0.5 )\n ~1.1071\n > y = base.acotf( 1.0 )\n ~0.7854\n > y = base.acotf( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscd( 0.0 )\n NaN\n > y = base.acscd( PI/6.0 )\n NaN\n > y = base.acscd( 1 )\n 90.0\n > y = base.acscd( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscdf( 0.0 )\n NaN\n > y = base.acscdf( 3.1415927410125732 / 6.0 )\n NaN\n > y = base.acscdf( 1.0 )\n 90.0\n > y = base.acscdf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n Computes the arccosecant of a single-precision floating-point number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acscf( 1.0 )\n ~1.57\n > y = base.acscf( 3.141592653589793 )\n ~0.32\n > y = base.acscf( -3.141592653589793 )\n ~-0.32\n > y = base.acscf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n Returns a filled \"generic\" array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled( 0.0, 3 )\n [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n Returns a filled two-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n Returns a filled three-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n Returns a filled four-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n Returns a filled five-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n Returns a filled \"generic\" array according to a provided callback function.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledBy( 3, clbk )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n Returns a filled n-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afillednd( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledndBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the input array.\n\n If provided an array-like object having a `filter` method , the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.filter( predicate, thisArg )\n\n If provided an array-like object without a `filter` method, the function\n performs a linear scan and always returns a generic array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > function f( v ) { return ( v > 0 ); };\n > var x = [ 1, -2, -3, 4 ];\n > var out = base.afilter( x, f )\n [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n Returns the first element of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: any\n First element.\n\n Examples\n --------\n > var out = base.afirst( [ 1, 2, 3 ] )\n 1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n Flattens an n-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n Flattens a two-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2d( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten2d( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n Flattens a three-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n Flattens a four-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n Flattens a five-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 2, 1 ], [ 4, 3 ] ]\n\n See Also\n --------\n base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 3, 4 ], [ 1, 2 ] ]\n\n See Also\n --------\n base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n Converts a string to alternate case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Alternate-cased string.\n\n Examples\n --------\n > var out = base.altcase( 'Hello World!' )\n 'hElLo wOrLd!'\n > out = base.altcase( 'I am a tiny little teapot' )\n 'i aM A TiNy lItTlE TeApOt'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n Returns a \"generic\" array filled with ones.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones( 3 )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n Returns a two-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones2d( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n Returns a three-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones3d( [ 1, 1, 3 ] )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n Returns a four-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n Returns a five-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n Returns an n-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aonesnd( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.aoneTo( 6 )\n [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n Parameters\n ----------\n args: Array\n Constructor arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var args = [ null, null, null ];\n > var s = new base.args2multislice( args );\n > s.data\n [ null, null, null ]\n > args = [ 10, new Slice( 0, 10, 1 ), null ];\n > s = new base.args2multislice( args );\n > s.data\n [ 10, , null ]\n\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecd( 0.0 )\n NaN\n > y = base.asecd( 2 )\n ~60.0\n > y = base.asecd( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecdf( 2.0 )\n ~60.0\n > y = base.asecdf( 0.0 )\n NaN\n > y = base.asecdf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech\n","base.asecf":"\nbase.asecf( x )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asecf( 1.0 )\n 0.0\n > y = base.asecf( 2.0 )\n ~1.0472\n > y = base.asecf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asind( 0.0 )\n 0.0\n > y = base.asind( PI / 6.0 )\n ~31.57\n > y = base.asind( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asindf( 0.0 )\n 0.0\n > y = base.asindf( 3.1415927410125732 / 6.0 )\n ~31.57\n > y = base.asindf( NaN )\n NaN\n\n See Also\n --------\n base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n Computes the arcsine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinf( 0.0 )\n 0.0\n > y = base.asinf( -3.14/6.0 )\n ~-0.551\n > y = base.asinf( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atand":"\nbase.atand( x )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in degrees).\n\n Examples\n --------\n > var y = base.atand( 0.0 )\n 0.0\n > y = base.atand( PI/6.0 )\n ~27.64\n > y = base.atand( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n Computes the arctangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanf( 0.0 )\n 0.0\n > y = base.atanf( -3.14/4.0 )\n ~-0.666\n > y = base.atanf( 3.14/4.0 )\n ~0.666\n > y = base.atanf( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n Returns a zero-filled \"generic\" array.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros( 3 )\n [ 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n Returns a zero-filled two-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros2d( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n Returns a zero-filled three-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros3d( [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n See Also\n --------\n base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n Returns a zero-filled four-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n Returns a zero-filled five-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n Returns a zero-filled n-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azerosnd( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.azeroTo( 6 )\n [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.5\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.camelcase":"\nbase.camelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = base.camelcase( 'Hello World!' )\n 'helloWorld'\n > out = base.camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = base.capitalize( 'beep' )\n 'Beep'\n > out = base.capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n \n > var re = real( v )\n -1.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n \n > var re = realf( v )\n -1.0\n > var im = imagf( v )\n 3.0\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( out )\n 5.56\n > var im = imag( out )\n -3.33\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5, 10 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1, 10 )\n 4.0\n > y = base.ceilsd( 12368.0, 2, 10 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 5.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( v )\n 5.55\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = realf( v )\n -1.0\n > var img = imagf( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n \n > var re = real( v )\n 0.1\n > var im = imag( v )\n -0.2\n\n See Also\n --------\n base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean\n Backward iteration for low surrogates.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = base.codePointAt( 'last man standing', 4, false )\n 32\n > out = base.codePointAt( 'presidential election', 8, true )\n 116\n > out = base.codePointAt( 'अनुच्छेद', 2, false )\n 2369\n > out = base.codePointAt( '🌷', 1, true )\n 127799\n","base.constantcase":"\nbase.constantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = base.constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = base.constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n Computes the cosine of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cosd( 0.0 )\n 1.0\n > y = base.cosd( 90.0 )\n 0.0\n > y = base.cosd( 60.0 )\n ~0.5\n > y = base.cosd( NaN )\n NaN\n\n See Also\n --------\n base.tand\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n Computes the cotangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cotd( 0.0 )\n Infinity\n > y = base.cotd( 90.0 )\n 0.0\n > y = base.cotd( 60.0 )\n ~0.58\n > y = base.cotd( NaN )\n NaN\n\n See Also\n --------\n base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 6.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n \n > var re = real( v )\n 5.56\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n Computes the cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.csc( 0.0 )\n Infinity\n > y = base.csc( PI/2.0 )\n ~1.0\n > y = base.csc( -PI/6.0 )\n ~-2.0\n > y = base.csc( NaN )\n NaN\n\n See Also\n --------\n base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n Computes the cosecant of a degree.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.cscd( 1.0 )\n ~57.30\n > y = base.cscd( PI )\n ~18.25\n > y = base.cscd( -PI )\n ~-18.25\n > y = base.cscd( NaN )\n NaN\n\n See Also\n --------\n base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n \n > var re = real( v )\n -0.6069136033622302\n > var im = imag( v )\n 0.79476781392673\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = base.dotcase( 'Hello World!' )\n 'hello.world'\n > out = base.dotcase( 'I am a tiny little teapot' )\n 'i.am.a.tiny.little.teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n Returns the entropy of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.entropy( 0, 1 )\n ~0.693\n > v = base.dists.discreteUniform.entropy( 4, 12 )\n ~2.197\n > v = base.dists.discreteUniform.entropy( 2, 8 )\n ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n Evaluates the quantile function for a studentized range distribution.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = quantile( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = quantile( 0.9, 17.0, 2.0 )\n ~0.913\n\n > y = quantile( 0.5, 3.0, 2.0, 2 )\n ~0.01\n\n > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n NaN\n > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.t.logcdf( 2.0, 0.1 )\n ~-0.493\n > y = base.dists.t.logcdf( 1.0, 2.0 )\n ~-0.237\n > y = base.dists.t.logcdf( -1.0, 4.0 )\n ~-1.677\n > y = base.dists.t.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.logcdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.t.logpdf( 0.3, 4.0 )\n ~-1.036\n > y = base.dists.t.logpdf( 2.0, 0.7 )\n ~-2.841\n > y = base.dists.t.logpdf( -1.0, 0.5 )\n ~-2.134\n > y = base.dists.t.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logpdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, and is thus\n equivalent to `str.length + len`. Default: str.length.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = base.endsWith( 'beep', 'ep', 4 )\n true\n > bool = base.endsWith( 'Beep', 'op', 4 )\n false\n > bool = base.endsWith( 'Beep', 'ee', 3 )\n true\n > bool = base.endsWith( 'Beep', 'ee', -1 )\n true\n > bool = base.endsWith( 'beep', '', 4 )\n true\n\n See Also\n --------\n base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.floorsd( 3.14159, 1, 10 )\n 3.0\n > y = base.floorsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePointRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster.\n - index: starting grapheme cluster index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n Function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n Generate string from a token array by interpolating values.\n\n Parameters\n ----------\n tokens: Array\n Array of string parts and format identifier objects.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n 'beep boop'\n > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n 'baz 1.00'\n > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n ' 12'\n\n See Also\n --------\n base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n Tokenize a string into an array of string parts and format identifier\n objects.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of string parts and format identifier objects.\n\n Examples\n --------\n > var out = base.formatTokenize( 'Hello %s!' )\n [ 'Hello ', {...}, '!' ]\n > out = base.formatTokenize( '%s %s %d' )\n [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n > out = base.formatTokenize( 'Pi: %.2f' )\n [ 'Pi: ', {...} ]\n\n See Also\n --------\n base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n Computes the sign of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Sign of the gamma function.\n\n Examples\n --------\n > var y = base.gammasgn( 1.0 )\n 1.0\n > y = base.gammasgn( -2.5 )\n -1.0\n > y = base.gammasgn( 0.0 )\n 0.0\n > y = base.gammasgn( NaN )\n NaN\n\n See Also\n --------\n base.gamma","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First number.\n\n b: integer\n Second number.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = base.headercase( 'Hello World!' )\n 'Hello-World'\n > out = base.headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n Converts an integer to a Slice object.\n\n In strict mode, the function returns an error object if an input value\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n max: integer\n Index upper bound (exclusive).\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s = base.int2slice( -1, 5, false );\n > s.start\n 4\n > s.stop\n 5\n > s.step\n 1\n\n See Also\n --------\n base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invcase":"\nbase.invcase( str )\n Converts a string to inverse case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Inverse-cased string.\n\n Examples\n --------\n > var out = base.invcase( 'Hello World!' )\n 'hELLO wORLD!'\n > out = base.invcase( 'I am A tiny LITTLE teapot' )\n 'i AM a TINY little TEAPOT'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a negative finite number.\n\n Examples\n --------\n > var bool = base.isNegativeFinite( -3.14 )\n true\n > bool = base.isNegativeFinite( -Infinity )\n false\n > bool = base.isNegativeFinite( 2.0 )\n false\n > bool = base.isNegativeFinite( NaN )\n false\n > bool = base.isNegativeFinite( -0.0 )\n false\n\n See Also\n --------\n base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative finite number.\n\n Examples\n --------\n > var out = base.isNonNegativeFinite( 5.0 )\n true\n > out = base.isNonNegativeFinite( 3.14 )\n true\n > out = base.isNonNegativeFinite( 0.0 )\n true\n > out = base.isNonNegativeFinite( Infinity )\n false\n > out = base.isNonNegativeFinite( -3.14 )\n false\n > out = base.isNonNegativeFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = base.isNonPositiveFinite( -3.14 )\n true\n > var bool = base.isNonPositiveFinite( 0.0 )\n true\n > var bool = base.isNonPositiveFinite( -Infinity )\n false\n > var bool = base.isNonPositiveFinite( 3.14 )\n false\n > var bool = base.isNonPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive finite number.\n\n Examples\n --------\n > var bool = base.isPositiveFinite( 5.0 )\n true\n > bool = base.isPositiveFinite( 3.14 )\n true\n > bool = base.isPositiveFinite( 0.0 )\n false\n > bool = base.isPositiveFinite( Infinity )\n false\n > bool = base.isPositiveFinite( -3.14 )\n false\n > bool = base.isPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = base.kebabcase( 'Hello World!' )\n 'hello-world'\n > out = base.kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n\n This function provides a common means for computing logarithms in base e.\n Argument reduction and adding the final term of the polynomial must be done\n by the caller for increased accuracy when different bases are used.\n\n Parameters\n ----------\n f: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var y = base.kernelLog1p( 1.0 )\n ~0.1931\n > y = base.kernelLog1p( 1.4142135623730951 )\n ~0.4672\n > y = base.kernelLog1p( NaN )\n NaN\n\n See Also\n --------\n base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.last":"\nbase.last( str, n )\n Returns the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.last( 'hello', 1 )\n 'o'\n > out = base.last( 'JavaScript', 6 )\n 'Script'\n > out = base.last( 'foo bar', 10 )\n 'foo bar'\n\n See Also\n --------\n base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n Returns the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastCodePoint( 'hello world', 1 )\n 'd'\n > out = base.lastCodePoint( 'JavaScript', 6 )\n 'Script'\n > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n 'द'\n\n See Also\n --------\n base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastGraphemeCluster( 'beep', 1 )\n 'p'\n > out = base.lastGraphemeCluster( 'Boop', 2 )\n 'op'\n > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n 'Script'\n\n See Also\n --------\n base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.leftPad( 'a', 5, ' ' )\n ' a'\n > out = base.leftPad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = base.leftPad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of a double-precision floating-point number.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = base.lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabsn( 3.14, -4.2 )\n 4.2\n > v = base.maxabsn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabsn( 3.14, NaN )\n NaN\n > v = base.maxabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabsn( 3.14, -4.2 )\n 3.14\n > v = base.minabsn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabsn( 3.14, NaN )\n NaN\n > v = base.minabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for both the minimum and\n maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabsn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabsn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabsn( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabsn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for the minimum value and\n negative infinity for the maximum value.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmaxn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxn( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxn( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmaxn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an object with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string\n Underlying data type. Must be a numeric data type or \"generic\".\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = base.ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n Returns a normalized Slice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: Slice\n Input slice object.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s1 = new Slice( 1, 10, 1 );\n > var s2 = base.normalizeSlice( s1, 5, false );\n > s2.start\n 1\n > s2.stop\n 5\n > s2.step\n 1\n > s1 = new Slice( -2, null, -1 );\n > s2 = base.normalizeSlice( s1, 10, false );\n > s2.start\n 8\n > s2.stop\n null\n > s2.step\n -1\n\n See Also\n --------\n base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = base.pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = base.pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = base.percentEncode( '☃' )\n '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n Converts an angle from radians to degrees (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n 90.0\n > d = base.rad2degf( -3.141592653589793 / 4.0 )\n -45.0\n > d = base.rad2degf( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2degf( 3.141592653589793 / 6.0 )\n 30.000001907348633\n\n See Also\n --------\n base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrt( 8.0 )\n 0.5\n > y = base.rcbrt( 1000.0 )\n 0.1\n > y = base.rcbrt( 0.0 )\n Infinity\n > y = base.rcbrt( PINF )\n 0.0\n > y = base.rcbrt( -8.0 )\n -0.5\n > y = base.rcbrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrtf( 8.0 )\n 0.5\n > y = base.rcbrtf( 1000.0 )\n ~0.1\n > y = base.rcbrtf( 0.0 )\n Infinity\n > y = base.rcbrtf( PINF )\n 0.0\n > y = base.rcbrtf( -8.0 )\n -0.5\n > y = base.rcbrtf( NaN )\n NaN\n\n See Also\n --------\n base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n Removes the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirst( 'beep', 1 )\n 'eep'\n > out = base.removeFirst( 'Boop', 1 )\n 'oop'\n > out = base.removeFirst( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n Removes the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstCodePoint( 'beep', 1 )\n 'eep'\n > out = base.removeFirstCodePoint( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstCodePoint( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n 'eep'\n > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n Removes the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLast( 'beep', 1 )\n 'bee'\n > out = base.removeLast( 'Boop', 1 )\n 'Boo'\n > out = base.removeLast( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n Removes the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastCodePoint( 'beep', 1 )\n 'bee'\n > out = base.removeLastCodePoint( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastCodePoint( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n 'bee'\n > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = base.repeat( 'a', 5 )\n 'aaaaa'\n > out = base.repeat( '', 100 )\n ''\n > out = base.repeat( 'beep', 0 )\n ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = base.replace( 'beep', /e/, 'o' )\n 'boep'\n\n See Also\n --------\n base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n Replaces the substring after the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n 'beep foo'\n > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n 'beep bofoo'\n > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n 'Hello Wofoo'\n > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n 'beep boop beepfoo'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n Replaces the substring after the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n 'beep foo'\n > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n 'beep boofoo'\n > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n 'Hellofoo'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n Replaces the substring before the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n 'foo boop'\n > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n 'foooop'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n Replaces the substring before the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n 'foo boop'\n > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n 'fooop'\n > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n 'fooo World!'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n Reverses the UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverse( 'beep' )\n 'peeb'\n > out = base.reverse( 'Boop' )\n 'pooB'\n > out = base.reverse( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n Reverses the Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseCodePoints( 'beep' )\n 'peeb'\n > out = base.reverseCodePoints( 'Boop' )\n 'pooB'\n > out = base.reverseCodePoints( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseGraphemeClusters( 'beep' )\n 'peeb'\n > out = base.reverseGraphemeClusters( 'Boop' )\n 'pooB'\n > out = base.reverseGraphemeClusters( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n Right pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.rightPad( 'a', 5, ' ' )\n 'a '\n > out = base.rightPad( 'beep', 10, 'b' )\n 'beepbbbbbb'\n > out = base.rightPad( 'boop', 12, 'beep' )\n 'boopbeepbeep'\n\n See Also\n --------\n base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string containing constructor arguments.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.sargs2multislice( 'null,null,null' );\n > s.data\n [ null, null, null ]\n > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n Computes the secant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Secant.\n\n Examples\n --------\n > var y = base.secd( 1.0 )\n ~1.0\n > y = base.secd( PI )\n ~1.0\n > y = base.secd( -PI )\n ~1.0\n > y = base.secd( NaN )\n NaN\n\n See Also\n --------\n base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n Converts a multidimensional subsequence string to a MultiSlice object.\n\n A multidimensional subsequence string is a comma-separated list of single-\n dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n For example, the following\n\n 2\n :\n 2:\n :10\n 2:10\n ::-1\n 10:2:-1\n :2:\n 2:10:\n 2::2\n :10:2\n :, :, :\n 1, 2, 3\n 0:10, 1:20:2, ::-1\n ...\n :, ..., 2\n\n are all valid multidimensional subsequence strings.\n\n Providing a single nonnegative integer `i` as a single-dimension index\n indexes the same elements as the subsequence `i:i+1`.\n\n Providing a single negative integer `i` as a single-dimension index indexes\n the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n size.\n\n While integers index the same elements as equivalent subsequences, providing\n an integer as a single-dimension index indicates to reduce the number of\n dimensions by one (e.g., if the provided shape corresponds to an array\n having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n In contrast, providing a subsequence indicates to retain a respective\n dimension (e.g., if the provided shape corresponds to an array having rank\n 2, then rank(A) == rank(A[':,:'])).\n\n A multidimensional subsequence string can only contain **one** ellipsis\n ('...') operator. An ellipsis indicates to apply ':' to each dimension\n necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n equals A['1:,:,:,2:5']).\n\n Except in the case of providing a single ellipsis, the number of single-\n dimension indexing expressions must equal the number of dimensions in the\n input shape.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if a single-dimension\n index expression which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n than the provided shape.\n - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n dimensions.\n - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n one ellipsis.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n shape: Array\n Maximum allowed slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n > s.data\n [ ]\n > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n > s.data\n [ 4, , ]\n\n See Also\n --------\n base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if provided a\n subsequence string which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n Converts a Slice object to a subsequence string.\n\n Parameters\n ----------\n slice: Slice\n Input slice.\n\n Returns\n -------\n out: string\n Subsequence string.\n\n Examples\n --------\n > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n '1:10:1'\n > out = base.slice2seq( new Slice( null, 10 ) )\n ':10'\n\n See Also\n --------\n base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n Returns the number of elements in a normalized slice.\n\n Parameters\n ----------\n slice: Slice\n Input normalized slice object.\n\n Returns\n -------\n len: integer\n Number of elements.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > base.sliceLength( s )\n 9\n\n See Also\n --------\n base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceNonReducedDimensions( s )\n [ 2 ]\n\n See Also\n --------\n base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceReducedDimensions( s )\n [ 0, 1 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n Returns the shape of a normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input normalized multi-slice object.\n\n Returns\n -------\n sh: Array\n Slice shape.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > var ms = new MultiSlice( s, s );\n > base.sliceShape( ms )\n [ 9, 9 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = base.snakecase( 'Hello World!' )\n 'hello_world'\n > out = base.snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n Evaluates Spence's function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.startcase":"\nbase.startcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = base.startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = base.startsWith( 'Beep', 'Be', 0 )\n true\n > bool = base.startsWith( 'Beep', 'ep', 0 )\n false\n > bool = base.startsWith( 'Beep', 'ee', 1 )\n true\n > bool = base.startsWith( 'Beep', 'ee', -3 )\n true\n > bool = base.startsWith( 'Beep', '', 0 )\n true\n\n See Also\n --------\n base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n\n Parameters\n ----------\n str: string\n Input string.\n \n p: number\n Probability of capitalization.\n\n Returns\n -------\n out: string\n Sticky-cased string.\n\n Examples\n --------\n > var out = base.stickycase( 'Hello World!' )\n \n\n > out = base.stickycase( 'I am a tiny little teapot' )\n \n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imagf( z )\n 6.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imagf( z )\n 8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two complex single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imagf( z )\n 6.0\n > z = x.get( 0 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imagf( z )\n 8.0\n > z = x0.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in\n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.dasumpw( 3, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.dasumpw( 3, x1, stride )\n 5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, stride )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, stride )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, stride )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dminsorted( N, x1, stride )\n -2.0\n\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride Length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride Length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride Length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasum( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasumors( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasumors( N, x1, stride )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for the strided array.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for the strided array.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsem( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsem( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemch( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemch( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsempn( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsempn( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemtk( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemtk( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemwd( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemwd( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsemyc( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsemyc( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in \n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n\n Parameters\n ----------\n dtype: integer\n Data type enumeration constant.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveEnum( 'float64' )\n \n > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n \n\n See Also\n --------\n base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n Returns the data type string associated with a supported data type value.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveStr( 'float64' )\n 'float64'\n > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n Adds a constant to each element in a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx( x.length, alpha, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx( N, alpha, x, stride )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > alpha = 5.0;\n > stride = 2;\n > base.strided.gapx( N, alpha, x1, stride )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > alpha = 5.0;\n > var stride = 2;\n > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsum( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsum( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumors( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gapxsumpw( N, 5.0, x1, stride )\n 14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gasumpw( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gasumpw( N, x1, stride )\n 5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n Fills a strided array with a specified scalar value.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill( N, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfill( N, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Constant.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy( N, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gfillBy( N, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansum( N, x1, stride )\n -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumors( N, x1, stride )\n -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gnansumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gnansumpw( N, x1, stride )\n -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n Reverses a strided array in-place.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev( N, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.grev( N, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.grev.ndarray( N, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n Multiplies a vector `x` by a constant `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gscal( x.length, alpha, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n Sorts a strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n Sorts a strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n Sorts a strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n Computes the sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsum( N, x1, stride )\n -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumkbn2( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumkbn2( N, x1, stride )\n -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumors( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumors( N, x1, stride )\n -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumors.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsumpw( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsumpw( N, x1, stride )\n -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n Computes the maximum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.max( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.max( N, x1, stride )\n 2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n Computes the maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxabs( N, x1, stride )\n 2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.maxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxsorted( N, x1, stride )\n 3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n 14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n Computes the arithmetic mean of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.mean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.mean( N, x1, stride )\n ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, stride )\n Computes the minimum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.min( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.min( N, x1, stride )\n -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n Computes the minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minabs( N, x1, stride )\n 1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.minBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minsorted( N, x1, stride )\n -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n 6\n\n See Also\n --------\n base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmax( N, x1, stride )\n 2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmaxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmin( N, x1, stride )\n -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanminabs( N, x1, stride )\n 1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanminBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanrange( N, x1, stride )\n 4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy( N, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanrangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdev( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevch( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevpn( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevtk( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevwd( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevyc( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n\n Parameters\n ----------\n x: TypedArray\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: TypedArray\n Typed array view having the same data type as the input array.\n\n Examples\n --------\n > var x = new Float64Array( 10 );\n > var out = base.strided.offsetView( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n Computes the range of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.range( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.range( N, x1, stride )\n 4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy( N, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.rangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n\n Parameters\n ----------\n x: Complex128Array|Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Real-valued floating-point array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n > x = new Complex64Array( 10 );\n > out = base.strided.reinterpretComplex( x, 0 )\n \n > bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n Returns a Float32Array view of a Complex64Array.\n\n Parameters\n ----------\n x: Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex64Array.\n\n Returns\n -------\n out: Float32Array\n Float32Array view.\n\n Examples\n --------\n > var x = new Complex64Array( 10 );\n > var out = base.strided.reinterpretComplex64( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n Returns a Float64Array view of a Complex128Array.\n\n Parameters\n ----------\n x: Complex128Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex128Array.\n\n Returns\n -------\n out: Float64Array\n Float64Array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex128( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and `stride` parameters determine which elements in the \n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sapxsumors( N, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sapxsumors( N, 5.0, x1, stride )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x, stride )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in the strided \n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride Length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > var N = base.floor( x.length / 2 );\n > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use \n a typed array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n based on starting indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array\n elements, ignore `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in the\n strided array are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.sdsnansum( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sdsnansum( 4, x1, stride )\n -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and stride parameters determine which elements in \n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sdssum( 3, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sdssum( 3, x1, stride )\n -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset,\n use a typed array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sdssumpw( 3, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sdssumpw( 3, x1, stride )\n -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, stride )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxabssorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxabssorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, stride )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smaxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smaxsorted( N, x1, stride )\n 3.0\n\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smean( N, x1, stride )\n ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanli( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanli( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanli.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, stride )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, stride )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sminsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sminsorted( N, x1, stride )\n -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.smskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided \n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, \n use a typed array view. \n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumkbn( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumkbn( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset,\n use a typed array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumkbn2( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumkbn2( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumors( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumors( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves the strided arrays\n are unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided\n array unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n Returns\n -------\n x: Float32Array\n Input array the strided array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n Computes the standard deviation of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n Computes the variance of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.varianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.varianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n Parses a string-serialized MultiSlice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n > s.data\n [ null, null, null ]\n > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n Parses a string-serialized Slice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: Slice|null\n Slice instance (or null).\n\n Examples\n --------\n > var s = new base.str2slice( 'Slice(1,10,1)' );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.str2slice( 'Slice(2,5,2)' );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n Computes the tangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tand( 0.0 )\n 0.0\n > y = base.tand( 90.0 )\n Infinity\n > y = base.tand( 60.0 )\n ~1.73\n > y = base.tand( NaN )\n NaN\n\n See Also\n --------\n base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n While powerful, this can lead to subtle bugs. In general, one should handle\n the returned ndarray as read-only.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n \n > var sh = x.shape\n [ 2, 3 ]\n > var y = base.transpose( x )\n \n > sh = y.shape\n [ 3, 2 ]\n > var bool = ( x.data === y.data )\n true\n > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n true\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string\n Custom replacement sequence.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.truncateMiddle( str, 5, '...' )\n 'b...p'\n > out = base.truncateMiddle( str, 5, '|' )\n 'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.truncsd( 3.14159, 1, 10 )\n 3.0\n > y = base.truncsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.umul":"\nbase.umul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = base.uncapitalize( 'Beep' )\n 'beep'\n > out = base.uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = base.uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n base.lowercase\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray()\n \n\n\nBooleanArray( length )\n Creates a boolean array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray( booleanarray )\n Creates a boolean array from another boolean array.\n\n Parameters\n ----------\n booleanarray: BooleanArray\n Boolean array from which to generate another boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var arr2 = new BooleanArray( arr1 )\n \n > var len = arr2.length\n 4\n\n\nBooleanArray( typedarray )\n Creates a boolean array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n \n > var arr = new BooleanArray( buf )\n \n > var len = arr.length\n 4\n\n\nBooleanArray( obj )\n Creates a boolean array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var len = arr1.length\n 4\n > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n > len = arr2.length\n 4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n Returns a boolean array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new BooleanArray( buf )\n \n > var len = arr1.length\n 240\n > var arr2 = new BooleanArray( buf, 8 )\n \n > len = arr2.length\n 232\n > var arr3 = new BooleanArray( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n \n\n\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1\n\n\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'\n\n\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false\n\n\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'\n\n\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: boolean\n Element value. \n\n Returns\n -------\n out: BooleanArray\n New typed array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n ","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: boolean\n Element value. \n\n Returns\n -------\n out: BooleanArray\n New typed array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Array\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary.\n - phones: manners of articulation for each sound.\n - symbols: complete list of ARPABET symbols used by the dictionary.\n - vp: verbal pronunciations of punctuation marks.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array()\n \n\n\nComplex64Array( length )\n Creates a 64-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex64Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex64Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex64Array( typedarray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex64Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex64Array( obj )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n > var arr2 = new Complex64Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new Complex64Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex64Array( buf, 8 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex64Array( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80\n\n\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n ","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n ","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n See Also\n --------\n isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = ddot( x, y )\n \n > z.get()\n -5.0\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n Interchanges two double-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var o = {a: 1, b: 2, c: 3};\n > var bool = everyInBy( o, positive )\n true\n\n See Also\n --------\n anyInBy, noneInBy, someInBy, everyBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > var bool = everyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n\n Examples\n --------\n > FLOAT32_E\n 2.7182817459106445\n\n See Also\n --------\n E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EXPONENT_MASK\n 2139095040\n > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n '01111111100000000000000000000000'\n\n See Also\n --------\n FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_FOURTH_PI\n 7.853981852531433e-1\n\n See Also\n --------\n FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_HALF_LN_TWO\n 0.3465735912322998\n\n See Also\n --------\n HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_HALF_PI\n 1.5707963705062866\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_HALF\n -0.6931471824645996\n\n See Also\n --------\n LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_PI\n 1.1447298526763916\n\n See Also\n --------\n FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TEN\n 2.3025851249694824\n\n See Also\n --------\n FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TWO\n 0.6931471824645996\n\n See Also\n --------\n FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT\n 127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n -127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT\n 38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n -38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_FIBONACCI\n 14930352\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n 34\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n 36\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_LUCAS\n 34\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT\n -126\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n -149\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT\n -37\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n -45\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n\n Examples\n --------\n > FLOAT32_PHI\n 1.6180340051651\n\n See Also\n --------\n PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_PI\n 3.1415927410125732\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGNIFICAND_MASK\n 8388607\n > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n '00000000011111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF\n 0.7071067690849304\n\n See Also\n --------\n SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF_PI\n 1.2533141374588013\n\n See Also\n --------\n SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PHI\n 1.272019624710083\n\n See Also\n --------\n SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PI\n 1.7724539041519165\n\n See Also\n --------\n FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_THREE\n 1.7320507764816284\n\n See Also\n --------\n FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO\n 1.4142135381698608\n\n See Also\n --------\n FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the `π` times `2` as single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO_PI\n 2.5066282749176025\n\n See Also\n --------\n FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > FLOAT32_TWO_PI\n 6.2831854820251465\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: starting character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","format":"\nformat( str, ...args )\n Insert supplied variable values into a format string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = format( 'Hello, %s!', 'World' )\n 'Hello, World!'\n\n > out = format( '%s %s', 'Hello', 'World' )\n 'Hello World'\n\n > out = format( 'Pi: %.2f', PI )\n 'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support arrow functions.\n\n Examples\n --------\n > var bool = hasArrowFunctionSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `atob` support.\n\n Examples\n --------\n > var bool = hasAtobSupport()\n \n\n See Also\n --------\n hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `btoa` support.\n\n Examples\n --------\n > var bool = hasBtoaSupport()\n \n\n See Also\n --------\n hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object.\n - result: either `x` or `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion.\n\n The predicate function callback accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value.\n - w: weight.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n\n Examples\n --------\n > IS_DOCKER\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n\n Examples\n --------\n > IS_MOBILE\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n\n Examples\n --------\n > IS_TOUCH_DEVICE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n Tests whether a value is an absolute HTTP(S) URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n Examples\n --------\n > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n true\n > bool = isAbsoluteHttpURI( 'example.com' )\n false\n > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n Tests whether a value is an absolute URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute URI.\n\n Examples\n --------\n > var bool = isAbsoluteURI( 'http://example.com/' )\n true\n > bool = isAbsoluteURI( 'example.com' )\n false\n > bool = isAbsoluteURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n Tests if a value is an arrow function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arrow function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isArrowFunction( beep )\n false\n > bool = isArrowFunction( {} )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCamelcase":"\nisCamelcase( value )\n Tests if a value is a camelcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a camelcase string.\n\n Examples\n --------\n > var bool = isCamelcase( 'helloWorld' )\n true\n > bool = isCamelcase( 'hello world' )\n false\n\n See Also\n --------\n isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n Tests if a value is a constantcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a constantcase string.\n\n Examples\n --------\n > var bool = isConstantcase( 'BEEP_BOOP' )\n true\n > bool = isConstantcase( 'BEEP and BOOP' )\n false\n\n See Also\n --------\n isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n Tests if a value is the current year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is the current year.\n\n Examples\n --------\n > var bool = isCurrentYear( new Date() )\n true\n > bool = isCurrentYear( currentYear() )\n true\n > bool = isCurrentYear( 2021 )\n false\n > bool = isCurrentYear( null )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isDomainName":"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n","isDurationString":"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a non-negative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n Tests if two arguments are both generic arrays and have equal values.\n\n The function performs strict equality comparison; thus, the function treats\n `-0` and `+0` as equal and `NaNs` as distinct.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are equal.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isEqualArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isEqualArray( x, y )\n false\n\n See Also\n --------\n isArray, isSameArray\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isKebabcase":"\nisKebabcase( value )\n Tests if a value is a string in kebab case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in kebab case.\n\n Examples\n --------\n > var bool = isKebabcase( 'beep-boop' )\n true\n > bool = isKebabcase( 'BEEP_BOOP' )\n false\n\n See Also\n --------\n isString","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n Tests if a value is an ndarray-like object having a specified data type.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n dtype: any\n Data type value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object having a\n specified data type.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLikeWithDataType( M, 'generic' )\n true\n > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n false\n > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n false\n > bool = isndarrayLikeWithDataType( {}, 'generic' )\n false\n\n See Also\n --------\n isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n Tests if a value is a finite negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite negative number.\n\n Examples\n --------\n > var bool = isNegativeFinite( -5.0 )\n true\n > bool = isNegativeFinite( new Number( -5.0 ) )\n true\n > bool = isNegativeFinite( -3.14 )\n true\n > bool = isNegativeFinite( 5.0 )\n false\n > bool = isNegativeFinite( null )\n false\n > bool = isNegativeFinite( -1.0/0.0 )\n false\n > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n Tests if a value is a nonpositive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = isNonPositiveFinite( -5.0 )\n true\n > bool = isNonPositiveFinite( new Number( -5.0 ) )\n true\n > bool = isNonPositiveFinite( -3.14 )\n true\n > bool = isNonPositiveFinite( 5.0 )\n false\n > bool = isNonPositiveFinite( null )\n false\n\n\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPascalcase":"\nisPascalcase( value )\n Tests if a value is a string in Pascal case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in Pascal case.\n\n Examples\n --------\n > var bool = isPascalcase( 'HelloWorld' )\n true\n > bool = isPascalcase( 'hello-world' )\n false\n\n See Also\n --------\n isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n Tests if a value is a positive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a positive finite number.\n\n Examples\n --------\n > var bool = isPositiveFinite( 5.0 )\n true\n > bool = isPositiveFinite( new Number( 5.0 ) )\n true\n > bool = isPositiveFinite( 3.14 )\n true\n > bool = isPositiveFinite( -5.0 )\n false\n > var bool = isPositiveFinite( 1.0/0.0 )\n false\n > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n false\n > bool = isPositiveFinite( null )\n false\n\n\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n Tests if a value is a ragged nested array. \n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a ragged nested array.\n\n Examples\n --------\n > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n true\n > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n false\n > bool = isRaggedNestedArray( 'beep' )\n false\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n Tests whether a value is a relative URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is a relative URI.\n\n Examples\n --------\n > var bool = isRelativeURI( '/images/example.png' )\n true\n > bool = isRelativeURI( 'http://www.example.com' )\n false\n > bool = isRelativeURI( null )\n false\n\n See Also\n --------\n isURI","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n Tests if two arguments are both array-like and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArrayLike( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArrayLike( x, y )\n true\n\n See Also\n --------\n isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding \n to the same date and time.\n\n Parameters\n ----------\n d1: any\n First input value.\n d2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether both values are Date objects \n corresponding to the same date and time.\n\n Examples\n --------\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var bool = isSameDateObject( d1, d2 )\n true\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n > var bool = isSameDateObject( d1, d2 )\n false\n \n See Also\n --------\n isDateObject, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n Tests if a value is a semantic version string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a provided value is a semantic version\n string.\n\n Examples\n --------\n > var bool = isSemVer( '1.0.0' )\n true\n > bool = isSemVer( '1.0.0-alpha.1' )\n true\n > bool = isSemVer( '0.1' )\n false\n > bool = isSemVer( null )\n false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n Tests if a value is a string in snake case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in snake case.\n\n Examples\n --------\n > var bool = isSnakecase( 'hello_world' )\n true\n > bool = isSnakecase( 'Hello World' )\n false\n\n See Also\n --------\n isString","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n Tests if a value is a startcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is a startcase string.\n\n Examples\n --------\n > var bool = isStartcase( 'Beep Boop' )\n true\n > bool = isStartcase( 'Beep and Boop' )\n false\n\n See Also\n --------\n isString","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n Tests if a value is a WebAssembly memory instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a WebAssembly memory instance.\n\n Examples\n --------\n > var bool = isWebAssemblyMemory( {} )\n false\n\n See Also\n --------\n hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n Tests if a string is well-formed.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is well-formed.\n\n Examples\n --------\n > var bool = isWellFormedString( '' )\n true\n\n > bool = isWellFormedString( new String( '' ) )\n true\n\n > bool = isWellFormedString( '\\uDBFF' )\n false\n\n > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n false\n\n > bool = isWellFormedString( [] )\n false\n\n > bool = isWellFormedString( '-5' )\n true\n\n > bool = isWellFormedString( null )\n false\n\n\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false\n\n\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value.\n - index: iterated value index (zero-based).\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value.\n - sprev: previous source iterated value.\n - dprev: previous downstream iterated value.\n - index: source iteration index (zero-based).\n - acc: previous resolved value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values.\n - index: iteration index (zero-based).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value.\n - index: source iteration index (zero-based).\n - n: iteration index (zero-based).\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value.\n - i: input iteration index (zero-based).\n - n: output (strided) iteration index (zero-based).\n - curr: current stride.\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 64.\n\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant\n object has the next\n iterated value (if one exists) and a\n boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n\n Examples\n --------\n > var it = iterTribonnaciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 0\n\n See Also\n --------\n base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n Returns the last character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = last( 'beep' )\n 'p'\n > out = last( 'Boop', 2 )\n 'op'\n > out = last( 'foo bar', 3 )\n 'bar'\n\n See Also\n --------\n firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n Trims `n` characters from the beginning of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrimN( ' abc ', 2 )\n 'abc '\n > var out = ltrimN( '!!!abc!!!', 2, '!' )\n '!abc!!!'\n\n See Also\n --------\n rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - index: invocation index (starting from zero).\n - next: callback to be invoked upon function completion.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `key`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - key\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - key\n - value\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - key: transformed key.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `value`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - value\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - value\n - key\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - value: transformed value.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size.\n - cities: cities.\n - labels: map labels.\n - temperature: temperature during the army's return from Russia.\n - rivers: river data.\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier).\n - title: chapter title (if available; otherwise, empty).\n - text: chapter text.\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n Converts an ndarray to an object supporting fancy indexing.\n\n An ndarray supporting fancy indexing is an ndarray which supports slicing\n via indexing expressions for both retrieval and assignment.\n\n A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n any mutations to the returned ndarray will affect the underlying input\n ndarray and vice versa.\n\n A fancy ndarray supports indexing using positive and negative integers (both\n numeric literals and strings), Slice and MultiSlice instances, subsequence\n expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n A fancy ndarray supports all properties and methods of the input ndarray,\n and, thus, a fancy ndarray can be consumed by any API which supports\n ndarray-like objects.\n\n For operations returning a new ndarray (e.g., when slicing or invoking an\n instance method), a fancy ndarray returns a new fancy ndarray having the\n same configuration as specified by provided options.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n are repeated (without additional memory allocation) to match the dimensions\n of a target ndarray instance.\n\n When assigning ndarrays to slices, the ndarray on the right-hand-side must\n be broadcast-compatible with dimensions implied by the slice.\n\n Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point ndarrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy ndarrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number ndarray, a fancy\n ndarray will cast the real-valued scalar to a complex number argument having\n an imaginary component equal to zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n out: ndarray\n Output ndarray supporting fancy indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Convert to a fancy ndarray:\n > var arr = ndarray2fancy( x );\n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n Serializes an ndarray as a JSON object.\n\n This function does *not* serialize data outside of the buffer region defined\n by the ndarray view.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2json( arr )\n {...}\n\n See Also\n --------\n array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n - binary: binary.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n [...]\n > out = ndarrayDataTypes( 'floating_point' )\n [...]\n > out = ndarrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n Converts an ndarray-like object to an ndarray.\n\n If provided a read-only ndarray, the function returns a read-only ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray-like object.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarraylike2ndarray( arr )\n \n\n See Also\n --------\n array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndemptyLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v > 2.0; };\n > var y = ndfilter( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n If a provided callback function returns `undefined`, the function skips the\n respective ndarray element. If the callback function returns a value other\n than `undefined`, the function stores the callback's return value in the\n output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n > var y = ndfilterMap( x, f );\n > ndarray2array( y )\n [ 30.0, 40.0 ]\n\n See Also\n --------\n ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n Invokes a callback function once for each ndarray element.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n > ndforEach( x, f );\n\n See Also\n --------\n ndmap","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n Wraps a provided array as an ndarray index object.\n\n ndarray index instances have no explicit functionality; however, they are\n used by \"fancy\" ndarrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying ndarray are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped ndarray, as the consumer will attempt to resolve an\n instance in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n\n\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n \n\n\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}\n\n\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n \n\n\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'\n\n\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n \n\n\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true\n\n\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'\n\n\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n \n\n\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n \n\n\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n ","ndindex.get":"\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n ","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n ","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n ","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n ","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n Returns an iterator which iterates over interleaved subarrays.\n\n For input ndarrays supporting read-only views, the function returns\n *read-only* views of interleaved subarrays. As input ndarrays may be\n broadcasted, a view is typically *not* contiguous. As more than one element\n of a returned view may refer to the same memory location, writing to a view\n may affect multiple elements. If you need to write to a subarray, copy the\n subarray before attempting mutation.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n arr: ArrayLike\n Input ndarrays. All ndarrays must be broadcast-compatible. After\n broadcasting, each broadcasted input ndarray must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack after broadcasting.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n options.keepdim: boolean (optional)\n Boolean indicating whether returned views should include the selected\n dimension as a singleton dimension. Including the selected dimension as\n a singleton dimension can be useful when wanting to ensure that returned\n views remain broadcast compatible with the input ndarray. Default:\n false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSelectDimension( x, 0 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `dims.length+1` dimensions.\n\n dims: Array\n Indices of dimensions to stack. If a dimension index is less than zero,\n the index is resolved relative to the last dimension, with the last\n dimension corresponding to the value `-1`. The list of indices must be\n unique and resolve to dimension indices sorted in ascending order.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerStacks( x, [ 1, 2 ] );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSubarrays( x, 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v*10.0; };\n > var y = ndmap( x, f );\n > ndarray2array( y )\n [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v <= 2.0; };\n > var y = ndreject( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Must be a numeric data type or \"generic\". Default:\n 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n > var bool = noneInBy( obj, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, forIn, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all own properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function isUnderage( v ) { return ( v < 18 ); };\n > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n > var bool = noneOwnBy( obj, isUnderage )\n false\n\n See Also\n --------\n anyOwnBy, everyOwnBy, forOwn, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number.\n - town: town name.\n - town_id: town identifier.\n - tract: tract identifier.\n - lon: longitude.\n - lat: latitude.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - bh: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - bonferroni: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - by: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - holm: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - hommel: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path.\n - data: file contents as either a Buffer or string.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n The regular expression captures the following groups:\n\n 1. The days component.\n 2. The hours component.\n 3. The minutes component.\n 4. The seconds component.\n 5. The milliseconds component.\n\n Returns\n -------\n re: RegExp: Regular expression\n Regular expression to match a duration string.\n\n Examples\n --------\n > var RE = reDurationString();\n > var parts = RE.exec( '3d2ms' )\n [...]\n > parts = RE.exec( '4h3m20s' )\n [...]\n\n\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n \n replacement: string\n Replacement string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = replaceBefore( str, ' ', 'foo' )\n 'foo boop'\n > out = replaceBefore( str, 'o', 'foo' )\n 'foooop'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - path: a resolved path.\n - next: a callback to be invoked after processing a resolved path.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer).\n - data: buffer data as an array of integers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n - re: real component (number).\n - im: imaginary component (number).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp).\n - pattern: regular expression pattern.\n - flags: regular expression flags.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n - data: typed array data as an array of numbers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n Trims `n` characters from the end of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrimN( ' abc ', 2 )\n ' abc'\n > var out = rtrimN( '!!!abc!!!', 2, '!' )\n '!!!abc!'\n\n See Also\n --------\n ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = sdot( x, y )\n \n > z.get()\n -5.0\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","sentencize":"\nsentencize( str )\n Splits a string into an array of sentences.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of sentences.\n\n Examples\n --------\n > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello Mrs. Maple, could you call me back?' ]\n\n > out = sentencize( 'Hello World! How are you?' )\n [ 'Hello World!', 'How are you?' ]\n\n See Also\n --------\n tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - complex128: 128-bit complex numbers.\n - complex64: 64-bit complex numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection value.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object contains at least `n`\n successful properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n > var bool = someInBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object's own properties satisfy a\n predicate for at least `n` properties; otherwise, the function\n returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n > var bool = someOwnBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year.\n - name: President name.\n - party: the President's political party.\n - text: speech text.\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group).\n - group: message group.\n - checksum: object containing checksum info.\n - text: message text (including headers).\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages).\n - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n - spam-1: spam e-mails (500 messages).\n - spam-2: spam e-mails collected at a later date (1396 messages).\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5).\n - value: checksum value.\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n Interchanges two single-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.356, ~0.786 ]\n > y0\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy( 2, x, 2, y, -1, clbk )\n [ ~1.317, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.567, ~0.962 ]\n > y0\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy( 2, x, 2, y, -1, clbk )\n [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~-0.588 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy( 2, x, 2, y, -1, clbk )\n [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n [ -Infinity, ~-0.255 ]\n > y0\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 13.0, 14.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 17.0, 16.0 ]\n > z0\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n [ 0.0, ~3.142, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.094, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n [ ~3.142, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.047, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy( 2, x, 2, y, -1, clbk )\n [ ~1.571, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.253, ~-0.524 ]\n > y0\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy( 2, x, 2, y, -1, clbk )\n [ ~1.444, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-1.444, 0.0 ]\n > y0\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy( 2, x, 2, y, -1, clbk )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.896, ~-0.464 ]\n > y0\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy( 2, x, 2, y, -1, clbk )\n [ Infinity, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.255, ~-0.549 ]\n > y0\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By( 2, x, 2, y, -1, clbk )\n [ ~0.998, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n [ ~0.984, ~0.765 ]\n > y0\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By( 2, x, 2, y, -1, clbk )\n [ ~0.05, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n [ ~0.124, ~0.44 ]\n > y0\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By( 2, x, 2, y, -1, clbk )\n [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n [ ~-0.932, ~0.088 ]\n > y0\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By( 2, x, 2, y, -1, clbk )\n [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n [ ~-2.704, ~-0.781 ]\n > y0\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy( 2, x, 2, y, -1, clbk )\n [ 1.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n [ 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy( 2, x, 2, y, -1, clbk )\n [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.839, ~-1.0 ]\n > y0\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - bool: boolean values.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 12.0, 33.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 52.0, 28.0 ]\n > z0\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy( 2, x, 2, y, -1, clbk )\n [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.544, ~0.002 ]\n > y0\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n [ ~11.045, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~7.071, 1.0 ]\n > y0\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 4.0, 5.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 8.0, 7.0 ]\n > z0\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - result: function result.\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object.\n - result: either the result of `x` or the provided argument `y`.\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`.\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > var arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n - BooleanArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type.\n - data: typed array data as a generic array.\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n \n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n \n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n ","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n ","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n WebAssembly memory constructor.\n\n Parameters\n ----------\n descriptor: Object\n Memory descriptor object.\n\n descriptor.initial: integer\n Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.maximum: integer (optional)\n Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.shared: boolean (optional)\n Boolean indicating whether the memory is shared. Default: false.\n\n Returns\n -------\n out: Memory\n WebAssembly memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n \n\n\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n \n\n\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n \n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n ","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n ","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} +{"abs":"\nabs( x[, options] )\n Computes the absolute value.\n\n If provided a number, the function returns a number.\n\n If provided an ndarray or array-like object, the function performs element-\n wise computation.\n\n If provided an array-like object, the function returns an array-like object\n having the same length and data type as `x`.\n\n If provided an ndarray, the function returns an ndarray having the same\n shape and data type as `x`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject|number\n Input value.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Output array order (either row-major (C-style) or column-major (Fortran-\n style)). Only applicable when the input array is an ndarray. By default,\n the output array order is inferred from the input array.\n\n options.dtype: string (optional)\n Output array data type. Only applicable when the input array is either\n an ndarray or array-like object. By default, the output array data type\n is inferred from the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject|number\n Results.\n\n Examples\n --------\n // Provide a number:\n > var y = abs( -1.0 )\n 1.0\n\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n > x = [ -1.0, -2.0 ];\n > y = abs( x )\n [ 1.0, 2.0 ]\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = abs( x )\n \n > y.get( 0, 1 )\n 2.0\n\n\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value and assigns results to a provided output array.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n Input array.\n\n y: ndarray|ArrayLikeObject\n Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n object) as the input array.\n\n Returns\n -------\n y: ndarray|ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Provide an array-like object:\n > var x = new Float64Array( [ -1.0, -2.0 ] );\n > var y = new Float64Array( x.length );\n > var out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > var bool = ( out === y )\n true\n\n > x = [ -1.0, -2.0 ];\n > y = [ 0.0, 0.0 ];\n > out = abs.assign( x, y )\n [ 1.0, 2.0 ]\n > bool = ( out === y )\n true\n\n // Provide an ndarray:\n > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n > out = abs.assign( x, y )\n \n > out.get( 0, 1 )\n 2.0\n > bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of falsy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of falsy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is falsy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of falsy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of falsy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of falsy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: the value of the current property being processed in the object\n - key: the key of the current property being processed in the object\n - object: the input object\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate. It must be non-null.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any value; otherwise, it returns `false`.\n\n Examples\n --------\n > function isNegative(value) { return value < 0 }\n > var obj = { a: 1, b: -2, c: 3, d: 4 }\n > var result = anyInBy(obj, isNegative)\n true\n\n See Also\n --------\n anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return\n value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for one own property; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n > var bool = anyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of truthy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of truthy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is truthy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of truthy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of truthy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of truthy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","aput":"\naput( x, indices, values[, options] )\n Replaces specified elements of an array with provided values.\n\n The function supports broadcasting a `values` array containing a single\n element against an `indices` array containing one or more elements.\n\n The function mutates the input array.\n\n Because each index is only validated at the time of replacing a particular\n element, mutation may occur even when one or more indices are out-of-bounds,\n including when the index mode indicates to raise an exception.\n\n If `indices` is an empty array, the function returns the input array\n unchanged.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n values: ArrayLikeObject\n Values to set. When `indices` contains one or more elements, `values`\n must be broadcast compatible with `indices` (i.e., must have either one\n element or the same number of elements as `indices`).\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aplace, atake\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: \"typed\" data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n \n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n \n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n ","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n ","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = base.acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianSquare( x )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosd( 0.0 )\n 90.0\n > y = base.acosd( PI/6.0 )\n ~58.43\n > y = base.acosd( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asind, base.atand\n","base.acosf":"\nbase.acosf( x )\n Computes the arccosine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosf( 1.0 )\n 0.0\n > y = base.acosf( 0.707 )\n ~0.7855\n > y = base.acosf( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotd( 0.0 )\n 90.0\n > y = base.acotd( PI/6.0 )\n ~62.36\n > y = base.acotd( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atand, base.cotd\n","base.acotf":"\nbase.acotf( x )\n Computes the inverse cotangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acotf( 2.0 )\n ~0.4636\n > y = base.acotf( 0.0 )\n ~1.5708\n > y = base.acotf( 0.5 )\n ~1.1071\n > y = base.acotf( 1.0 )\n ~0.7854\n > y = base.acotf( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscd( 0.0 )\n NaN\n > y = base.acscd( PI/6.0 )\n NaN\n > y = base.acscd( 1 )\n 90.0\n > y = base.acscd( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscdf( 0.0 )\n NaN\n > y = base.acscdf( 3.1415927410125732 / 6.0 )\n NaN\n > y = base.acscdf( 1.0 )\n 90.0\n > y = base.acscdf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n Computes the arccosecant of a single-precision floating-point number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acscf( 1.0 )\n ~1.57\n > y = base.acscf( 3.141592653589793 )\n ~0.32\n > y = base.acscf( -3.141592653589793 )\n ~-0.32\n > y = base.acscf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n Returns a filled \"generic\" array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled( 0.0, 3 )\n [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n Returns a filled two-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n Returns a filled three-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n Returns a filled four-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n Returns a filled five-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n Returns a filled \"generic\" array according to a provided callback function.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledBy( 3, clbk )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n Returns a filled n-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afillednd( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledndBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the input array.\n\n If provided an array-like object having a `filter` method , the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.filter( predicate, thisArg )\n\n If provided an array-like object without a `filter` method, the function\n performs a linear scan and always returns a generic array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > function f( v ) { return ( v > 0 ); };\n > var x = [ 1, -2, -3, 4 ];\n > var out = base.afilter( x, f )\n [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n Returns the first element of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: any\n First element.\n\n Examples\n --------\n > var out = base.afirst( [ 1, 2, 3 ] )\n 1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n Flattens an n-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n Flattens a two-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2d( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten2d( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n Flattens a three-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n Flattens a four-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n Flattens a five-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 2, 1 ], [ 4, 3 ] ]\n\n See Also\n --------\n base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 3, 4 ], [ 1, 2 ] ]\n\n See Also\n --------\n base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n Converts a string to alternate case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Alternate-cased string.\n\n Examples\n --------\n > var out = base.altcase( 'Hello World!' )\n 'hElLo wOrLd!'\n > out = base.altcase( 'I am a tiny little teapot' )\n 'i aM A TiNy lItTlE TeApOt'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n Returns a \"generic\" array filled with ones.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones( 3 )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n Returns a two-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones2d( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n Returns a three-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones3d( [ 1, 1, 3 ] )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n Returns a four-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n Returns a five-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n Returns an n-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aonesnd( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.aoneTo( 6 )\n [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n Parameters\n ----------\n args: Array\n Constructor arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var args = [ null, null, null ];\n > var s = new base.args2multislice( args );\n > s.data\n [ null, null, null ]\n > args = [ 10, new Slice( 0, 10, 1 ), null ];\n > s = new base.args2multislice( args );\n > s.data\n [ 10, , null ]\n\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecd( 0.0 )\n NaN\n > y = base.asecd( 2 )\n ~60.0\n > y = base.asecd( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecdf( 2.0 )\n ~60.0\n > y = base.asecdf( 0.0 )\n NaN\n > y = base.asecdf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech\n","base.asecf":"\nbase.asecf( x )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asecf( 1.0 )\n 0.0\n > y = base.asecf( 2.0 )\n ~1.0472\n > y = base.asecf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asind( 0.0 )\n 0.0\n > y = base.asind( PI / 6.0 )\n ~31.57\n > y = base.asind( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asindf( 0.0 )\n 0.0\n > y = base.asindf( 3.1415927410125732 / 6.0 )\n ~31.57\n > y = base.asindf( NaN )\n NaN\n\n See Also\n --------\n base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n Computes the arcsine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinf( 0.0 )\n 0.0\n > y = base.asinf( -3.14/6.0 )\n ~-0.551\n > y = base.asinf( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atand":"\nbase.atand( x )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in degrees).\n\n Examples\n --------\n > var y = base.atand( 0.0 )\n 0.0\n > y = base.atand( PI/6.0 )\n ~27.64\n > y = base.atand( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n Computes the arctangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanf( 0.0 )\n 0.0\n > y = base.atanf( -3.14/4.0 )\n ~-0.666\n > y = base.atanf( 3.14/4.0 )\n ~0.666\n > y = base.atanf( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n Returns a zero-filled \"generic\" array.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros( 3 )\n [ 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n Returns a zero-filled two-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros2d( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n Returns a zero-filled three-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros3d( [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n See Also\n --------\n base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n Returns a zero-filled four-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n Returns a zero-filled five-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n Returns a zero-filled n-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azerosnd( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.azeroTo( 6 )\n [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.5\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.camelcase":"\nbase.camelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = base.camelcase( 'Hello World!' )\n 'helloWorld'\n > out = base.camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = base.capitalize( 'beep' )\n 'Beep'\n > out = base.capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n \n > var re = real( v )\n -1.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n \n > var re = realf( v )\n -1.0\n > var im = imagf( v )\n 3.0\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( out )\n 5.56\n > var im = imag( out )\n -3.33\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5, 10 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1, 10 )\n 4.0\n > y = base.ceilsd( 12368.0, 2, 10 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n \n > var re = real( y )\n 1.0\n > var im = imag( y )\n 0.0\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n \n > re = real( y )\n ~0.540\n > im = imag( y )\n ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 5.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n \n > var re = real( v )\n 5.55\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = realf( v )\n -1.0\n > var img = imagf( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n \n > var re = real( v )\n 0.1\n > var im = imag( v )\n -0.2\n\n See Also\n --------\n base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmul.assign":"\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmul.strided":"\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean\n Backward iteration for low surrogates.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = base.codePointAt( 'last man standing', 4, false )\n 32\n > out = base.codePointAt( 'presidential election', 8, true )\n 116\n > out = base.codePointAt( 'अनुच्छेद', 2, false )\n 2369\n > out = base.codePointAt( '🌷', 1, true )\n 127799\n","base.constantcase":"\nbase.constantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = base.constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = base.constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n Computes the cosine of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cosd( 0.0 )\n 1.0\n > y = base.cosd( 90.0 )\n 0.0\n > y = base.cosd( 60.0 )\n ~0.5\n > y = base.cosd( NaN )\n NaN\n\n See Also\n --------\n base.tand\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n Computes the cotangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cotd( 0.0 )\n Infinity\n > y = base.cotd( 90.0 )\n 0.0\n > y = base.cotd( 60.0 )\n ~0.58\n > y = base.cotd( NaN )\n NaN\n\n See Also\n --------\n base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n \n > var re = real( v )\n 6.0\n > var im = imag( v )\n 3.0\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n \n > var re = real( v )\n 5.56\n > var im = imag( v )\n -3.34\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n Computes the cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.csc( 0.0 )\n Infinity\n > y = base.csc( PI/2.0 )\n ~1.0\n > y = base.csc( -PI/6.0 )\n ~-2.0\n > y = base.csc( NaN )\n NaN\n\n See Also\n --------\n base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n Computes the cosecant of a degree.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.cscd( 1.0 )\n ~57.30\n > y = base.cscd( PI )\n ~18.25\n > y = base.cscd( -PI )\n ~-18.25\n > y = base.cscd( NaN )\n NaN\n\n See Also\n --------\n base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n \n > var re = real( v )\n -0.6069136033622302\n > var im = imag( v )\n 0.79476781392673\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = base.dotcase( 'Hello World!' )\n 'hello.world'\n > out = base.dotcase( 'I am a tiny little teapot' )\n 'i.am.a.tiny.little.teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n Returns the entropy of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.entropy( 0, 1 )\n ~0.693\n > v = base.dists.discreteUniform.entropy( 4, 12 )\n ~2.197\n > v = base.dists.discreteUniform.entropy( 2, 8 )\n ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n Evaluates the quantile function for a studentized range distribution.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = quantile( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = quantile( 0.9, 17.0, 2.0 )\n ~0.913\n\n > y = quantile( 0.5, 3.0, 2.0, 2 )\n ~0.01\n\n > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n NaN\n > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.t.logcdf( 2.0, 0.1 )\n ~-0.493\n > y = base.dists.t.logcdf( 1.0, 2.0 )\n ~-0.237\n > y = base.dists.t.logcdf( -1.0, 4.0 )\n ~-1.677\n > y = base.dists.t.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.logcdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.t.logpdf( 0.3, 4.0 )\n ~-1.036\n > y = base.dists.t.logpdf( 2.0, 0.7 )\n ~-2.841\n > y = base.dists.t.logpdf( -1.0, 0.5 )\n ~-2.134\n > y = base.dists.t.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logpdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, and is thus\n equivalent to `str.length + len`. Default: str.length.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = base.endsWith( 'beep', 'ep', 4 )\n true\n > bool = base.endsWith( 'Beep', 'op', 4 )\n false\n > bool = base.endsWith( 'Beep', 'ee', 3 )\n true\n > bool = base.endsWith( 'Beep', 'ee', -1 )\n true\n > bool = base.endsWith( 'beep', '', 4 )\n true\n\n See Also\n --------\n base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.floorsd( 3.14159, 1, 10 )\n 3.0\n > y = base.floorsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePointRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster.\n - index: starting grapheme cluster index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n Function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n Generate string from a token array by interpolating values.\n\n Parameters\n ----------\n tokens: Array\n Array of string parts and format identifier objects.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n 'beep boop'\n > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n 'baz 1.00'\n > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n ' 12'\n\n See Also\n --------\n base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n Tokenize a string into an array of string parts and format identifier\n objects.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of string parts and format identifier objects.\n\n Examples\n --------\n > var out = base.formatTokenize( 'Hello %s!' )\n [ 'Hello ', {...}, '!' ]\n > out = base.formatTokenize( '%s %s %d' )\n [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n > out = base.formatTokenize( 'Pi: %.2f' )\n [ 'Pi: ', {...} ]\n\n See Also\n --------\n base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n Computes the sign of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Sign of the gamma function.\n\n Examples\n --------\n > var y = base.gammasgn( 1.0 )\n 1.0\n > y = base.gammasgn( -2.5 )\n -1.0\n > y = base.gammasgn( 0.0 )\n 0.0\n > y = base.gammasgn( NaN )\n NaN\n\n See Also\n --------\n base.gamma","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First number.\n\n b: integer\n Second number.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = base.headercase( 'Hello World!' )\n 'Hello-World'\n > out = base.headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n Converts an integer to a Slice object.\n\n In strict mode, the function returns an error object if an input value\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n max: integer\n Index upper bound (exclusive).\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s = base.int2slice( -1, 5, false );\n > s.start\n 4\n > s.stop\n 5\n > s.step\n 1\n\n See Also\n --------\n base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invcase":"\nbase.invcase( str )\n Converts a string to inverse case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Inverse-cased string.\n\n Examples\n --------\n > var out = base.invcase( 'Hello World!' )\n 'hELLO wORLD!'\n > out = base.invcase( 'I am A tiny LITTLE teapot' )\n 'i AM a TINY little TEAPOT'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a negative finite number.\n\n Examples\n --------\n > var bool = base.isNegativeFinite( -3.14 )\n true\n > bool = base.isNegativeFinite( -Infinity )\n false\n > bool = base.isNegativeFinite( 2.0 )\n false\n > bool = base.isNegativeFinite( NaN )\n false\n > bool = base.isNegativeFinite( -0.0 )\n false\n\n See Also\n --------\n base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative finite number.\n\n Examples\n --------\n > var out = base.isNonNegativeFinite( 5.0 )\n true\n > out = base.isNonNegativeFinite( 3.14 )\n true\n > out = base.isNonNegativeFinite( 0.0 )\n true\n > out = base.isNonNegativeFinite( Infinity )\n false\n > out = base.isNonNegativeFinite( -3.14 )\n false\n > out = base.isNonNegativeFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = base.isNonPositiveFinite( -3.14 )\n true\n > var bool = base.isNonPositiveFinite( 0.0 )\n true\n > var bool = base.isNonPositiveFinite( -Infinity )\n false\n > var bool = base.isNonPositiveFinite( 3.14 )\n false\n > var bool = base.isNonPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive finite number.\n\n Examples\n --------\n > var bool = base.isPositiveFinite( 5.0 )\n true\n > bool = base.isPositiveFinite( 3.14 )\n true\n > bool = base.isPositiveFinite( 0.0 )\n false\n > bool = base.isPositiveFinite( Infinity )\n false\n > bool = base.isPositiveFinite( -3.14 )\n false\n > bool = base.isPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = base.kebabcase( 'Hello World!' )\n 'hello-world'\n > out = base.kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n\n This function provides a common means for computing logarithms in base e.\n Argument reduction and adding the final term of the polynomial must be done\n by the caller for increased accuracy when different bases are used.\n\n Parameters\n ----------\n f: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var y = base.kernelLog1p( 1.0 )\n ~0.1931\n > y = base.kernelLog1p( 1.4142135623730951 )\n ~0.4672\n > y = base.kernelLog1p( NaN )\n NaN\n\n See Also\n --------\n base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.last":"\nbase.last( str, n )\n Returns the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.last( 'hello', 1 )\n 'o'\n > out = base.last( 'JavaScript', 6 )\n 'Script'\n > out = base.last( 'foo bar', 10 )\n 'foo bar'\n\n See Also\n --------\n base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n Returns the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastCodePoint( 'hello world', 1 )\n 'd'\n > out = base.lastCodePoint( 'JavaScript', 6 )\n 'Script'\n > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n 'द'\n\n See Also\n --------\n base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastGraphemeCluster( 'beep', 1 )\n 'p'\n > out = base.lastGraphemeCluster( 'Boop', 2 )\n 'op'\n > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n 'Script'\n\n See Also\n --------\n base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.leftPad( 'a', 5, ' ' )\n ' a'\n > out = base.leftPad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = base.leftPad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of a double-precision floating-point number.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = base.lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabsn( 3.14, -4.2 )\n 4.2\n > v = base.maxabsn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabsn( 3.14, NaN )\n NaN\n > v = base.maxabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabsn( 3.14, -4.2 )\n 3.14\n > v = base.minabsn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabsn( 3.14, NaN )\n NaN\n > v = base.minabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for both the minimum and\n maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabsn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabsn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabsn( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabsn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for the minimum value and\n negative infinity for the maximum value.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmaxn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxn( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxn( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmaxn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an object with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string\n Underlying data type. Must be a numeric data type or \"generic\".\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = base.ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n Returns a normalized Slice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: Slice\n Input slice object.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s1 = new Slice( 1, 10, 1 );\n > var s2 = base.normalizeSlice( s1, 5, false );\n > s2.start\n 1\n > s2.stop\n 5\n > s2.step\n 1\n > s1 = new Slice( -2, null, -1 );\n > s2 = base.normalizeSlice( s1, 10, false );\n > s2.start\n 8\n > s2.stop\n null\n > s2.step\n -1\n\n See Also\n --------\n base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = base.pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = base.pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = base.percentEncode( '☃' )\n '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n Converts an angle from radians to degrees (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n 90.0\n > d = base.rad2degf( -3.141592653589793 / 4.0 )\n -45.0\n > d = base.rad2degf( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2degf( 3.141592653589793 / 6.0 )\n 30.000001907348633\n\n See Also\n --------\n base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrt( 8.0 )\n 0.5\n > y = base.rcbrt( 1000.0 )\n 0.1\n > y = base.rcbrt( 0.0 )\n Infinity\n > y = base.rcbrt( PINF )\n 0.0\n > y = base.rcbrt( -8.0 )\n -0.5\n > y = base.rcbrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrtf( 8.0 )\n 0.5\n > y = base.rcbrtf( 1000.0 )\n ~0.1\n > y = base.rcbrtf( 0.0 )\n Infinity\n > y = base.rcbrtf( PINF )\n 0.0\n > y = base.rcbrtf( -8.0 )\n -0.5\n > y = base.rcbrtf( NaN )\n NaN\n\n See Also\n --------\n base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n Removes the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirst( 'beep', 1 )\n 'eep'\n > out = base.removeFirst( 'Boop', 1 )\n 'oop'\n > out = base.removeFirst( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n Removes the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstCodePoint( 'beep', 1 )\n 'eep'\n > out = base.removeFirstCodePoint( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstCodePoint( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n 'eep'\n > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n Removes the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLast( 'beep', 1 )\n 'bee'\n > out = base.removeLast( 'Boop', 1 )\n 'Boo'\n > out = base.removeLast( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n Removes the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastCodePoint( 'beep', 1 )\n 'bee'\n > out = base.removeLastCodePoint( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastCodePoint( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n 'bee'\n > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = base.repeat( 'a', 5 )\n 'aaaaa'\n > out = base.repeat( '', 100 )\n ''\n > out = base.repeat( 'beep', 0 )\n ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = base.replace( 'beep', /e/, 'o' )\n 'boep'\n\n See Also\n --------\n base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n Replaces the substring after the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n 'beep foo'\n > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n 'beep bofoo'\n > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n 'Hello Wofoo'\n > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n 'beep boop beepfoo'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n Replaces the substring after the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n 'beep foo'\n > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n 'beep boofoo'\n > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n 'Hellofoo'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n Replaces the substring before the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n 'foo boop'\n > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n 'foooop'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n Replaces the substring before the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n 'foo boop'\n > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n 'fooop'\n > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n 'fooo World!'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n Reverses the UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverse( 'beep' )\n 'peeb'\n > out = base.reverse( 'Boop' )\n 'pooB'\n > out = base.reverse( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n Reverses the Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseCodePoints( 'beep' )\n 'peeb'\n > out = base.reverseCodePoints( 'Boop' )\n 'pooB'\n > out = base.reverseCodePoints( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseGraphemeClusters( 'beep' )\n 'peeb'\n > out = base.reverseGraphemeClusters( 'Boop' )\n 'pooB'\n > out = base.reverseGraphemeClusters( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n Right pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.rightPad( 'a', 5, ' ' )\n 'a '\n > out = base.rightPad( 'beep', 10, 'b' )\n 'beepbbbbbb'\n > out = base.rightPad( 'boop', 12, 'beep' )\n 'boopbeepbeep'\n\n See Also\n --------\n base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string containing constructor arguments.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.sargs2multislice( 'null,null,null' );\n > s.data\n [ null, null, null ]\n > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n Computes the secant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Secant.\n\n Examples\n --------\n > var y = base.secd( 1.0 )\n ~1.0\n > y = base.secd( PI )\n ~1.0\n > y = base.secd( -PI )\n ~1.0\n > y = base.secd( NaN )\n NaN\n\n See Also\n --------\n base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n Converts a multidimensional subsequence string to a MultiSlice object.\n\n A multidimensional subsequence string is a comma-separated list of single-\n dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n For example, the following\n\n 2\n :\n 2:\n :10\n 2:10\n ::-1\n 10:2:-1\n :2:\n 2:10:\n 2::2\n :10:2\n :, :, :\n 1, 2, 3\n 0:10, 1:20:2, ::-1\n ...\n :, ..., 2\n\n are all valid multidimensional subsequence strings.\n\n Providing a single nonnegative integer `i` as a single-dimension index\n indexes the same elements as the subsequence `i:i+1`.\n\n Providing a single negative integer `i` as a single-dimension index indexes\n the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n size.\n\n While integers index the same elements as equivalent subsequences, providing\n an integer as a single-dimension index indicates to reduce the number of\n dimensions by one (e.g., if the provided shape corresponds to an array\n having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n In contrast, providing a subsequence indicates to retain a respective\n dimension (e.g., if the provided shape corresponds to an array having rank\n 2, then rank(A) == rank(A[':,:'])).\n\n A multidimensional subsequence string can only contain **one** ellipsis\n ('...') operator. An ellipsis indicates to apply ':' to each dimension\n necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n equals A['1:,:,:,2:5']).\n\n Except in the case of providing a single ellipsis, the number of single-\n dimension indexing expressions must equal the number of dimensions in the\n input shape.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if a single-dimension\n index expression which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n than the provided shape.\n - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n dimensions.\n - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n one ellipsis.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n shape: Array\n Maximum allowed slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n > s.data\n [ ]\n > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n > s.data\n [ 4, , ]\n\n See Also\n --------\n base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if provided a\n subsequence string which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n Converts a Slice object to a subsequence string.\n\n Parameters\n ----------\n slice: Slice\n Input slice.\n\n Returns\n -------\n out: string\n Subsequence string.\n\n Examples\n --------\n > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n '1:10:1'\n > out = base.slice2seq( new Slice( null, 10 ) )\n ':10'\n\n See Also\n --------\n base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n Returns the number of elements in a normalized slice.\n\n Parameters\n ----------\n slice: Slice\n Input normalized slice object.\n\n Returns\n -------\n len: integer\n Number of elements.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > base.sliceLength( s )\n 9\n\n See Also\n --------\n base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceNonReducedDimensions( s )\n [ 2 ]\n\n See Also\n --------\n base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceReducedDimensions( s )\n [ 0, 1 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n Returns the shape of a normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input normalized multi-slice object.\n\n Returns\n -------\n sh: Array\n Slice shape.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > var ms = new MultiSlice( s, s );\n > base.sliceShape( ms )\n [ 9, 9 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = base.snakecase( 'Hello World!' )\n 'hello_world'\n > out = base.snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n Evaluates Spence's function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.startcase":"\nbase.startcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = base.startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = base.startsWith( 'Beep', 'Be', 0 )\n true\n > bool = base.startsWith( 'Beep', 'ep', 0 )\n false\n > bool = base.startsWith( 'Beep', 'ee', 1 )\n true\n > bool = base.startsWith( 'Beep', 'ee', -3 )\n true\n > bool = base.startsWith( 'Beep', '', 0 )\n true\n\n See Also\n --------\n base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n\n Parameters\n ----------\n str: string\n Input string.\n \n p: number\n Probability of capitalization.\n\n Returns\n -------\n out: string\n Sticky-cased string.\n\n Examples\n --------\n > var out = base.stickycase( 'Hello World!' )\n \n\n > out = base.stickycase( 'I am a tiny little teapot' )\n \n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imagf( z )\n 6.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imagf( z )\n 8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two complex single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > z = y.get( 0 );\n > re = realf( z )\n 5.0\n > im = imagf( z )\n 6.0\n > z = x.get( 0 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > z = y0.get( 2 );\n > re = realf( z )\n 7.0\n > im = imagf( z )\n 8.0\n > z = x0.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > var z = y.get( 0 );\n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 2.0\n > z = x.get( 0 );\n > re = realf( z )\n 6.0\n > im = imagf( z )\n 7.0\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > z = y.get( y.length-1 );\n > re = realf( z )\n 3.0\n > im = imagf( z )\n 4.0\n > z = x.get( 1 );\n > re = realf( z )\n 0.0\n > im = imagf( z )\n 0.0\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax( N, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumax( N, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin( N, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cumin( N, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs( N, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.strided.cuminabs( N, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in\n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.dasumpw( 3, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.dasumpw( 3, x1, stride )\n 5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, strideX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > var N = base.floor( x.length / 2 );\n > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Index increment for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasum( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanasumors( N, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanasumors( N, x1, stride )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanpw( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpw( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for the strided array.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for the strided array.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dnanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsem( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsem( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemch( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemch( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsempn( N, 1, x, stride )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsempn( N, 1, x1, stride )\n ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemtk( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemtk( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemwd( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemwd( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemyc( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemyc( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed.\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsnanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsnanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1.0, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevyc( 3, 1.0, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevyc( 3, 1.0, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dsvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dsvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n\n Parameters\n ----------\n dtype: integer\n Data type enumeration constant.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveEnum( 'float64' )\n \n > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n \n\n See Also\n --------\n base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n Returns the data type string associated with a supported data type value.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveStr( 'float64' )\n 'float64'\n > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.dvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmtk( 3, 1.0/3.0, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmtk( 3, 1.0/3.0, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mean: number\n Mean.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1.0/3.0, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( 4, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.gasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, strideX )\n Fills a strided array with a specified scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, strideX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: current array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( 3, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfillBy( 3, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, strideX )\n Reverses a strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.grev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n Multiplies a vector `x` by a constant `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var alpha = 5.0;\n > base.strided.gscal( x.length, alpha, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n Sorts a strided array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsorthp( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n Sorts a strided array using insertion sort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortins( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n Sorts a strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.gsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n Computes the sum of strided array elements.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.gsum( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.gsum( N, x1, stride )\n -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.gsum.ndarray( N, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, strideX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, strideX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, strideX )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, strideX )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n Computes the maximum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.max( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.max( N, x1, stride )\n 2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.max.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n Computes the maximum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxabs( N, x1, stride )\n 2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.maxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.maxsorted( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.maxsorted( N, x1, stride )\n 3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n 14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n Computes the arithmetic mean of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.mean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.mean( N, x1, stride )\n ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.meanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.meanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted( N, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mediansorted( N, x1, 2 )\n 2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, stride )\n Computes the minimum value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.min( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.min( N, x1, stride )\n -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.min.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n Computes the minimum absolute value of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minabs( N, x1, stride )\n 1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.minBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.minsorted( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.minsorted( N, x1, stride )\n -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.minsorted.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n 6\n\n See Also\n --------\n base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.mskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmax( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmax( N, x1, stride )\n 2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmaxabs( N, x, stride )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmaxabs( N, x1, stride )\n 2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy( N, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmaxBy( N, x1, 2, accessor )\n -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanmin( N, x, stride )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanmin( N, x1, stride )\n -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmin.ndarray( N, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanminabs( N, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanminabs( N, x1, stride )\n 1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy( N, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanminBy( N, x1, 2, accessor )\n -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanrange( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanrange( N, x1, stride )\n 4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrange.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy( N, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanrangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdev( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevch( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevpn( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevtk( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevwd( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc( N, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.nanstdevyc( N, 1, x1, 2 )\n ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.nanvarianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.nanvarianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n\n Parameters\n ----------\n x: TypedArray\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: TypedArray\n Typed array view having the same data type as the input array.\n\n Examples\n --------\n > var x = new Float64Array( 10 );\n > var out = base.strided.offsetView( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n Computes the range of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.range( N, x, stride )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.range( N, x1, stride )\n 4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.range.ndarray( N, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy( N, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.rangeBy( N, x1, 2, accessor )\n 8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n\n Parameters\n ----------\n x: Complex128Array|Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Real-valued floating-point array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n > x = new Complex64Array( 10 );\n > out = base.strided.reinterpretComplex( x, 0 )\n \n > bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n Returns a Float32Array view of a Complex64Array.\n\n Parameters\n ----------\n x: Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex64Array.\n\n Returns\n -------\n out: Float32Array\n Float32Array view.\n\n Examples\n --------\n > var x = new Complex64Array( 10 );\n > var out = base.strided.reinterpretComplex64( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n Returns a Float64Array view of a Complex128Array.\n\n Parameters\n ----------\n x: Complex128Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex128Array.\n\n Returns\n -------\n out: Float64Array\n Float64Array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex128( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array\n elements, ignore `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in the\n strided array are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.sdsnansum( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sdsnansum( 4, x1, stride )\n -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and stride parameters determine which elements in \n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sdssum( 3, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sdssum( 3, x1, stride )\n -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset,\n use a typed array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.sdssumpw( 3, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.sdssumpw( 3, x1, stride )\n -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smean( N, x1, stride )\n ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeankbn2( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeankbn2( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanlipw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanlipw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.smeanpw( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.smeanpw( N, x1, stride )\n ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, strideX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanors( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanors( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanpn( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanpn( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanmeanwd( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanmeanwd( N, x1, stride )\n ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax( N, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n 2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin( N, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange( N, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n 4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided \n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, \n use a typed array view. \n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumkbn( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumkbn( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset,\n use a typed array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumkbn2( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumkbn2( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumors( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumors( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves the strided arrays\n are unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided\n array unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n Returns\n -------\n x: Float32Array\n Input array the strided array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for the strided array.\n\n offset: integer\n Starting index of the strided array.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n Computes the standard deviation of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.stdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.stdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.svariancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.svariancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n Computes the variance of a strided array.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variance( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variance( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancech( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancech( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancepn( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancepn( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancetk( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancetk( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.variancewd( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.variancewd( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.varianceyc( N, 1, x, stride )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.varianceyc( N, 1, x1, stride )\n ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n > v = y.get( 0 )\n \n > re = real( v )\n 5.0\n > im = imag( v )\n 6.0\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n > v = y1.get( 0 )\n \n > re = real( v )\n 7.0\n > im = imag( v )\n 8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n > var v = y.get( 0 )\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n 2.0\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n > v = y.get( y.length-1 )\n \n > re = real( v )\n 3.0\n > im = imag( v )\n 4.0\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n Parses a string-serialized MultiSlice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n > s.data\n [ null, null, null ]\n > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n Parses a string-serialized Slice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: Slice|null\n Slice instance (or null).\n\n Examples\n --------\n > var s = new base.str2slice( 'Slice(1,10,1)' );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.str2slice( 'Slice(2,5,2)' );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n Computes the tangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tand( 0.0 )\n 0.0\n > y = base.tand( 90.0 )\n Infinity\n > y = base.tand( 60.0 )\n ~1.73\n > y = base.tand( NaN )\n NaN\n\n See Also\n --------\n base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n While powerful, this can lead to subtle bugs. In general, one should handle\n the returned ndarray as read-only.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n \n > var sh = x.shape\n [ 2, 3 ]\n > var y = base.transpose( x )\n \n > sh = y.shape\n [ 3, 2 ]\n > var bool = ( x.data === y.data )\n true\n > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n true\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string\n Custom replacement sequence.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.truncateMiddle( str, 5, '...' )\n 'b...p'\n > out = base.truncateMiddle( str, 5, '|' )\n 'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.truncsd( 3.14159, 1, 10 )\n 3.0\n > y = base.truncsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.umul":"\nbase.umul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = base.uncapitalize( 'Beep' )\n 'beep'\n > out = base.uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = base.uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n base.lowercase\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray()\n \n\n\nBooleanArray( length )\n Creates a boolean array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray( booleanarray )\n Creates a boolean array from another boolean array.\n\n Parameters\n ----------\n booleanarray: BooleanArray\n Boolean array from which to generate another boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var arr2 = new BooleanArray( arr1 )\n \n > var len = arr2.length\n 4\n\n\nBooleanArray( typedarray )\n Creates a boolean array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n \n > var arr = new BooleanArray( buf )\n \n > var len = arr.length\n 4\n\n\nBooleanArray( obj )\n Creates a boolean array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var len = arr1.length\n 4\n > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n > len = arr2.length\n 4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n Returns a boolean array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new BooleanArray( buf )\n \n > var len = arr1.length\n 240\n > var arr2 = new BooleanArray( buf, 8 )\n \n > len = arr2.length\n 232\n > var arr3 = new BooleanArray( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n \n\n\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1\n\n\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'\n\n\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false\n\n\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'\n\n\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: boolean\n Element value. \n\n Returns\n -------\n out: BooleanArray\n New typed array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n ","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n \n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: boolean\n Element value. \n\n Returns\n -------\n out: BooleanArray\n New typed array.\n \n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Array\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary.\n - phones: manners of articulation for each sound.\n - symbols: complete list of ARPABET symbols used by the dictionary.\n - vp: verbal pronunciations of punctuation marks.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array()\n \n\n\nComplex64Array( length )\n Creates a 64-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex64Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex64Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex64Array( typedarray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex64Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex64Array( obj )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n > var arr2 = new Complex64Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new Complex64Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex64Array( buf, 8 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex64Array( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80\n\n\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0\n\n\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex64Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n ","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = realf( v[ 1 ] )\n 1.0\n > var im = imagf( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = realf( v[ 1 ] )\n 2.0\n > im = imagf( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = realf( v[ 1 ] )\n 3.0\n > im = imagf( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n 1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n 2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 2.0\n > var im = imagf( z )\n -2.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n 3.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n 2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 1.0\n > im = imagf( z )\n 1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = realf( z )\n 1.0\n > var im = imagf( z )\n -1.0\n > z = out.get( 1 )\n \n > re = realf( z )\n 2.0\n > im = imagf( z )\n -2.0\n > z = out.get( 2 )\n \n > re = realf( z )\n 3.0\n > im = imagf( z )\n -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = realf( v )\n 1.0\n > var im = imagf( v )\n -1.0\n > v = it.next().value\n \n > re = realf( v )\n 2.0\n > im = imagf( v )\n -2.0\n > var bool = it.next().done\n true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex64\n Element value. \n\n Returns\n -------\n out: Complex64Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = realf( z )\n 3.0\n > var im = imagf( z )\n -3.0\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n \n Returns\n -------\n out: Complex128Array\n A typed array.\n \n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n ","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n \n start: integer\n Source start index position.\n \n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, ]\n > var re = real( v[ 1 ] )\n 1.0\n > var im = imag( v[ 1 ] )\n -1.0\n > v = it.next().value\n [ 1, ]\n > re = real( v[ 1 ] )\n 2.0\n > im = imag( v[ 1 ] )\n -2.0\n > v = it.next().value\n [ 2, ]\n > re = real( v[ 1 ] )\n 3.0\n > im = imag( v[ 1 ] )\n -3.0\n > var bool = it.next().done\n true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n 1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context. \n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n 2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n \n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n \n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n \n Returns\n -------\n out: string\n Array serialized as a string.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n \n Returns\n -------\n out: integer\n Array index or `-1`.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n \n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element. \n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n \n Returns\n -------\n out: any\n Accumulated result.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n \n thisArg: Any (optional)\n Execution context.\n \n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n \n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n Modified array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = arr.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = arr.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n \n > var re = real( z )\n 2.0\n > var im = imag( z )\n -2.0\n > z = out.get( 1 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n \n options: Object (optional)\n An object containing serialization options.\n \n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var z = out.get( 0 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n 3.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n 2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 1.0\n > im = imag( z )\n 1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n \n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n \n > var re = real( z )\n 1.0\n > var im = imag( z )\n -1.0\n > z = out.get( 1 )\n \n > re = real( z )\n 2.0\n > im = imag( z )\n -2.0\n > z = out.get( 2 )\n \n > re = real( z )\n 3.0\n > im = imag( z )\n -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n \n > var re = real( v )\n 1.0\n > var im = imag( v )\n -1.0\n > v = it.next().value\n \n > re = real( v )\n 2.0\n > im = imag( v )\n -2.0\n > var bool = it.next().done\n true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n \n value: Complex128\n Element value. \n\n Returns\n -------\n out: Complex128Array\n New typed array.\n \n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n \n > var z = out.get( 1 )\n \n > var re = real( z )\n 3.0\n > var im = imag( z )\n -3.0\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n See Also\n --------\n isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = ddot( x, y )\n \n > z.get()\n -5.0\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n Interchanges two double-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var o = {a: 1, b: 2, c: 3};\n > var bool = everyInBy( o, positive )\n true\n\n See Also\n --------\n anyInBy, noneInBy, someInBy, everyBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > var bool = everyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n\n Examples\n --------\n > FLOAT32_E\n 2.7182817459106445\n\n See Also\n --------\n E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EXPONENT_MASK\n 2139095040\n > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n '01111111100000000000000000000000'\n\n See Also\n --------\n FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_FOURTH_PI\n 7.853981852531433e-1\n\n See Also\n --------\n FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_HALF_LN_TWO\n 0.3465735912322998\n\n See Also\n --------\n HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_HALF_PI\n 1.5707963705062866\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_HALF\n -0.6931471824645996\n\n See Also\n --------\n LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_PI\n 1.1447298526763916\n\n See Also\n --------\n FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TEN\n 2.3025851249694824\n\n See Also\n --------\n FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TWO\n 0.6931471824645996\n\n See Also\n --------\n FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT\n 127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n -127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT\n 38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n -38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_FIBONACCI\n 14930352\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n 34\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n 36\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_LUCAS\n 34\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT\n -126\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n -149\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT\n -37\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n -45\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n\n Examples\n --------\n > FLOAT32_PHI\n 1.6180340051651\n\n See Also\n --------\n PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_PI\n 3.1415927410125732\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGNIFICAND_MASK\n 8388607\n > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n '00000000011111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF\n 0.7071067690849304\n\n See Also\n --------\n SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF_PI\n 1.2533141374588013\n\n See Also\n --------\n SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PHI\n 1.272019624710083\n\n See Also\n --------\n SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PI\n 1.7724539041519165\n\n See Also\n --------\n FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_THREE\n 1.7320507764816284\n\n See Also\n --------\n FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO\n 1.4142135381698608\n\n See Also\n --------\n FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the `π` times `2` as single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO_PI\n 2.5066282749176025\n\n See Also\n --------\n FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > FLOAT32_TWO_PI\n 6.2831854820251465\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: starting character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","format":"\nformat( str, ...args )\n Insert supplied variable values into a format string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = format( 'Hello, %s!', 'World' )\n 'Hello, World!'\n\n > out = format( '%s %s', 'Hello', 'World' )\n 'Hello World'\n\n > out = format( 'Pi: %.2f', PI )\n 'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support arrow functions.\n\n Examples\n --------\n > var bool = hasArrowFunctionSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `atob` support.\n\n Examples\n --------\n > var bool = hasAtobSupport()\n \n\n See Also\n --------\n hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `btoa` support.\n\n Examples\n --------\n > var bool = hasBtoaSupport()\n \n\n See Also\n --------\n hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object.\n - result: either `x` or `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion.\n\n The predicate function callback accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value.\n - w: weight.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n\n Examples\n --------\n > IS_DOCKER\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n\n Examples\n --------\n > IS_MOBILE\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n\n Examples\n --------\n > IS_TOUCH_DEVICE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n Tests whether a value is an absolute HTTP(S) URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n Examples\n --------\n > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n true\n > bool = isAbsoluteHttpURI( 'example.com' )\n false\n > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n Tests whether a value is an absolute URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute URI.\n\n Examples\n --------\n > var bool = isAbsoluteURI( 'http://example.com/' )\n true\n > bool = isAbsoluteURI( 'example.com' )\n false\n > bool = isAbsoluteURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n Tests if a value is an arrow function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arrow function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isArrowFunction( beep )\n false\n > bool = isArrowFunction( {} )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCamelcase":"\nisCamelcase( value )\n Tests if a value is a camelcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a camelcase string.\n\n Examples\n --------\n > var bool = isCamelcase( 'helloWorld' )\n true\n > bool = isCamelcase( 'hello world' )\n false\n\n See Also\n --------\n isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex128';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n Tests if a value is a constantcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a constantcase string.\n\n Examples\n --------\n > var bool = isConstantcase( 'BEEP_BOOP' )\n true\n > bool = isConstantcase( 'BEEP and BOOP' )\n false\n\n See Also\n --------\n isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n Tests if a value is the current year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is the current year.\n\n Examples\n --------\n > var bool = isCurrentYear( new Date() )\n true\n > bool = isCurrentYear( currentYear() )\n true\n > bool = isCurrentYear( 2021 )\n false\n > bool = isCurrentYear( null )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isDomainName":"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n","isDurationString":"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n Tests if two arguments are both generic arrays and have equal values.\n\n The function performs strict equality comparison; thus, the function treats\n `-0` and `+0` as equal and `NaNs` as distinct.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are equal.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isEqualArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isEqualArray( x, y )\n false\n\n See Also\n --------\n isArray, isSameArray\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isKebabcase":"\nisKebabcase( value )\n Tests if a value is a string in kebab case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in kebab case.\n\n Examples\n --------\n > var bool = isKebabcase( 'beep-boop' )\n true\n > bool = isKebabcase( 'BEEP_BOOP' )\n false\n\n See Also\n --------\n isString","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n Tests if a value is an ndarray-like object having a specified data type.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n dtype: any\n Data type value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object having a\n specified data type.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLikeWithDataType( M, 'generic' )\n true\n > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n false\n > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n false\n > bool = isndarrayLikeWithDataType( {}, 'generic' )\n false\n\n See Also\n --------\n isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n Tests if a value is a finite negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite negative number.\n\n Examples\n --------\n > var bool = isNegativeFinite( -5.0 )\n true\n > bool = isNegativeFinite( new Number( -5.0 ) )\n true\n > bool = isNegativeFinite( -3.14 )\n true\n > bool = isNegativeFinite( 5.0 )\n false\n > bool = isNegativeFinite( null )\n false\n > bool = isNegativeFinite( -1.0/0.0 )\n false\n > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n Tests if a value is a nonpositive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = isNonPositiveFinite( -5.0 )\n true\n > bool = isNonPositiveFinite( new Number( -5.0 ) )\n true\n > bool = isNonPositiveFinite( -3.14 )\n true\n > bool = isNonPositiveFinite( 5.0 )\n false\n > bool = isNonPositiveFinite( null )\n false\n\n\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPascalcase":"\nisPascalcase( value )\n Tests if a value is a string in Pascal case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in Pascal case.\n\n Examples\n --------\n > var bool = isPascalcase( 'HelloWorld' )\n true\n > bool = isPascalcase( 'hello-world' )\n false\n\n See Also\n --------\n isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n Tests if a value is a positive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a positive finite number.\n\n Examples\n --------\n > var bool = isPositiveFinite( 5.0 )\n true\n > bool = isPositiveFinite( new Number( 5.0 ) )\n true\n > bool = isPositiveFinite( 3.14 )\n true\n > bool = isPositiveFinite( -5.0 )\n false\n > var bool = isPositiveFinite( 1.0/0.0 )\n false\n > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n false\n > bool = isPositiveFinite( null )\n false\n\n\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n Tests if a value is a ragged nested array. \n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a ragged nested array.\n\n Examples\n --------\n > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n true\n > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n false\n > bool = isRaggedNestedArray( 'beep' )\n false\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n Tests whether a value is a relative URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is a relative URI.\n\n Examples\n --------\n > var bool = isRelativeURI( '/images/example.png' )\n true\n > bool = isRelativeURI( 'http://www.example.com' )\n false\n > bool = isRelativeURI( null )\n false\n\n See Also\n --------\n isURI","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n Tests if two arguments are both array-like and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArrayLike( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArrayLike( x, y )\n true\n\n See Also\n --------\n isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding \n to the same date and time.\n\n Parameters\n ----------\n d1: any\n First input value.\n d2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether both values are Date objects \n corresponding to the same date and time.\n\n Examples\n --------\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var bool = isSameDateObject( d1, d2 )\n true\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n > var bool = isSameDateObject( d1, d2 )\n false\n \n See Also\n --------\n isDateObject, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n Tests if a value is a semantic version string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a provided value is a semantic version\n string.\n\n Examples\n --------\n > var bool = isSemVer( '1.0.0' )\n true\n > bool = isSemVer( '1.0.0-alpha.1' )\n true\n > bool = isSemVer( '0.1' )\n false\n > bool = isSemVer( null )\n false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n Tests if a value is a string in snake case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in snake case.\n\n Examples\n --------\n > var bool = isSnakecase( 'hello_world' )\n true\n > bool = isSnakecase( 'Hello World' )\n false\n\n See Also\n --------\n isString","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n Tests if a value is a startcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is a startcase string.\n\n Examples\n --------\n > var bool = isStartcase( 'Beep Boop' )\n true\n > bool = isStartcase( 'Beep and Boop' )\n false\n\n See Also\n --------\n isString","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n Tests if a value is a WebAssembly memory instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a WebAssembly memory instance.\n\n Examples\n --------\n > var bool = isWebAssemblyMemory( {} )\n false\n\n See Also\n --------\n hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n Tests if a string is well-formed.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is well-formed.\n\n Examples\n --------\n > var bool = isWellFormedString( '' )\n true\n\n > bool = isWellFormedString( new String( '' ) )\n true\n\n > bool = isWellFormedString( '\\uDBFF' )\n false\n\n > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n false\n\n > bool = isWellFormedString( [] )\n false\n\n > bool = isWellFormedString( '-5' )\n true\n\n > bool = isWellFormedString( null )\n false\n\n\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false\n\n\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value.\n - index: iterated value index (zero-based).\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value.\n - sprev: previous source iterated value.\n - dprev: previous downstream iterated value.\n - index: source iteration index (zero-based).\n - acc: previous resolved value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values.\n - index: iteration index (zero-based).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value.\n - index: source iteration index (zero-based).\n - n: iteration index (zero-based).\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value.\n - i: input iteration index (zero-based).\n - n: output (strided) iteration index (zero-based).\n - curr: current stride.\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 64.\n\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant\n object has the next\n iterated value (if one exists) and a\n boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n\n Examples\n --------\n > var it = iterTribonnaciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 0\n\n See Also\n --------\n base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n Returns the last character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = last( 'beep' )\n 'p'\n > out = last( 'Boop', 2 )\n 'op'\n > out = last( 'foo bar', 3 )\n 'bar'\n\n See Also\n --------\n firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n Trims `n` characters from the beginning of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrimN( ' abc ', 2 )\n 'abc '\n > var out = ltrimN( '!!!abc!!!', 2, '!' )\n '!abc!!!'\n\n See Also\n --------\n rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - index: invocation index (starting from zero).\n - next: callback to be invoked upon function completion.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `key`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - key\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - key\n - value\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - key: transformed key.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `value`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - value\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - value\n - key\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - value: transformed value.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size.\n - cities: cities.\n - labels: map labels.\n - temperature: temperature during the army's return from Russia.\n - rivers: river data.\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier).\n - title: chapter title (if available; otherwise, empty).\n - text: chapter text.\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n Converts an ndarray to an object supporting fancy indexing.\n\n An ndarray supporting fancy indexing is an ndarray which supports slicing\n via indexing expressions for both retrieval and assignment.\n\n A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n any mutations to the returned ndarray will affect the underlying input\n ndarray and vice versa.\n\n A fancy ndarray supports indexing using positive and negative integers (both\n numeric literals and strings), Slice and MultiSlice instances, subsequence\n expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n A fancy ndarray supports all properties and methods of the input ndarray,\n and, thus, a fancy ndarray can be consumed by any API which supports\n ndarray-like objects.\n\n For operations returning a new ndarray (e.g., when slicing or invoking an\n instance method), a fancy ndarray returns a new fancy ndarray having the\n same configuration as specified by provided options.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n are repeated (without additional memory allocation) to match the dimensions\n of a target ndarray instance.\n\n When assigning ndarrays to slices, the ndarray on the right-hand-side must\n be broadcast-compatible with dimensions implied by the slice.\n\n Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point ndarrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy ndarrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number ndarray, a fancy\n ndarray will cast the real-valued scalar to a complex number argument having\n an imaginary component equal to zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n out: ndarray\n Output ndarray supporting fancy indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Convert to a fancy ndarray:\n > var arr = ndarray2fancy( x );\n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n Serializes an ndarray as a JSON object.\n\n This function does *not* serialize data outside of the buffer region defined\n by the ndarray view.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2json( arr )\n {...}\n\n See Also\n --------\n array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n - binary: binary.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n [...]\n > out = ndarrayDataTypes( 'floating_point' )\n [...]\n > out = ndarrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n Converts an ndarray-like object to an ndarray.\n\n If provided a read-only ndarray, the function returns a read-only ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray-like object.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarraylike2ndarray( arr )\n \n\n See Also\n --------\n array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndemptyLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v > 2.0; };\n > var y = ndfilter( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n If a provided callback function returns `undefined`, the function skips the\n respective ndarray element. If the callback function returns a value other\n than `undefined`, the function stores the callback's return value in the\n output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n > var y = ndfilterMap( x, f );\n > ndarray2array( y )\n [ 30.0, 40.0 ]\n\n See Also\n --------\n ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n Invokes a callback function once for each ndarray element.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n > ndforEach( x, f );\n\n See Also\n --------\n ndmap","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n Wraps a provided array as an ndarray index object.\n\n ndarray index instances have no explicit functionality; however, they are\n used by \"fancy\" ndarrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying ndarray are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped ndarray, as the consumer will attempt to resolve an\n instance in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n\n\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n \n\n\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}\n\n\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n \n\n\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'\n\n\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n \n\n\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true\n\n\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'\n\n\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n \n\n\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n \n\n\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n ","ndindex.get":"\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n ","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n ","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n ","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n ","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n Returns an iterator which iterates over interleaved subarrays.\n\n For input ndarrays supporting read-only views, the function returns\n *read-only* views of interleaved subarrays. As input ndarrays may be\n broadcasted, a view is typically *not* contiguous. As more than one element\n of a returned view may refer to the same memory location, writing to a view\n may affect multiple elements. If you need to write to a subarray, copy the\n subarray before attempting mutation.\n\n The function throws an error if a provided broadcast-incompatible ndarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n arr: ArrayLike\n Input ndarrays. All ndarrays must be broadcast-compatible. After\n broadcasting, each broadcasted input ndarray must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack after broadcasting.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n options.keepdim: boolean (optional)\n Boolean indicating whether returned views should include the selected\n dimension as a singleton dimension. Including the selected dimension as\n a singleton dimension can be useful when wanting to ensure that returned\n views remain broadcast compatible with the input ndarray. Default:\n false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSelectDimension( x, 0 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `dims.length+1` dimensions.\n\n dims: Array\n Indices of dimensions to stack. If a dimension index is less than zero,\n the index is resolved relative to the last dimension, with the last\n dimension corresponding to the value `-1`. The list of indices must be\n unique and resolve to dimension indices sorted in ascending order.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerStacks( x, [ 1, 2 ] );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSubarrays( x, 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v*10.0; };\n > var y = ndmap( x, f );\n > ndarray2array( y )\n [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v <= 2.0; };\n > var y = ndreject( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Underlying data type. Must be a numeric data type or \"generic\". Default:\n 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n \n > var sh = arr.shape\n [ 2, 2 ]\n > var dt = arr.dtype\n 'float64'\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var dt = x.dtype\n 'float64'\n > var y = ndzerosLike( x )\n \n > sh = y.shape\n [ 2, 2 ]\n > dt = y.dtype\n 'float64'\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n > var bool = noneInBy( obj, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, forIn, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all own properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function isUnderage( v ) { return ( v < 18 ); };\n > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n > var bool = noneOwnBy( obj, isUnderage )\n false\n\n See Also\n --------\n anyOwnBy, everyOwnBy, forOwn, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number.\n - town: town name.\n - town_id: town identifier.\n - tract: tract identifier.\n - lon: longitude.\n - lat: latitude.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - bh: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - bonferroni: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - by: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - holm: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - hommel: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path.\n - data: file contents as either a Buffer or string.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n The regular expression captures the following groups:\n\n 1. The days component.\n 2. The hours component.\n 3. The minutes component.\n 4. The seconds component.\n 5. The milliseconds component.\n\n Returns\n -------\n re: RegExp: Regular expression\n Regular expression to match a duration string.\n\n Examples\n --------\n > var RE = reDurationString();\n > var parts = RE.exec( '3d2ms' )\n [...]\n > parts = RE.exec( '4h3m20s' )\n [...]\n\n\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n \n replacement: string\n Replacement string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = replaceBefore( str, ' ', 'foo' )\n 'foo boop'\n > out = replaceBefore( str, 'o', 'foo' )\n 'foooop'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - path: a resolved path.\n - next: a callback to be invoked after processing a resolved path.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer).\n - data: buffer data as an array of integers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n - re: real component (number).\n - im: imaginary component (number).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp).\n - pattern: regular expression pattern.\n - flags: regular expression flags.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n - data: typed array data as an array of numbers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n Trims `n` characters from the end of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrimN( ' abc ', 2 )\n ' abc'\n > var out = rtrimN( '!!!abc!!!', 2, '!' )\n '!!!abc!'\n\n See Also\n --------\n ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = sdot( x, y )\n \n > z.get()\n -5.0\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","sentencize":"\nsentencize( str )\n Splits a string into an array of sentences.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of sentences.\n\n Examples\n --------\n > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello Mrs. Maple, could you call me back?' ]\n\n > out = sentencize( 'Hello World! How are you?' )\n [ 'Hello World!', 'How are you?' ]\n\n See Also\n --------\n tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - complex128: 128-bit complex numbers.\n - complex64: 64-bit complex numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection value.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object contains at least `n`\n successful properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n > var bool = someInBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object's own properties satisfy a\n predicate for at least `n` properties; otherwise, the function\n returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n > var bool = someOwnBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year.\n - name: President name.\n - party: the President's political party.\n - text: speech text.\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group).\n - group: message group.\n - checksum: object containing checksum info.\n - text: message text (including headers).\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages).\n - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n - spam-1: spam e-mails (500 messages).\n - spam-2: spam e-mails collected at a later date (1396 messages).\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5).\n - value: checksum value.\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n Interchanges two single-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.356, ~0.786 ]\n > y0\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy( 2, x, 2, y, -1, clbk )\n [ ~1.317, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.567, ~0.962 ]\n > y0\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy( 2, x, 2, y, -1, clbk )\n [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~-0.588 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy( 2, x, 2, y, -1, clbk )\n [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n [ -Infinity, ~-0.255 ]\n > y0\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 13.0, 14.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 17.0, 16.0 ]\n > z0\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n [ 0.0, ~3.142, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.094, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n [ ~3.142, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.047, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy( 2, x, 2, y, -1, clbk )\n [ ~1.571, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.253, ~-0.524 ]\n > y0\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy( 2, x, 2, y, -1, clbk )\n [ ~1.444, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-1.444, 0.0 ]\n > y0\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy( 2, x, 2, y, -1, clbk )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.896, ~-0.464 ]\n > y0\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy( 2, x, 2, y, -1, clbk )\n [ Infinity, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.255, ~-0.549 ]\n > y0\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By( 2, x, 2, y, -1, clbk )\n [ ~0.998, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n [ ~0.984, ~0.765 ]\n > y0\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By( 2, x, 2, y, -1, clbk )\n [ ~0.05, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n [ ~0.124, ~0.44 ]\n > y0\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By( 2, x, 2, y, -1, clbk )\n [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n [ ~-0.932, ~0.088 ]\n > y0\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By( 2, x, 2, y, -1, clbk )\n [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n [ ~-2.704, ~-0.781 ]\n > y0\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy( 2, x, 2, y, -1, clbk )\n [ 1.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n [ 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy( 2, x, 2, y, -1, clbk )\n [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.839, ~-1.0 ]\n > y0\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - bool: boolean values.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 12.0, 33.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 52.0, 28.0 ]\n > z0\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy( 2, x, 2, y, -1, clbk )\n [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.544, ~0.002 ]\n > y0\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n [ ~11.045, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~7.071, 1.0 ]\n > y0\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 4.0, 5.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 8.0, 7.0 ]\n > z0\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - result: function result.\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object.\n - result: either the result of `x` or the provided argument `y`.\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`.\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > var arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n - BooleanArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type.\n - data: typed array data as a generic array.\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n \n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n \n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n ","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n ","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n WebAssembly memory constructor.\n\n Parameters\n ----------\n descriptor: Object\n Memory descriptor object.\n\n descriptor.initial: integer\n Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.maximum: integer (optional)\n Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.shared: boolean (optional)\n Boolean indicating whether the memory is shared. Default: false.\n\n Returns\n -------\n out: Memory\n WebAssembly memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n \n\n\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n \n\n\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n \n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n ","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n ","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv index cb8d6c47900b..525234c8318f 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.csv +++ b/lib/node_modules/@stdlib/repl/info/data/data.csv @@ -244,6 +244,8 @@ base.cinv,"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-pre base.clamp,"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n" base.clampf,"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n" base.cmul,"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n" +base.cmul.assign,"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n" +base.cmul.strided,"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n" base.cmulf,"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n" base.cneg,"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n" base.cnegf,"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n" @@ -691,7 +693,7 @@ base.dists.laplace.stdev,"\nbase.dists.laplace.stdev( μ:number, b:number )\n base.dists.laplace.variance,"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n" base.dists.levy.cdf,"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n" base.dists.levy.cdf.factory,"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n" -base.dists.levy.entropy,"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n" +base.dists.levy.entropy,"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n" base.dists.levy.Levy,"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n" base.dists.levy.logcdf,"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n" base.dists.levy.logcdf.factory,"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n" @@ -708,7 +710,7 @@ base.dists.levy.stdev,"\nbase.dists.levy.stdev( μ:number, c:number )\n Retur base.dists.levy.variance,"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n" base.dists.logistic.cdf,"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n" base.dists.logistic.cdf.factory,"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n" -base.dists.logistic.entropy,"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n" +base.dists.logistic.entropy,"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n" base.dists.logistic.kurtosis,"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n" base.dists.logistic.logcdf,"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n" base.dists.logistic.logcdf.factory,"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n" @@ -1734,26 +1736,26 @@ base.strided.dmax,"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integ base.strided.dmax.ndarray,"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n" base.strided.dmaxabs,"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n" base.strided.dmaxabs.ndarray,"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n" -base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n" -base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n" -base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n" -base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n" +base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n" +base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n" +base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.dmean,"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n" base.strided.dmean.ndarray,"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n" -base.strided.dmeankbn,"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n" -base.strided.dmeankbn.ndarray,"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" -base.strided.dmeankbn2,"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n" -base.strided.dmeankbn2.ndarray,"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n" -base.strided.dmeanli,"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" -base.strided.dmeanli.ndarray,"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" +base.strided.dmeankbn,"\nbase.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n" +base.strided.dmeankbn.ndarray,"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" +base.strided.dmeankbn2,"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n" +base.strided.dmeankbn2.ndarray,"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n" +base.strided.dmeanli,"\nbase.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" +base.strided.dmeanli.ndarray,"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" base.strided.dmeanlipw,"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n" base.strided.dmeanlipw.ndarray,"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n" -base.strided.dmeanors,"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n" -base.strided.dmeanors.ndarray,"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n" +base.strided.dmeanors,"\nbase.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n" +base.strided.dmeanors.ndarray,"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n" base.strided.dmeanpn,"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n" base.strided.dmeanpn.ndarray,"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n" -base.strided.dmeanpw,"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n" -base.strided.dmeanpw.ndarray,"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n" +base.strided.dmeanpw,"\nbase.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n" +base.strided.dmeanpw.ndarray,"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n" base.strided.dmeanstdev,"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n" base.strided.dmeanstdev.ndarray,"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n" base.strided.dmeanstdevpn,"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n" @@ -1762,18 +1764,18 @@ base.strided.dmeanvar,"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Ar base.strided.dmeanvar.ndarray,"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n" base.strided.dmeanvarpn,"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n" base.strided.dmeanvarpn.ndarray,"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n" -base.strided.dmeanwd,"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n" -base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" -base.strided.dmediansorted,"\nbase.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n" -base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.dmeanwd,"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n" +base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" +base.strided.dmediansorted,"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n" +base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.dmidrange,"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n" base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n" base.strided.dmin,"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n" base.strided.dmin.ndarray,"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n" base.strided.dminabs,"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n" base.strided.dminabs.ndarray,"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n" -base.strided.dminsorted,"\nbase.strided.dminsorted( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n" -base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.dminsorted,"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n" +base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.dmskabs,"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n" base.strided.dmskabs.ndarray,"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n" base.strided.dmskabs2,"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n" @@ -1820,10 +1822,10 @@ base.strided.dnanmeanors,"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, base.strided.dnanmeanors.ndarray,"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n" base.strided.dnanmeanpn,"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n" base.strided.dnanmeanpn.ndarray,"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n" -base.strided.dnanmeanpw,"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n" -base.strided.dnanmeanpw.ndarray,"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n" -base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n" -base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n" +base.strided.dnanmeanpw,"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n" +base.strided.dnanmeanpw.ndarray,"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n" +base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n" +base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n" base.strided.dnanmin,"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n" base.strided.dnanmin.ndarray,"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n" base.strided.dnanminabs,"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n" @@ -1900,26 +1902,26 @@ base.strided.dsdot,"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:int base.strided.dsdot.ndarray,"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n" base.strided.dsem,"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n" base.strided.dsem.ndarray,"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n" -base.strided.dsemch,"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n" -base.strided.dsemch.ndarray,"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n" +base.strided.dsemch,"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n" +base.strided.dsemch.ndarray,"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n" base.strided.dsempn,"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n" base.strided.dsempn.ndarray,"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n" -base.strided.dsemtk,"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n" -base.strided.dsemtk.ndarray,"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n" -base.strided.dsemwd,"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n" -base.strided.dsemwd.ndarray,"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n" -base.strided.dsemyc,"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n" -base.strided.dsemyc.ndarray,"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n" +base.strided.dsemtk,"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n" +base.strided.dsemtk.ndarray,"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n" +base.strided.dsemwd,"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n" +base.strided.dsemwd.ndarray,"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n" +base.strided.dsemyc,"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n" +base.strided.dsemyc.ndarray,"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n" base.strided.dsmean,"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n" base.strided.dsmean.ndarray,"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n" -base.strided.dsmeanors,"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n" -base.strided.dsmeanors.ndarray,"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n" -base.strided.dsmeanpn,"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n" -base.strided.dsmeanpn.ndarray,"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n" -base.strided.dsmeanpw,"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n" -base.strided.dsmeanpw.ndarray,"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n" -base.strided.dsmeanwd,"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n" -base.strided.dsmeanwd.ndarray,"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n" +base.strided.dsmeanors,"\nbase.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n" +base.strided.dsmeanors.ndarray,"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n" +base.strided.dsmeanpn,"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n" +base.strided.dsmeanpn.ndarray,"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n" +base.strided.dsmeanpw,"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n" +base.strided.dsmeanpw.ndarray,"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n" +base.strided.dsmeanwd,"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n" +base.strided.dsmeanwd.ndarray,"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n" base.strided.dsnanmean,"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n" base.strided.dsnanmean.ndarray,"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n" base.strided.dsnanmeanors,"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n" @@ -1958,26 +1960,26 @@ base.strided.dssumpw,"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX base.strided.dssumpw.ndarray,"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n" base.strided.dstdev,"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n" base.strided.dstdev.ndarray,"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n" -base.strided.dstdevch,"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" -base.strided.dstdevch.ndarray,"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" +base.strided.dstdevch,"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" +base.strided.dstdevch.ndarray,"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" base.strided.dstdevpn,"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n" base.strided.dstdevpn.ndarray,"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n" -base.strided.dstdevtk,"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n" -base.strided.dstdevtk.ndarray,"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n" -base.strided.dstdevwd,"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n" -base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" -base.strided.dstdevyc,"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n" -base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n" -base.strided.dsum,"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements.\n" -base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n" +base.strided.dstdevtk,"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n" +base.strided.dstdevtk.ndarray,"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n" +base.strided.dstdevwd,"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n" +base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" +base.strided.dstdevyc,"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n" +base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n" +base.strided.dsum,"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements.\n" +base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n" base.strided.dsumkbn,"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n" base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" -base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n" -base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n" -base.strided.dsumors,"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n" -base.strided.dsumors.ndarray,"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n" -base.strided.dsumpw,"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n" -base.strided.dsumpw.ndarray,"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n" +base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n" +base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n" +base.strided.dsumors,"\nbase.strided.dsumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n" +base.strided.dsumors.ndarray,"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n" +base.strided.dsumpw,"\nbase.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n" +base.strided.dsumpw.ndarray,"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n" base.strided.dsvariance,"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n" base.strided.dsvariance.ndarray,"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n" base.strided.dsvariancepn,"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n" @@ -1992,38 +1994,38 @@ base.strided.dtypeResolveStr,"\nbase.strided.dtypeResolveStr( dtype:any )\n R base.strided.dtypeStr2Enum,"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n" base.strided.dvariance,"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array.\n" base.strided.dvariance.ndarray,"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n" -base.strided.dvariancech,"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n" -base.strided.dvariancech.ndarray,"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n" +base.strided.dvariancech,"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n" +base.strided.dvariancech.ndarray,"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n" base.strided.dvariancepn,"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n" base.strided.dvariancepn.ndarray,"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n" -base.strided.dvariancetk,"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n" -base.strided.dvariancetk.ndarray,"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n" -base.strided.dvariancewd,"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n" -base.strided.dvariancewd.ndarray,"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n" -base.strided.dvarianceyc,"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n" -base.strided.dvarianceyc.ndarray,"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n" +base.strided.dvariancetk,"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n" +base.strided.dvariancetk.ndarray,"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n" +base.strided.dvariancewd,"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n" +base.strided.dvariancewd.ndarray,"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n" +base.strided.dvarianceyc,"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n" +base.strided.dvarianceyc.ndarray,"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n" base.strided.dvarm,"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n" base.strided.dvarm.ndarray,"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n" base.strided.dvarmpn,"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n" base.strided.dvarmpn.ndarray,"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n" -base.strided.dvarmtk,"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n" -base.strided.dvarmtk.ndarray,"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n" -base.strided.gapx,"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n Adds a constant to each element in a strided array.\n" -base.strided.gapx.ndarray,"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n" -base.strided.gapxsum,"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum.\n" -base.strided.gapxsum.ndarray,"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n" -base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n" -base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n" -base.strided.gapxsumkbn2,"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n" -base.strided.gapxsumkbn2.ndarray,"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n" -base.strided.gapxsumors,"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n" -base.strided.gapxsumors.ndarray,"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n" -base.strided.gapxsumpw,"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n" -base.strided.gapxsumpw.ndarray,"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n" +base.strided.dvarmtk,"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n" +base.strided.dvarmtk.ndarray,"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n" +base.strided.gapx,"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n" +base.strided.gapx.ndarray,"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n" +base.strided.gapxsum,"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum.\n" +base.strided.gapxsum.ndarray,"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n" +base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n" +base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" +base.strided.gapxsumkbn2,"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n" +base.strided.gapxsumkbn2.ndarray,"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n" +base.strided.gapxsumors,"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n" +base.strided.gapxsumors.ndarray,"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n" +base.strided.gapxsumpw,"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n" +base.strided.gapxsumpw.ndarray,"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n" base.strided.gasum,"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n" base.strided.gasum.ndarray,"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n" -base.strided.gasumpw,"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n" -base.strided.gasumpw.ndarray,"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n" +base.strided.gasumpw,"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n" +base.strided.gasumpw.ndarray,"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n" base.strided.gaxpy,"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n" base.strided.gaxpy.ndarray,"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n" base.strided.gcopy,"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n" @@ -2040,26 +2042,26 @@ base.strided.gcusumpw,"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|T base.strided.gcusumpw.ndarray,"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n" base.strided.gdot,"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n" base.strided.gdot.ndarray,"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n" -base.strided.gfill,"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n Fills a strided array with a specified scalar value.\n" -base.strided.gfill.ndarray,"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n stride:integer, offset:integer )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n" -base.strided.gfillBy,"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n" -base.strided.gfillBy.ndarray,"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n" +base.strided.gfill,"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )\n Fills a strided array with a specified scalar constant.\n" +base.strided.gfill.ndarray,"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n" +base.strided.gfillBy,"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n" +base.strided.gfillBy.ndarray,"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n" base.strided.gnannsumkbn,"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n" base.strided.gnannsumkbn.ndarray,"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n" -base.strided.gnansum,"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n" -base.strided.gnansum.ndarray,"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n" -base.strided.gnansumkbn,"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n" -base.strided.gnansumkbn.ndarray,"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n" -base.strided.gnansumkbn2,"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n" -base.strided.gnansumkbn2.ndarray,"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n" -base.strided.gnansumors,"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n" -base.strided.gnansumors.ndarray,"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n" -base.strided.gnansumpw,"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n" -base.strided.gnansumpw.ndarray,"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n" +base.strided.gnansum,"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n" +base.strided.gnansum.ndarray,"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n" +base.strided.gnansumkbn,"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n" +base.strided.gnansumkbn.ndarray,"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n" +base.strided.gnansumkbn2,"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n" +base.strided.gnansumkbn2.ndarray,"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n" +base.strided.gnansumors,"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n" +base.strided.gnansumors.ndarray,"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n" +base.strided.gnansumpw,"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n" +base.strided.gnansumpw.ndarray,"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n" base.strided.gnrm2,"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n" base.strided.gnrm2.ndarray,"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n" -base.strided.grev,"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n Reverses a strided array in-place.\n" -base.strided.grev.ndarray,"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n" +base.strided.grev,"\nbase.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )\n Reverses a strided array in-place.\n" +base.strided.grev.ndarray,"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n" base.strided.gscal,"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Multiplies a vector `x` by a constant `alpha`.\n" base.strided.gscal.ndarray,"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n" base.strided.gsort2hp,"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n" @@ -2076,14 +2078,14 @@ base.strided.gsortsh,"\nbase.strided.gsortsh( N:integer, order:number, x:Array|T base.strided.gsortsh.ndarray,"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n" base.strided.gsum,"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements.\n" base.strided.gsum.ndarray,"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n" -base.strided.gsumkbn,"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n" -base.strided.gsumkbn.ndarray,"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n" -base.strided.gsumkbn2,"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n" -base.strided.gsumkbn2.ndarray,"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n" -base.strided.gsumors,"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n" -base.strided.gsumors.ndarray,"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n" -base.strided.gsumpw,"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using pairwise summation.\n" -base.strided.gsumpw.ndarray,"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n" +base.strided.gsumkbn,"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n" +base.strided.gsumkbn.ndarray,"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n" +base.strided.gsumkbn2,"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n" +base.strided.gsumkbn2.ndarray,"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n" +base.strided.gsumors,"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n" +base.strided.gsumors.ndarray,"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n" +base.strided.gsumpw,"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using pairwise summation.\n" +base.strided.gsumpw.ndarray,"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n" base.strided.gswap,"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n" base.strided.gswap.ndarray,"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n" base.strided.mapBy,"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n" @@ -2207,22 +2209,22 @@ base.strided.sabs,"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integ base.strided.sabs.ndarray,"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n" base.strided.sabs2,"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n" base.strided.sabs2.ndarray,"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n" -base.strided.sapx,"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n" -base.strided.sapx.ndarray,"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n" -base.strided.sapxsum,"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n" -base.strided.sapxsum.ndarray,"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n" -base.strided.sapxsumkbn,"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n" -base.strided.sapxsumkbn.ndarray,"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n" -base.strided.sapxsumkbn2,"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n" -base.strided.sapxsumkbn2.ndarray,"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n" -base.strided.sapxsumors,"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n" -base.strided.sapxsumors.ndarray,"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n" -base.strided.sapxsumpw,"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n" -base.strided.sapxsumpw.ndarray,"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n" +base.strided.sapx,"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n" +base.strided.sapx.ndarray,"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.sapxsum,"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n" +base.strided.sapxsum.ndarray,"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n" +base.strided.sapxsumkbn,"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n" +base.strided.sapxsumkbn.ndarray,"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n" +base.strided.sapxsumkbn2,"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n" +base.strided.sapxsumkbn2.ndarray,"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n" +base.strided.sapxsumors,"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n" +base.strided.sapxsumors.ndarray,"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n" +base.strided.sapxsumpw,"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n" +base.strided.sapxsumpw.ndarray,"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n" base.strided.sasum,"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n" base.strided.sasum.ndarray,"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n" -base.strided.sasumpw,"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n" -base.strided.sasumpw.ndarray,"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n" +base.strided.sasumpw,"\nbase.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n" +base.strided.sasumpw.ndarray,"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n" base.strided.saxpy,"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n" base.strided.saxpy.ndarray,"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n" base.strided.scbrt,"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n" @@ -2243,8 +2245,8 @@ base.strided.scusum,"\nbase.strided.scusum( N:integer, sum:number, x:Float32Arra base.strided.scusum.ndarray,"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n" base.strided.scusumkbn,"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n" base.strided.scusumkbn.ndarray,"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" -base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n" -base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n" +base.strided.scusumkbn2,"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n" +base.strided.scusumkbn2.ndarray,"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n" base.strided.scusumors,"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n" base.strided.scusumors.ndarray,"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n" base.strided.scusumpw,"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n" @@ -2261,8 +2263,8 @@ base.strided.sdsdot,"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32A base.strided.sdsdot.ndarray,"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n" base.strided.sdsmean,"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n" base.strided.sdsmean.ndarray,"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n" -base.strided.sdsmeanors,"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n" -base.strided.sdsmeanors.ndarray,"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n" +base.strided.sdsmeanors,"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n" +base.strided.sdsmeanors.ndarray,"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n" base.strided.sdsnanmean,"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n" base.strided.sdsnanmean.ndarray,"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n" base.strided.sdsnanmeanors,"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n" @@ -2289,18 +2291,18 @@ base.strided.smax,"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integ base.strided.smax.ndarray,"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n" base.strided.smaxabs,"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n" base.strided.smaxabs.ndarray,"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n" -base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n" -base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n" -base.strided.smaxsorted,"\nbase.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n" -base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n" +base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n" +base.strided.smaxsorted,"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n" +base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.smean,"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n" base.strided.smean.ndarray,"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n" base.strided.smeankbn,"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n" base.strided.smeankbn.ndarray,"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n" base.strided.smeankbn2,"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n" base.strided.smeankbn2.ndarray,"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n" -base.strided.smeanli,"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" -base.strided.smeanli.ndarray,"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" +base.strided.smeanli,"\nbase.strided.smeanli( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" +base.strided.smeanli.ndarray,"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" base.strided.smeanlipw,"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n" base.strided.smeanlipw.ndarray,"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n" base.strided.smeanors,"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n" @@ -2309,18 +2311,18 @@ base.strided.smeanpn,"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride: base.strided.smeanpn.ndarray,"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n" base.strided.smeanpw,"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n" base.strided.smeanpw.ndarray,"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n" -base.strided.smeanwd,"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n" -base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" -base.strided.smediansorted,"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n" -base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.smeanwd,"\nbase.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n" +base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" +base.strided.smediansorted,"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n" +base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.smidrange,"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n" base.strided.smidrange.ndarray,"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n" base.strided.smin,"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n" base.strided.smin.ndarray,"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n" base.strided.sminabs,"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n" base.strided.sminabs.ndarray,"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n" -base.strided.sminsorted,"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n" -base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.sminsorted,"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n" +base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.smskabs,"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n" base.strided.smskabs.ndarray,"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n" base.strided.smskabs2,"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n" @@ -2439,12 +2441,12 @@ base.strided.ssqrt,"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:int base.strided.ssqrt.ndarray,"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n" base.strided.sstdev,"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n" base.strided.sstdev.ndarray,"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n" -base.strided.sstdevch,"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" -base.strided.sstdevch.ndarray,"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" +base.strided.sstdevch,"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n" +base.strided.sstdevch.ndarray,"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n" base.strided.sstdevpn,"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n" base.strided.sstdevpn.ndarray,"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n" -base.strided.sstdevtk,"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n" -base.strided.sstdevtk.ndarray,"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n" +base.strided.sstdevtk,"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n" +base.strided.sstdevtk.ndarray,"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n" base.strided.sstdevwd,"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n" base.strided.sstdevwd.ndarray,"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" base.strided.sstdevyc,"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n" @@ -2477,16 +2479,16 @@ base.strided.strunc,"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:i base.strided.strunc.ndarray,"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n" base.strided.svariance,"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array.\n" base.strided.svariance.ndarray,"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n" -base.strided.svariancech,"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n" -base.strided.svariancech.ndarray,"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n" +base.strided.svariancech,"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n" +base.strided.svariancech.ndarray,"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n" base.strided.svariancepn,"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n" base.strided.svariancepn.ndarray,"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n" -base.strided.svariancetk,"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n" -base.strided.svariancetk.ndarray,"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n" +base.strided.svariancetk,"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n" +base.strided.svariancetk.ndarray,"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n" base.strided.svariancewd,"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n" base.strided.svariancewd.ndarray,"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n" -base.strided.svarianceyc,"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n" -base.strided.svarianceyc.ndarray,"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n" +base.strided.svarianceyc,"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n" +base.strided.svarianceyc.ndarray,"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n" base.strided.ternary,"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n" base.strided.ternary.ndarray,"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n" base.strided.unary,"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n" diff --git a/lib/node_modules/@stdlib/repl/info/data/data.json b/lib/node_modules/@stdlib/repl/info/data/data.json index f1fc5246902d..f36908c9fba1 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.json +++ b/lib/node_modules/@stdlib/repl/info/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n","base.acosf":"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n","base.acotf":"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n","base.acscdf":"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n","base.acscf":"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array )\n Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array )\n Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array )\n Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array )\n Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array )\n Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array )\n Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array )\n Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array )\n Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array )\n Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array )\n Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n","base.asecdf":"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n","base.asecf":"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n","base.asindf":"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n","base.asinf":"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n","base.atanf":"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array )\n Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array )\n Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array )\n Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array )\n Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array )\n Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.camelcase":"\nbase.camelcase( str:string )\n Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n Tokenize a string into an array of string parts and format identifier\n objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.last":"\nbase.last( str:string, n:integer )\n Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject, order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the first occurrence of a specified search\n string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the last occurrence of a specified search\n string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the first occurrence of a specified search\n string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the last occurrence of a specified search\n string.\n","base.reverse":"\nbase.reverse( str:string )\n Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n Right pads a string such that the padded string has a length of at least\n `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array, strict:boolean )\n Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, stride:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using an\n improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using a\n second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Adds a constant to each strided array element and computes the sum using\n pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n stride:integer, offset:integer )\n Fills a strided array with a specified scalar value using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n offset:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n obj:Object|Function, bool:boolean )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n offset:integer )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each element in a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided \n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array\n elements, ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\nBooleanArray( length:integer )\n Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\nComplex64Array( length:integer )\n Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the `π` times `2` as single-precision floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","format":"\nformat( str:string, ...args:any )\n Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have equal values.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding \n to the same date and time.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStartcase":"\nisStartcase( value:any )\n Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n Returns the ndarray associated with the instance having a provided\n identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )\n Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} +{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n","base.acosf":"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n","base.acotf":"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n","base.acscdf":"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n","base.acscf":"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array )\n Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array )\n Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array )\n Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array )\n Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array )\n Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array )\n Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array )\n Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array )\n Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array )\n Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array )\n Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n","base.asecdf":"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n","base.asecf":"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n","base.asindf":"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n","base.asinf":"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n","base.atanf":"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array )\n Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array )\n Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array )\n Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array )\n Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array )\n Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.camelcase":"\nbase.camelcase( str:string )\n Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds a single-precision complex floating-point number toward positive\n infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmul.assign":"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmul.strided":"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n Tokenize a string into an array of string parts and format identifier\n objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.last":"\nbase.last( str:string, n:integer )\n Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject, order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n assigns results to a provided output array.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the first occurrence of a specified search\n string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the last occurrence of a specified search\n string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the first occurrence of a specified search\n string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the last occurrence of a specified search\n string.\n","base.reverse":"\nbase.reverse( str:string )\n Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n Right pads a string such that the padded string has a length of at least\n `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array, strict:boolean )\n Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number and assigns\n results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one complex single-precision floating-point vector to\n another complex single-precision floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two complex single-precision floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, stride:integer, offset:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )\n Fills a strided array with a specified scalar constant.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer )\n Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n stride:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n obj:Object|Function, bool:boolean )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n offset:integer )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n stride:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Adds a constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array\n elements, ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n stride:integer, offset:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n stride:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, stride:integer, offset:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\nBooleanArray( length:integer )\n Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\nComplex64Array( length:integer )\n Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or \n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the `π` times `2` as single-precision floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","format":"\nformat( str:string, ...args:any )\n Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have equal values.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding \n to the same date and time.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStartcase":"\nisStartcase( value:any )\n Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n Returns the ndarray associated with the instance having a provided\n identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )\n Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `x` to a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} diff --git a/lib/node_modules/@stdlib/repl/lib/actions.js b/lib/node_modules/@stdlib/repl/lib/actions.js new file mode 100644 index 000000000000..86ceb3aecafb --- /dev/null +++ b/lib/node_modules/@stdlib/repl/lib/actions.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* List of REPL actions. +* +* @private +* @name ACTIONS +* @type {Object} +*/ +var ACTIONS = [ + 'moveRight', + 'moveLeft', + 'moveWordRight', + 'moveWordLeft', + 'moveBeginning', + 'moveEnd', + 'tab', + 'indentLineRight', + 'indentLineLeft', + 'deleteLeft', + 'deleteRight', + 'deleteWordLeft', + 'deleteWordRight', + 'deleteLineLeft', + 'deleteLineRight', + 'yankKilled', + 'yankPop', + 'undo', + 'redo', + 'transposeAboutCursor', + 'uppercaseNextWord', + 'capitalizeNextWord', + 'lowercaseNextWord', + 'clearScreen' +]; + + +// EXPORTS // + +module.exports = ACTIONS; diff --git a/lib/node_modules/@stdlib/repl/lib/commands.js b/lib/node_modules/@stdlib/repl/lib/commands.js index 6d843e9a2369..88c4a5a63ea9 100644 --- a/lib/node_modules/@stdlib/repl/lib/commands.js +++ b/lib/node_modules/@stdlib/repl/lib/commands.js @@ -48,6 +48,7 @@ var onHelp = require( './commands/help.js' ); var onInfo = require( './commands/info.js' ); var isWorkspace = require( './commands/is_workspace.js' ); var isKeyword = require( './commands/is_keyword.js' ); +var onKeybindings = require( './commands/keybindings.js' ); var onLicense = require( './commands/license_text.js' ); var onLoad = require( './commands/load.js' ); var onLoadWorkspace = require( './commands/load_workspace.js' ); @@ -60,6 +61,7 @@ var onRenameWorkspace = require( './commands/rename_workspace.js' ); var onRerequire = require( './commands/rerequire.js' ); var onRerun = require( './commands/rerun.js' ); var onReset = require( './commands/reset.js' ); +var onSetKeybinding = require( './commands/set_keybinding.js' ); var onSettings = require( './commands/settings.js' ); var onThemes = require( './commands/themes.js' ); var onTutorial = require( './commands/tutorial.js' ); @@ -122,6 +124,7 @@ function commands( repl ) { cmds.push( [ 'info', onInfo( repl, cmds ), false ] ); cmds.push( [ 'isKeyword', isKeyword( repl ), false ] ); cmds.push( [ 'isWorkspace', isWorkspace( repl ), false ] ); + cmds.push( [ 'keybindings', onKeybindings( repl ), false ] ); cmds.push( [ 'license', onLicense( repl ), false ] ); cmds.push( [ 'load', onLoad( repl ), false ] ); cmds.push( [ 'loadWorkspace', onLoadWorkspace( repl ), false ] ); @@ -134,6 +137,7 @@ function commands( repl ) { cmds.push( [ 'rerequire', onRerequire( repl ), false ] ); cmds.push( [ 'rerun', onRerun( repl ), false ] ); cmds.push( [ 'reset', onReset( repl ), false ] ); + cmds.push( [ 'setKeybinding', onSetKeybinding( repl ), false ] ); cmds.push( [ 'settings', onSettings( repl ), false ] ); cmds.push( [ 'themes', onThemes( repl ), false ] ); cmds.push( [ 'tutorial', onTutorial( repl ), false ] ); diff --git a/lib/node_modules/@stdlib/repl/lib/commands/keybindings.js b/lib/node_modules/@stdlib/repl/lib/commands/keybindings.js new file mode 100644 index 000000000000..628d2126b959 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/lib/commands/keybindings.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MODULES // + +var format = require( '@stdlib/string/format' ); +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var ACTIONS = require( './../actions.js' ); + + +// VARIABLES // + +var isAction = contains( ACTIONS ); + + +// MAIN // + +/** +* Returns a callback to be invoked upon calling the `keybindings` command. +* +* @private +* @param {REPL} repl - REPL instance +* @returns {Function} callback +*/ +function command( repl ) { + return onCommand; + + /** + * Returns all (or select) keybindings. + * + * @private + * @param {string} [action] - action name + * @returns {(Object|Array)} keybindings object or a list of keybindings + */ + function onCommand() { + var action; + var nargs; + + nargs = arguments.length; + if ( nargs === 0 ) { + return repl.keybindings(); + } + if ( nargs === 1 ) { + action = arguments[ 0 ]; + if ( !isString( action ) ) { + repl._ostream.write( format( 'Error: invalid argument. First argument must be a string. Value: `%s`.', action ) ); + return; + } + if ( !isAction( action ) ) { + repl._ostream.write( format( 'Error: invalid argument. First argument must be a valid action name. Value: `%s`.', action ) ); + return; + } + return repl.keybindings()[ action ]; + } + } +} + + +// EXPORTS // + +module.exports = command; diff --git a/lib/node_modules/@stdlib/repl/lib/commands/set_keybinding.js b/lib/node_modules/@stdlib/repl/lib/commands/set_keybinding.js new file mode 100644 index 000000000000..6a73f0a9712f --- /dev/null +++ b/lib/node_modules/@stdlib/repl/lib/commands/set_keybinding.js @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MODULES // + +var format = require( '@stdlib/string/format' ); +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var ACTIONS = require( './../actions.js' ); + + +// VARIABLES // + +var isAction = contains( ACTIONS ); + + +// MAIN // + +/** +* Returns a callback to be invoked upon calling the `setKeybinding` command. +* +* @private +* @param {REPL} repl - REPL instance +* @returns {Function} callback +*/ +function command( repl ) { + return onCommand; + + /** + * Sets a keybinding. + * + * @private + * @param {string} action - action name + * @param {Array} [keys] - list of keys + * @returns {void} + */ + function onCommand() { + var action; + var nargs; + var keys; + + nargs = arguments.length; + if ( nargs === 0 ) { + repl._ostream.write( 'Error: invalid argument. First argument must be an action name.\n' ); + return; + } + action = arguments[ 0 ]; + if ( nargs === 1 ) { + if ( !isString( action ) ) { + repl._ostream.write( format( 'Error: invalid argument. First argument must be a string. Value: `%s`.\n', action ) ); + return; + } + if ( !isAction( action ) ) { + repl._ostream.write( format( 'Error: invalid argument. First argument must be a valid action name. Value: `%s`.\n', action ) ); + return; + } + repl._ostream.write( 'Listening for keypresses...' ); + repl._isCapturingKeybinding = true; + repl._targetAction = action; + return; + } + keys = arguments[ 1 ]; + try { + repl.setKeybinding( action, keys ); + repl._ostream.write( format( '\nSuccessfully set keybindings for action `%s`.\n', action ) ); + } catch ( err ) { + repl._ostream.write( format( 'Error: %s\n', err.message ) ); + } + } +} + + +// EXPORTS // + +module.exports = command; diff --git a/lib/node_modules/@stdlib/repl/lib/default_keybindings.js b/lib/node_modules/@stdlib/repl/lib/default_keybindings.js new file mode 100644 index 000000000000..4e5ee984a4d4 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/lib/default_keybindings.js @@ -0,0 +1,338 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-lines */ + +'use strict'; + +// MAIN // + +/** +* Table mapping of REPL actions and their corresponding keybinding triggers. +* +* @private +* @name DEFAULT_KEYBINDINGS +* @type {Object} +*/ +var DEFAULT_KEYBINDINGS = { + 'moveRight': [ + { + 'name': 'right', + 'ctrl': false, + 'shift': false, + 'meta': false + }, + { + 'name': 'f', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'moveLeft': [ + { + 'name': 'left', + 'ctrl': false, + 'shift': false, + 'meta': false + }, + { + 'name': 'b', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'moveWordRight': [ + { + 'name': 'right', + 'ctrl': true, + 'shift': false, + 'meta': false + }, + { + 'name': 'f', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'moveWordLeft': [ + { + 'name': 'left', + 'ctrl': true, + 'shift': false, + 'meta': false + }, + { + 'name': 'b', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'moveBeginning': [ + { + 'name': 'home', + 'ctrl': false, + 'shift': false, + 'meta': false + }, + { + 'name': 'a', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'moveEnd': [ + { + 'name': 'end', + 'ctrl': false, + 'shift': false, + 'meta': false + }, + { + 'name': 'e', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'tab': [ + { + 'name': 't', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'indentLineRight': [ + { + 'name': 'right', + 'ctrl': false, + 'shift': false, + 'meta': true + }, + { + 'name': 'i', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'indentLineLeft': [ + { + 'name': 'left', + 'ctrl': false, + 'shift': false, + 'meta': true + }, + { + 'name': 'i', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'deleteLeft': [ + { + 'name': 'backspace', + 'ctrl': false, + 'shift': false, + 'meta': false + }, + { + 'name': 'h', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'deleteRight': [ + { + 'name': 'delete', + 'ctrl': false, + 'shift': false, + 'meta': false + } + ], + 'deleteWordLeft': [ + { + 'name': 'backspace', + 'ctrl': true, + 'shift': false, + 'meta': false + }, + { + 'name': 'backspace', + 'ctrl': false, + 'shift': false, + 'meta': true + }, + { + 'name': 'w', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'deleteWordRight': [ + { + 'name': 'delete', + 'ctrl': true, + 'shift': false, + 'meta': false + }, + { + 'name': 'delete', + 'ctrl': false, + 'shift': false, + 'meta': true + }, + { + 'name': 'd', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'deleteLineLeft': [ + { + 'name': 'backspace', + 'ctrl': true, + 'shift': true, + 'meta': false + }, + { + 'name': 'u', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'deleteLineRight': [ + { + 'name': 'delete', + 'ctrl': true, + 'shift': true, + 'meta': false + }, + { + 'name': 'k', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'yankKilled': [ + { + 'name': 'y', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'yankPop': [ + { + 'name': 'y', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'undo': [ + { + 'name': '/', + 'ctrl': true, + 'shift': false, + 'meta': false + }, + { + 'name': '-', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'redo': [ + { + 'name': '6', + 'ctrl': true, + 'shift': false, + 'meta': false + }, + { + 'name': '6', + 'ctrl': true, + 'shift': true, + 'meta': false + }, + { + 'name': '^', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'transposeAboutCursor': [ + { + 'name': 't', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ], + 'uppercaseNextWord': [ + { + 'name': 'u', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'capitalizeNextWord': [ + { + 'name': 'c', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'lowercaseNextWord': [ + { + 'name': 'l', + 'ctrl': false, + 'shift': false, + 'meta': true + } + ], + 'clearScreen': [ + { + 'name': 'l', + 'ctrl': true, + 'shift': false, + 'meta': false + } + ] +}; + + +// EXPORTS // + +module.exports = DEFAULT_KEYBINDINGS; diff --git a/lib/node_modules/@stdlib/repl/lib/defaults.js b/lib/node_modules/@stdlib/repl/lib/defaults.js index 0c0789ec801c..5811564cd508 100644 --- a/lib/node_modules/@stdlib/repl/lib/defaults.js +++ b/lib/node_modules/@stdlib/repl/lib/defaults.js @@ -22,7 +22,7 @@ var stdin = require( '@stdlib/streams/node/stdin' ); var stdout = require( '@stdlib/streams/node/stdout' ); -var KEYBINDINGS = require( './keybindings.js' ); +var DEFAULT_KEYBINDINGS = require( './default_keybindings.js' ); var WELCOME = require( './welcome_text.js' ); @@ -80,7 +80,7 @@ function defaults() { 'quiet': false, // REPL keybindings: - 'keybindings': KEYBINDINGS, + 'keybindings': DEFAULT_KEYBINDINGS, // User settings: 'settings': { diff --git a/lib/node_modules/@stdlib/repl/lib/display_prompt.js b/lib/node_modules/@stdlib/repl/lib/display_prompt.js index e4004bbaa5ff..344cede3bbf7 100644 --- a/lib/node_modules/@stdlib/repl/lib/display_prompt.js +++ b/lib/node_modules/@stdlib/repl/lib/display_prompt.js @@ -42,7 +42,7 @@ function displayPrompt( repl, preserveCursor ) { var ws; // Avoid displaying a prompt if the REPL is currently in paging mode... - if ( repl._ostream.isPaging ) { + if ( repl._ostream.isPaging || repl._isCapturingKeybinding ) { return; } len = repl._cmd.length; diff --git a/lib/node_modules/@stdlib/repl/lib/editor_actions.js b/lib/node_modules/@stdlib/repl/lib/editor_actions.js index 3a06e7ae34b1..e8803da827d7 100644 --- a/lib/node_modules/@stdlib/repl/lib/editor_actions.js +++ b/lib/node_modules/@stdlib/repl/lib/editor_actions.js @@ -25,10 +25,10 @@ var readline = require( 'readline' ); var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); var ltrimN = require( '@stdlib/string/left-trim-n' ); +var contains = require( '@stdlib/array/base/assert/contains' ).factory; var uppercase = require( '@stdlib/string/base/uppercase' ); var lowercase = require( '@stdlib/string/base/lowercase' ); var capitalize = require( '@stdlib/string/base/capitalize' ); -var matchKeybindings = require( './match_keybinding.js' ); var parseKey = require( './parse_key.js' ); @@ -61,6 +61,7 @@ var EDITOR_ACTIONS = [ 'lowercaseNextWord', 'clearScreen' ]; +var isEditorAction = contains( EDITOR_ACTIONS ); // MAIN // @@ -523,21 +524,18 @@ setNonEnumerableReadOnly( EditorActions.prototype, 'clearScreen', function clear * @returns {boolean} boolean indicating whether an editor action was triggered */ setNonEnumerableReadOnly( EditorActions.prototype, 'beforeKeypress', function beforeKeypress( data, key ) { - var actionKeys; var inputKeys; + var action; var i; if ( !key ) { return false; } inputKeys = parseKey( key ); - for ( i = 0; i < EDITOR_ACTIONS.length; i++ ) { - actionKeys = this._keybindings[ EDITOR_ACTIONS[ i ] ]; - if ( !actionKeys ) { - continue; // no keybindings configured for the action - } - if ( matchKeybindings( inputKeys, actionKeys ) ) { - this[ EDITOR_ACTIONS[ i ] ](); + for ( i = 0; i < inputKeys.length; i++ ) { + action = this._keybindings.getAction( inputKeys[ i ] ); + if ( action && isEditorAction( action ) ) { + this[ action ](); return true; } } diff --git a/lib/node_modules/@stdlib/repl/lib/help_text.js b/lib/node_modules/@stdlib/repl/lib/help_text.js index 10737246d93c..56a16d5245e2 100644 --- a/lib/node_modules/@stdlib/repl/lib/help_text.js +++ b/lib/node_modules/@stdlib/repl/lib/help_text.js @@ -20,86 +20,95 @@ // MAIN // +// NOTE: Width shouldn't exceed 80 characters. var MSG = [ '', - ' help() Print help text.', - ' help(alias) Print help text for a specified alias.', - ' help(alias.) Print help text for a specified property.', - '', - ' info(alias) Print brief help text for a specified alias.', - ' info(alias.) Print brief help text for a specified property.', - '', - ' example(alias) Run examples for a specified alias.', - ' example(alias.) Run examples for a specified property.', - '', - ' tutorial() List tutorials.', - ' tutorial(name) Run a specified tutorial.', - '', - ' settings() List settings.', - ' settings(name) Return setting value.', - ' settings(name,value) Set a specified setting value.', - '', - ' ans Return the result of the last executed command.', - ' vars() List current workspace variable names.', - ' clearVars() Delete current workspace variables.', - '', - ' workspace() Switch to a specified (possibly new) workspace.', - ' workspaces() List workspace names.', - ' isWorkspace() Assert whether a workspace exists.', - ' varsWorkspace() List workspace variable names.', - ' loadWorkspace() Load variables from a specified workspace.', - ' clearWorkspace() Delete variables in a specified workspace.', - ' deleteWorkspace() Delete a specified workspace.', - ' renameWorkspace() Rename a specified workspace.', - ' currentWorkspace Return the name of the current workspace.', - '', - ' themes() List available color themes.', - ' addTheme(name,value) Add a new color theme.', - ' deleteTheme(name) Delete a specified color theme.', - ' renameTheme(old,new) Rename a specified color theme.', - ' getTheme([name]) Return the current (or a specified) theme\'s color palette.', - '', - ' assignin() Assign a value to a workspace variable.', - ' assignfrom() Read in a value from another workspace.', - '', - ' evalin() Evaluate an expression in a specified workspace.', - '', - ' rerun() Rerun previous commands.', - '', - ' require() Import a module, JSON, or local file.', - ' rerequire() Re-import a module, JSON, or local file.', - ' deeprerequire() Re-import a module and its dependencies.', - ' load() Load and evaluate a JavaScript file line-by-line.', - '', - ' save() Save previous commands to a specified file.', - ' saveStart() Start saving commands to a specified file.', - ' saveStop() Stop saving commands.', - '', - ' presentationStart() Start a REPL presentation.', - ' presentationStop() Stop a REPL presentation.', - '', - ' userDoc() Add user-defined documentation.', - ' clearUserDocs() Clear user-defined documentation.', - '', - ' clearHistory() Clear the REPL history.', - '', - ' clear() Clear the entire REPL screen and scrollback history.', - ' reset() Reset the REPL.', - ' quit() Exit the REPL.', - '', - ' aliases() List namespace contents.', - ' alias2pkg() Convert an alias to a stdlib package name.', - ' pkg2alias() Convert a stdlib package name to an alias.', - ' alias2related() List related aliases.', - ' pkg2related() List related package names.', - ' isKeyword() Assert whether a value is a reserved keyword/alias.', - '', - ' citation() Print how to cite stdlib in publications.', - ' license() Print license information.', - ' copyright() Print copyright information.', - ' contributors() List contributors.', - ' credits() Print credits.', - ' donate() Print donation information.', + ' help() Print help text.', + ' help(alias) Print help text for a specified alias.', + ' help(alias.) Print help text for a specified property.', + '', + ' info(alias) Print brief help text for a specified alias.', + ' info(alias.) Print brief help text for a specified property.', + '', + ' example(alias) Run examples for a specified alias.', + ' example(alias.) Run examples for a specified property.', + '', + ' tutorial() List tutorials.', + ' tutorial(name) Run a specified tutorial.', + '', + ' settings() List settings.', + ' settings(name) Return setting value.', + ' settings(name,value) Set a specified setting value.', + '', + ' ans Return the result of the last executed command.', + ' vars() List current workspace variable names.', + ' clearVars() Delete current workspace variables.', + '', + ' workspace() Switch to a specified (possibly new) workspace.', + ' workspaces() List workspace names.', + ' isWorkspace() Assert whether a workspace exists.', + ' varsWorkspace() List workspace variable names.', + ' loadWorkspace() Load variables from a specified workspace.', + ' clearWorkspace() Delete variables in a specified workspace.', + ' deleteWorkspace() Delete a specified workspace.', + ' renameWorkspace() Rename a specified workspace.', + ' currentWorkspace Return the name of the current workspace.', + '', + ' themes() List available color themes.', + ' addTheme(name,value) Add a new color theme.', + ' deleteTheme(name) Delete a specified color theme.', + ' renameTheme(old,new) Rename a specified color theme.', + ' getTheme([name]) Return the current (or a specified) theme\'s', + ' color palette.', + '', + ' keybindings([name]) List all (or select) keybindings.', + ' setKeybinding(name,[keys]) Set a keybinding.', + '', + ' assignin() Assign a value to a workspace variable.', + ' assignfrom() Read in a value from another workspace.', + '', + ' evalin() Evaluate an expression in a specified', + ' workspace.', + '', + ' rerun() Rerun previous commands.', + '', + ' require() Import a module, JSON, or local file.', + ' rerequire() Re-import a module, JSON, or local file.', + ' deeprerequire() Re-import a module and its dependencies.', + ' load() Load and evaluate a JavaScript file', + ' line-by-line.', + '', + ' save() Save previous commands to a specified file.', + ' saveStart() Start saving commands to a specified file.', + ' saveStop() Stop saving commands.', + '', + ' presentationStart() Start a REPL presentation.', + ' presentationStop() Stop a REPL presentation.', + '', + ' userDoc() Add user-defined documentation.', + ' clearUserDocs() Clear user-defined documentation.', + '', + ' clearHistory() Clear the REPL history.', + '', + ' clear() Clear the entire REPL screen and scrollback', + ' history.', + ' reset() Reset the REPL.', + ' quit() Exit the REPL.', + '', + ' aliases() List namespace contents.', + ' alias2pkg() Convert an alias to a stdlib package name.', + ' pkg2alias() Convert a stdlib package name to an alias.', + ' alias2related() List related aliases.', + ' pkg2related() List related package names.', + ' isKeyword() Assert whether a value is a reserved', + ' keyword/alias.', + '', + ' citation() Print how to cite stdlib in publications.', + ' license() Print license information.', + ' copyright() Print copyright information.', + ' contributors() List contributors.', + ' credits() Print credits.', + ' donate() Print donation information.', '', '' ].join( '\n' ); diff --git a/lib/node_modules/@stdlib/repl/lib/keybindings.js b/lib/node_modules/@stdlib/repl/lib/keybindings.js index e45834a4d360..5dacbad65adf 100644 --- a/lib/node_modules/@stdlib/repl/lib/keybindings.js +++ b/lib/node_modules/@stdlib/repl/lib/keybindings.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -16,334 +16,156 @@ * limitations under the License. */ -/* eslint-disable max-lines */ +/* eslint-disable no-restricted-syntax, no-invalid-this */ 'use strict'; +// MODULES // + +var objectKeys = require( '@stdlib/utils/keys' ); +var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var format = require( '@stdlib/string/format' ); +var deepCopy = require( '@stdlib/utils/copy' ); +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var validateKeybindings = require( './validate_keybindings.js' ); +var ACTIONS = require( './actions.js' ); + + +// VARIABLES // + +var REPLACER = [ 'name', 'ctrl', 'shift', 'meta' ]; +var isAction = contains( ACTIONS ); + + // MAIN // /** -* Table mapping of REPL actions and their corresponding keybinding triggers. +* Keybindings constructor. * -* @name KEYBINDINGS -* @type {Object} +* @private +* @constructor +* @param {Object} keybindings - keybindings object +* @throws {TypeError} each key must correspond to a single action +* @returns {Keybindings} keybindings instance */ -var KEYBINDINGS = { - 'moveRight': [ - { - 'name': 'right', - 'ctrl': false, - 'shift': false, - 'meta': false - }, - { - 'name': 'f', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'moveLeft': [ - { - 'name': 'left', - 'ctrl': false, - 'shift': false, - 'meta': false - }, - { - 'name': 'b', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'moveWordRight': [ - { - 'name': 'right', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': 'f', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'moveWordLeft': [ - { - 'name': 'left', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': 'b', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'moveBeginning': [ - { - 'name': 'home', - 'ctrl': false, - 'shift': false, - 'meta': false - }, - { - 'name': 'a', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'moveEnd': [ - { - 'name': 'end', - 'ctrl': false, - 'shift': false, - 'meta': false - }, - { - 'name': 'e', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'tab': [ - { - 'name': 't', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'indentLineRight': [ - { - 'name': 'right', - 'ctrl': false, - 'shift': false, - 'meta': true - }, - { - 'name': 'i', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'indentLineLeft': [ - { - 'name': 'left', - 'ctrl': false, - 'shift': false, - 'meta': true - }, - { - 'name': 'i', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'deleteLeft': [ - { - 'name': 'backspace', - 'ctrl': false, - 'shift': false, - 'meta': false - }, - { - 'name': 'h', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'deleteRight': [ - { - 'name': 'delete', - 'ctrl': false, - 'shift': false, - 'meta': false - }, - { - 'name': 'd', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'deleteWordLeft': [ - { - 'name': 'backspace', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': 'backspace', - 'ctrl': false, - 'shift': false, - 'meta': true - }, - { - 'name': 'w', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'deleteWordRight': [ - { - 'name': 'delete', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': 'delete', - 'ctrl': false, - 'shift': false, - 'meta': true - }, - { - 'name': 'd', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'deleteLineLeft': [ - { - 'name': 'backspace', - 'ctrl': true, - 'shift': true, - 'meta': false - }, - { - 'name': 'u', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'deleteLineRight': [ - { - 'name': 'delete', - 'ctrl': true, - 'shift': true, - 'meta': false - }, - { - 'name': 'k', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'yankKilled': [ - { - 'name': 'y', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'yankPop': [ - { - 'name': 'y', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'undo': [ - { - 'name': '/', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': '-', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'redo': [ - { - 'name': '6', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': '6', - 'ctrl': true, - 'shift': true, - 'meta': false - }, - { - 'name': '^', - 'ctrl': true, - 'shift': false, - 'meta': false - }, - { - 'name': 'y', - 'ctrl': false, - 'shift': true, - 'meta': false - } - ], - 'transposeAboutCursor': [ - { - 'name': 't', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ], - 'uppercaseNextWord': [ - { - 'name': 'u', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'capitalizeNextWord': [ - { - 'name': 'c', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'lowercaseNextWord': [ - { - 'name': 'l', - 'ctrl': false, - 'shift': false, - 'meta': true - } - ], - 'clearScreen': [ - { - 'name': 'l', - 'ctrl': true, - 'shift': false, - 'meta': false - } - ] -}; +function Keybindings( keybindings ) { + var actions; + var action; + var keys; + var key; + var i; + var j; + + if ( !( this instanceof Keybindings ) ) { + return new Keybindings( keybindings ); + } + + // Initialize internal variables to store keybindings: + this._action2Keys = keybindings; + this._key2Action = {}; + + // Create a hash table of keybindings: + actions = objectKeys( keybindings ); + for ( i = 0; i < actions.length; i++ ) { + action = actions[ i ]; + keys = keybindings[ action ]; + for ( j = 0; j < keys.length; j++ ) { + key = JSON.stringify( keys[ j ], REPLACER ); + if ( hasOwnProp( this._key2Action, key ) ) { + throw new TypeError( format( 'invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`', key ) ); + } + this._key2Action[ key ] = action; + } + } + + return this; +} + +/** +* Sets a keybinding. +* +* @private +* @name set +* @memberof Keybindings.prototype +* @type {Function} +* @param {string} action - action name +* @param {Array} keys - list of keys +* @throws {TypeError} first argument must be a valid action name +* @throws {TypeError} second argument must be an array of valid keys corresponding to a single action +* @returns {void} +*/ +setNonEnumerableReadOnly( Keybindings.prototype, 'set', function set( action, keys ) { + var validatedKeys; + var JSONKeys; + var key; + var obj; + var out; + var err; + var i; + + if ( !isAction( action ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a valid action name. Value: `%s`.', action ) ); + } + + // Validate provided keys: + obj = {}; + out = {}; + obj[ action ] = keys; + err = validateKeybindings( out, obj ); + if ( err ) { + throw err; + } + + // Check for collisions in existing hash table: + JSONKeys = []; + validatedKeys = out[ action ]; + for ( i = 0; i < validatedKeys.length; i++ ) { + key = JSON.stringify( validatedKeys[ i ], REPLACER ); + if ( hasOwnProp( this._key2Action, key ) ) { + throw new TypeError( format( 'invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`', key ) ); + } + JSONKeys.push( key ); + } + // Update hash table: + for ( i = 0; i < JSONKeys.length; i++ ) { + this._key2Action[ JSONKeys[ i ] ] = action; + } + this._action2Keys[ action ] = validatedKeys; +}); + +/** +* Gets action name corresponding to the specified key. +* +* @private +* @name getAction +* @memberof Keybindings.prototype +* @type {Function} +* @param {Object} key +* @returns {(string|null)} action name +*/ +setNonEnumerableReadOnly( Keybindings.prototype, 'getAction', function getAction( key ) { + var serializedKey = JSON.stringify( key, REPLACER ); + if ( !hasOwnProp( this._key2Action, serializedKey ) ) { + return null; + } + return this._key2Action[ serializedKey ]; +}); + +/** +* Lists all keybindings. +* +* @private +* @name list +* @memberof Keybindings.prototype +* @type {Function} +* @returns {Object} keybindings object +*/ +setNonEnumerableReadOnly( Keybindings.prototype, 'list', function list() { + return deepCopy( this._action2Keys ); +}); // EXPORTS // -module.exports = KEYBINDINGS; +module.exports = Keybindings; diff --git a/lib/node_modules/@stdlib/repl/lib/main.js b/lib/node_modules/@stdlib/repl/lib/main.js index b04bcf12da61..33f6595cbc1f 100644 --- a/lib/node_modules/@stdlib/repl/lib/main.js +++ b/lib/node_modules/@stdlib/repl/lib/main.js @@ -16,7 +16,7 @@ * limitations under the License. */ -/* eslint-disable no-restricted-syntax, no-invalid-this, no-underscore-dangle, max-lines, max-lines-per-function */ +/* eslint-disable no-restricted-syntax, no-invalid-this, no-underscore-dangle, max-lines, max-lines-per-function, max-statements */ 'use strict'; @@ -49,6 +49,7 @@ var fifo = require( '@stdlib/utils/fifo' ); var nextTick = require( '@stdlib/utils/next-tick' ); var assign = require( '@stdlib/object/assign' ); var validate = require( './validate.js' ); +var parseKey = require( './parse_key.js' ); var defaults = require( './defaults.js' ); var isSettingName = require( './is_setting_name.js' ); var setAliases = require( './set_aliases.js' ); @@ -63,6 +64,7 @@ var inputPrompt = require( './input_prompt.js' ); var OutputStream = require( './output_stream.js' ); var completerFactory = require( './completer.js' ); var MultilineHandler = require( './multiline_handler.js' ); +var Keybindings = require( './keybindings.js' ); var EditorActions = require( './editor_actions.js' ); var CompleterEngine = require( './completer_engine.js' ); var PreviewCompleter = require( './completer_preview.js' ); @@ -198,7 +200,6 @@ function REPL( options ) { setNonEnumerableReadOnly( this, '_timeout', opts.timeout ); setNonEnumerableReadOnly( this, '_isTTY', opts.isTTY ); setNonEnumerableReadOnly( this, '_sandbox', opts.sandbox ); - setNonEnumerableReadOnly( this, '_keybindings', opts.keybindings ); setNonEnumerableReadOnly( this, '_settings', opts.settings ); setNonEnumerable( this, '_quiet', opts.quiet ); // allow this to be internally toggled @@ -260,6 +261,10 @@ function REPL( options ) { // Initialize an internal variable for setting a command callback: setNonEnumerable( this, '_done', void 0 ); + // Initialize internal variables for setting a keybinding: + setNonEnumerable( this, '_isCapturingKeybinding', false ); + setNonEnumerable( this, '_targetAction', '' ); + // Create a REPL execution context: setNonEnumerable( this, '_context', this.createContext() ); @@ -278,6 +283,9 @@ function REPL( options ) { // Initialize a multi-line handler: setNonEnumerableReadOnly( this, '_multilineHandler', new MultilineHandler( this, this._rli._ttyWrite ) ); + // Initialize keybindings: + setNonEnumerableReadOnly( this, '_keybindings', new Keybindings( opts.keybindings ) ); + // Initialize an editor actions instance: setNonEnumerableReadOnly( this, '_editorActions', new EditorActions( this, this._rli._ttyWrite ) ); @@ -359,6 +367,10 @@ function REPL( options ) { self._ostream.beforeKeypress( data, key ); return; } + if ( self._isCapturingKeybinding ) { + self._captureKeybinding( key ); + return; + } self._autoCloser.beforeKeypress( data, key ); completed = self._previewCompleter.beforeKeypress( data, key ); FLG = self._editorActions.beforeKeypress( data, key ); @@ -548,6 +560,34 @@ setNonEnumerableReadOnly( REPL.prototype, '_prompt', function prompt() { return inputPrompt( this._inputPrompt, this._count ); }); +/** +* Captures the next "keypress" as a keybinding. +* +* @private +* @name _captureKeybinding +* @memberof REPL.prototype +* @type {Function} +* @param {(Object|void)} key - key object +* @returns {void} +*/ +setNonEnumerableReadOnly( REPL.prototype, '_captureKeybinding', function captureKeybinding( key ) { + var parsedKeys; + + if ( !key ) { + return; + } + parsedKeys = parseKey( key ); + try { + this.setKeybinding( this._targetAction, parsedKeys ); + this._ostream.write( format( '\n\nSuccessfully set the following keybindings for action `%s`.\n\n%s\n', this._targetAction, JSON.stringify( parsedKeys, null, 2 ) ) ); + } catch ( err ) { + this._ostream.write( format( '\n\nError: %s\n', err.message ) ); + } + this._isCapturingKeybinding = false; + this._targetAction = ''; + displayPrompt( this, false ); +}); + /** * Returns the current line's prompt length. * @@ -1064,6 +1104,80 @@ setNonEnumerableReadOnly( REPL.prototype, 'deleteTheme', function deleteTheme( n this._syntaxHighlighter.deleteTheme( name ); }); +/** +* Returns all REPL keybindings. +* +* @name keybindings +* @memberof REPL.prototype +* @type {Function} +* @returns {Object} table mapping action names to a list of keybindings +* +* @example +* var debug = require( '@stdlib/streams/node/debug-sink' ); +* +* // Create a new REPL: +* var repl = new REPL({ +* 'output': debug() +* }); +* +* // ... +* +* // Fetch all current keybindings: +* var keybindings = repl.keybindings(); +* +* // ... +* +* // Close the REPL: +* repl.close(); +*/ +setNonEnumerableReadOnly( REPL.prototype, 'keybindings', function keybindings() { + return this._keybindings.list(); +}); + +/** +* Sets a keybinding. +* +* @name setKeybinding +* @memberof REPL.prototype +* @type {Function} +* @param {string} action - action name +* @param {Array} keys - list of keys +* @throws {TypeError} first argument must be a string +* @throws {TypeError} second argument must be an array of valid keys +* @returns {void} +* +* @example +* var debug = require( '@stdlib/streams/node/debug-sink' ); +* +* // Create a new REPL: +* var repl = new REPL({ +* 'output': debug() +* }); +* +* // ... +* +* // Set a keybinding for the `clearScreen` action: +* repl.setKeybinding( 'clearScreen', [ +* { +* 'name': 'l', +* 'ctrl': true, +* 'shift': false, +* 'meta': false +* } +* ]); +* +* // ... +* +* // Close the REPL: +* repl.close(); +*/ +setNonEnumerableReadOnly( REPL.prototype, 'setKeybinding', function setKeybinding( action, keys ) { + if ( !isString( action ) ) { + throw new TypeError( format( 'invalid argument. First argument must be a string. Value: `%s`.', action ) ); + } + this._keybindings.set( action, keys ); +}); + /** * Loads and evaluates a JavaScript file line-by-line. * diff --git a/lib/node_modules/@stdlib/repl/lib/match_keybinding.js b/lib/node_modules/@stdlib/repl/lib/match_keybinding.js deleted file mode 100644 index abe171ad9011..000000000000 --- a/lib/node_modules/@stdlib/repl/lib/match_keybinding.js +++ /dev/null @@ -1,53 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MAIN // - -/** -* Matches a list of possible input keybindings against a list of accepted keybindings. -* -* @private -* @param {Array} inputKeys - list of possible input keys -* @param {Array} acceptedKeys - list of accepted keys -* @returns {boolean} boolean indicating whether the input keys match the accepted keys -*/ -function matchKeybindings( inputKeys, acceptedKeys ) { - var i; - var j; - - for ( i = 0; i < acceptedKeys.length; i++ ) { - for ( j = 0; j < inputKeys.length; j++ ) { - if ( - acceptedKeys[ i ].name === inputKeys[ j ].name && - acceptedKeys[ i ].ctrl === inputKeys[ j ].ctrl && - acceptedKeys[ i ].shift === inputKeys[ j ].shift && - acceptedKeys[ i ].meta === inputKeys[ j ].meta - ) { - return true; - } - } - } - return false; -} - - -// EXPORTS // - -module.exports = matchKeybindings; diff --git a/lib/node_modules/@stdlib/repl/lib/tokenizer.js b/lib/node_modules/@stdlib/repl/lib/tokenizer.js index 188ae75ce857..825aba460bbd 100644 --- a/lib/node_modules/@stdlib/repl/lib/tokenizer.js +++ b/lib/node_modules/@stdlib/repl/lib/tokenizer.js @@ -24,6 +24,7 @@ var parse = require( 'acorn-loose' ).parse; var walk = require( 'acorn-walk' ); +var hasProp = require( '@stdlib/assert/has-property' ); var linkedList = require( '@stdlib/utils/linked-list' ); var contains = require( '@stdlib/array/base/assert/contains' ); var resolveLocalScopes = require( './resolve_local_scopes.js' ); @@ -227,7 +228,7 @@ function tokenizer( line, context ) { for ( i = 0; i < COMMANDS.length; i++ ) { command = COMMANDS[ i ]; if ( node.name === command[ 0 ] ) { - tokens.push( { + tokens.push({ 'value': node.name, 'type': 'command', 'start': node.start, @@ -240,14 +241,14 @@ function tokenizer( line, context ) { identifier = context[ node.name ]; if ( identifier ) { if ( isLiteralType( typeof identifier ) ) { - tokens.push( { + tokens.push({ 'value': node.name, 'type': 'variable', 'start': node.start, 'end': node.end }); } else { - tokens.push( { + tokens.push({ 'value': node.name, 'type': typeof identifier, 'start': node.start, @@ -313,9 +314,13 @@ function tokenizer( line, context ) { } // Case: 'bar' in `foo['bar']` - property already pushed as a string token. Ignore... if ( property.value.type === 'Literal' ) { - obj = obj[ property.value.value ]; - if ( !obj ) { - // Property not found in context: + try { + if ( !hasProp( obj, property.value.value ) ) { + // Property not found in context: + break; + } + obj = obj[ property.value.value ]; + } catch ( error ) { // eslint-disable-line no-unused-vars break; } property = properties.next(); @@ -323,9 +328,13 @@ function tokenizer( line, context ) { } // Case: `foo.bar` - resolve property and push it as a token... if ( property.value.type === 'Identifier' ) { - obj = obj[ property.value.name ]; - if ( !obj ) { - // Property not found in context: + try { + if ( !hasProp( obj, property.value.name ) ) { + // Property not found in context: + break; + } + obj = obj[ property.value.name ]; + } catch ( error ) { // eslint-disable-line no-unused-vars break; } if ( !compute ) { @@ -356,9 +365,13 @@ function tokenizer( line, context ) { // Couldn't compute the internal `MemberExpression` into a definite name: break; } - obj = obj[ computed ]; - if ( !obj ) { - // Property not found in context: + try { + if ( !hasProp( obj, computed ) ) { + // Property not found in context: + break; + } + obj = obj[ computed ]; + } catch ( error ) { // eslint-disable-line no-unused-vars break; } property = properties.next(); diff --git a/lib/node_modules/@stdlib/repl/lib/validate_keybindings.js b/lib/node_modules/@stdlib/repl/lib/validate_keybindings.js index 7398c0bc7ec7..028db55c72ef 100644 --- a/lib/node_modules/@stdlib/repl/lib/validate_keybindings.js +++ b/lib/node_modules/@stdlib/repl/lib/validate_keybindings.js @@ -22,40 +22,15 @@ var isPlainObject = require( '@stdlib/assert/is-plain-object' ); var isArray = require( '@stdlib/assert/is-array' ); -var isString = require( '@stdlib/assert/is-string' ); -var isBoolean = require( '@stdlib/assert/is-boolean' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var format = require( '@stdlib/string/format' ); +var ACTIONS = require( './actions.js' ); // VARIABLES // -var ACTIONS = [ - 'moveRight', - 'moveLeft', - 'moveWordRight', - 'moveWordLeft', - 'moveBeginning', - 'moveEnd', - 'tab', - 'indentLineRight', - 'indentLineLeft', - 'deleteLeft', - 'deleteRight', - 'deleteWordLeft', - 'deleteWordRight', - 'deleteLineLeft', - 'deleteLineRight', - 'yankKilled', - 'yankPop', - 'undo', - 'redo', - 'transposeAboutCursor', - 'uppercaseNextWord', - 'capitalizeNextWord', - 'lowercaseNextWord', - 'clearScreen' -]; var KEY_BOOLEAN_PROPS = [ 'ctrl', 'shift', 'meta' ]; @@ -94,6 +69,7 @@ function validateKey( obj ) { /** * Validates keybindings. * +* @private * @param {Object} opts - destination object * @param {Object} options - settings options * @returns {(Error|null)} error or null @@ -124,7 +100,7 @@ function validate( opts, options ) { if ( err ) { return err; } - out.push( { + out.push({ 'name': o.name, 'ctrl': o.ctrl || false, 'shift': o.shift || false, diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.csv b/lib/node_modules/@stdlib/repl/signature/data/data.csv index 04f473f6110e..1fe0825e5a7e 100644 --- a/lib/node_modules/@stdlib/repl/signature/data/data.csv +++ b/lib/node_modules/@stdlib/repl/signature/data/data.csv @@ -244,6 +244,8 @@ base.cinv,"base.cinv( z )" base.clamp,"base.clamp( v, min, max )" base.clampf,"base.clampf( v, min, max )" base.cmul,"base.cmul( z1, z2 )" +base.cmul.assign,"base.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )" +base.cmul.strided,"base.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )" base.cmulf,"base.cmulf( z1, z2 )" base.cneg,"base.cneg( z )" base.cnegf,"base.cnegf( z )" @@ -1735,26 +1737,26 @@ base.strided.dmax,"base.strided.dmax( N, x, strideX )" base.strided.dmax.ndarray,"base.strided.dmax.ndarray( N, x, strideX, offsetX )" base.strided.dmaxabs,"base.strided.dmaxabs( N, x, strideX )" base.strided.dmaxabs.ndarray,"base.strided.dmaxabs.ndarray( N, x, strideX, offsetX )" -base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N, x, stride )" -base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N, x, stride, offset )" -base.strided.dmaxsorted,"base.strided.dmaxsorted( N, x, stride )" -base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N, x, stride, offset )" +base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N, x, strideX )" +base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )" +base.strided.dmaxsorted,"base.strided.dmaxsorted( N, x, strideX )" +base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )" base.strided.dmean,"base.strided.dmean( N, x, stride )" base.strided.dmean.ndarray,"base.strided.dmean.ndarray( N, x, stride, offset )" -base.strided.dmeankbn,"base.strided.dmeankbn( N, x, stride )" -base.strided.dmeankbn.ndarray,"base.strided.dmeankbn.ndarray( N, x, stride, offset )" -base.strided.dmeankbn2,"base.strided.dmeankbn2( N, x, stride )" -base.strided.dmeankbn2.ndarray,"base.strided.dmeankbn2.ndarray( N, x, stride, offset )" -base.strided.dmeanli,"base.strided.dmeanli( N, x, stride )" -base.strided.dmeanli.ndarray,"base.strided.dmeanli.ndarray( N, x, stride, offset )" +base.strided.dmeankbn,"base.strided.dmeankbn( N, x, strideX )" +base.strided.dmeankbn.ndarray,"base.strided.dmeankbn.ndarray( N, x, strideX, offsetX )" +base.strided.dmeankbn2,"base.strided.dmeankbn2( N, x, strideX )" +base.strided.dmeankbn2.ndarray,"base.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )" +base.strided.dmeanli,"base.strided.dmeanli( N, x, strideX )" +base.strided.dmeanli.ndarray,"base.strided.dmeanli.ndarray( N, x, strideX, offsetX )" base.strided.dmeanlipw,"base.strided.dmeanlipw( N, x, stride )" base.strided.dmeanlipw.ndarray,"base.strided.dmeanlipw.ndarray( N, x, stride, offset )" -base.strided.dmeanors,"base.strided.dmeanors( N, x, stride )" -base.strided.dmeanors.ndarray,"base.strided.dmeanors.ndarray( N, x, stride, offset )" +base.strided.dmeanors,"base.strided.dmeanors( N, x, strideX )" +base.strided.dmeanors.ndarray,"base.strided.dmeanors.ndarray( N, x, strideX, offsetX )" base.strided.dmeanpn,"base.strided.dmeanpn( N, x, stride )" base.strided.dmeanpn.ndarray,"base.strided.dmeanpn.ndarray( N, x, stride, offset )" -base.strided.dmeanpw,"base.strided.dmeanpw( N, x, stride )" -base.strided.dmeanpw.ndarray,"base.strided.dmeanpw.ndarray( N, x, stride, offset )" +base.strided.dmeanpw,"base.strided.dmeanpw( N, x, strideX )" +base.strided.dmeanpw.ndarray,"base.strided.dmeanpw.ndarray( N, x, strideX, offsetX )" base.strided.dmeanstdev,"base.strided.dmeanstdev( N, c, x, strideX, out, strideOut )" base.strided.dmeanstdev.ndarray,"base.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )" base.strided.dmeanstdevpn,"base.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )" @@ -1763,18 +1765,18 @@ base.strided.dmeanvar,"base.strided.dmeanvar( N, c, x, strideX, out, strideOut ) base.strided.dmeanvar.ndarray,"base.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )" base.strided.dmeanvarpn,"base.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )" base.strided.dmeanvarpn.ndarray,"base.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )" -base.strided.dmeanwd,"base.strided.dmeanwd( N, x, stride )" -base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N, x, stride, offset )" -base.strided.dmediansorted,"base.strided.dmediansorted( N, x, stride )" -base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N, x, stride, offset )" +base.strided.dmeanwd,"base.strided.dmeanwd( N, x, strideX )" +base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N, x, strideX, offsetX )" +base.strided.dmediansorted,"base.strided.dmediansorted( N, x, strideX )" +base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N, x, strideX, offsetX )" base.strided.dmidrange,"base.strided.dmidrange( N, x, strideX )" base.strided.dmidrange.ndarray,"base.strided.dmidrange.ndarray( N, x, strideX, offsetX )" base.strided.dmin,"base.strided.dmin( N, x, strideX )" base.strided.dmin.ndarray,"base.strided.dmin.ndarray( N, x, strideX, offsetX )" base.strided.dminabs,"base.strided.dminabs( N, x, strideX )" base.strided.dminabs.ndarray,"base.strided.dminabs.ndarray( N, x, strideX, offsetX )" -base.strided.dminsorted,"base.strided.dminsorted( N, x, stride )" -base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N, x, stride, offset )" +base.strided.dminsorted,"base.strided.dminsorted( N, x, strideX )" +base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N, x, strideX, offsetX )" base.strided.dmskabs,"base.strided.dmskabs( N, x, sx, m, sm, y, sy )" base.strided.dmskabs.ndarray,"base.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )" base.strided.dmskabs2,"base.strided.dmskabs2( N, x, sx, m, sm, y, sy )" @@ -1821,10 +1823,10 @@ base.strided.dnanmeanors,"base.strided.dnanmeanors( N, x, stride )" base.strided.dnanmeanors.ndarray,"base.strided.dnanmeanors.ndarray( N, x, stride, offset )" base.strided.dnanmeanpn,"base.strided.dnanmeanpn( N, x, stride )" base.strided.dnanmeanpn.ndarray,"base.strided.dnanmeanpn.ndarray( N, x, stride, offset )" -base.strided.dnanmeanpw,"base.strided.dnanmeanpw( N, x, stride )" -base.strided.dnanmeanpw.ndarray,"base.strided.dnanmeanpw.ndarray( N, x, stride, offset )" -base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N, x, stride )" -base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N, x, stride, offset )" +base.strided.dnanmeanpw,"base.strided.dnanmeanpw( N, x, strideX )" +base.strided.dnanmeanpw.ndarray,"base.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )" +base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N, x, strideX )" +base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )" base.strided.dnanmin,"base.strided.dnanmin( N, x, strideX )" base.strided.dnanmin.ndarray,"base.strided.dnanmin.ndarray( N, x, strideX, offsetX )" base.strided.dnanminabs,"base.strided.dnanminabs( N, x, strideX )" @@ -1901,26 +1903,26 @@ base.strided.dsdot,"base.strided.dsdot( N, x, strideX, y, strideY )" base.strided.dsdot.ndarray,"base.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" base.strided.dsem,"base.strided.dsem( N, correction, x, stride )" base.strided.dsem.ndarray,"base.strided.dsem.ndarray( N, correction, x, stride, offset )" -base.strided.dsemch,"base.strided.dsemch( N, correction, x, stride )" -base.strided.dsemch.ndarray,"base.strided.dsemch.ndarray( N, correction, x, stride, offset )" +base.strided.dsemch,"base.strided.dsemch( N, correction, x, strideX )" +base.strided.dsemch.ndarray,"base.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )" base.strided.dsempn,"base.strided.dsempn( N, correction, x, stride )" base.strided.dsempn.ndarray,"base.strided.dsempn.ndarray( N, correction, x, stride, offset )" -base.strided.dsemtk,"base.strided.dsemtk( N, correction, x, stride )" -base.strided.dsemtk.ndarray,"base.strided.dsemtk.ndarray( N, correction, x, stride, offset )" -base.strided.dsemwd,"base.strided.dsemwd( N, correction, x, stride )" -base.strided.dsemwd.ndarray,"base.strided.dsemwd.ndarray( N, correction, x, stride, offset )" -base.strided.dsemyc,"base.strided.dsemyc( N, correction, x, stride )" -base.strided.dsemyc.ndarray,"base.strided.dsemyc.ndarray( N, correction, x, stride, offset )" +base.strided.dsemtk,"base.strided.dsemtk( N, correction, x, strideX )" +base.strided.dsemtk.ndarray,"base.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dsemwd,"base.strided.dsemwd( N, correction, x, strideX )" +base.strided.dsemwd.ndarray,"base.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dsemyc,"base.strided.dsemyc( N, correction, x, strideX )" +base.strided.dsemyc.ndarray,"base.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )" base.strided.dsmean,"base.strided.dsmean( N, x, stride )" base.strided.dsmean.ndarray,"base.strided.dsmean.ndarray( N, x, stride, offset )" -base.strided.dsmeanors,"base.strided.dsmeanors( N, x, stride )" -base.strided.dsmeanors.ndarray,"base.strided.dsmeanors.ndarray( N, x, stride, offset )" -base.strided.dsmeanpn,"base.strided.dsmeanpn( N, x, stride )" -base.strided.dsmeanpn.ndarray,"base.strided.dsmeanpn.ndarray( N, x, stride, offset )" -base.strided.dsmeanpw,"base.strided.dsmeanpw( N, x, stride )" -base.strided.dsmeanpw.ndarray,"base.strided.dsmeanpw.ndarray( N, x, stride, offset )" -base.strided.dsmeanwd,"base.strided.dsmeanwd( N, x, stride )" -base.strided.dsmeanwd.ndarray,"base.strided.dsmeanwd.ndarray( N, x, stride, offset )" +base.strided.dsmeanors,"base.strided.dsmeanors( N, x, strideX )" +base.strided.dsmeanors.ndarray,"base.strided.dsmeanors.ndarray( N, x, strideX, offsetX )" +base.strided.dsmeanpn,"base.strided.dsmeanpn( N, x, strideX )" +base.strided.dsmeanpn.ndarray,"base.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )" +base.strided.dsmeanpw,"base.strided.dsmeanpw( N, x, strideX )" +base.strided.dsmeanpw.ndarray,"base.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )" +base.strided.dsmeanwd,"base.strided.dsmeanwd( N, x, strideX )" +base.strided.dsmeanwd.ndarray,"base.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )" base.strided.dsnanmean,"base.strided.dsnanmean( N, x, stride )" base.strided.dsnanmean.ndarray,"base.strided.dsnanmean.ndarray( N, x, stride, offset )" base.strided.dsnanmeanors,"base.strided.dsnanmeanors( N, x, stride )" @@ -1959,26 +1961,26 @@ base.strided.dssumpw,"base.strided.dssumpw( N, x, strideX )" base.strided.dssumpw.ndarray,"base.strided.dssumpw.ndarray( N, x, strideX, offsetX )" base.strided.dstdev,"base.strided.dstdev( N, correction, x, stride )" base.strided.dstdev.ndarray,"base.strided.dstdev.ndarray( N, correction, x, stride, offset )" -base.strided.dstdevch,"base.strided.dstdevch( N, correction, x, stride )" -base.strided.dstdevch.ndarray,"base.strided.dstdevch.ndarray( N, correction, x, stride, offset )" +base.strided.dstdevch,"base.strided.dstdevch( N, correction, x, strideX )" +base.strided.dstdevch.ndarray,"base.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )" base.strided.dstdevpn,"base.strided.dstdevpn( N, correction, x, stride )" base.strided.dstdevpn.ndarray,"base.strided.dstdevpn.ndarray( N, correction, x, stride, offset )" -base.strided.dstdevtk,"base.strided.dstdevtk( N, correction, x, stride )" -base.strided.dstdevtk.ndarray,"base.strided.dstdevtk.ndarray( N, correction, x, stride, offset )" -base.strided.dstdevwd,"base.strided.dstdevwd( N, correction, x, stride )" -base.strided.dstdevwd.ndarray,"base.strided.dstdevwd.ndarray( N, correction, x, stride, offset )" -base.strided.dstdevyc,"base.strided.dstdevyc( N, correction, x, stride )" -base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N, correction, x, stride, offset )" -base.strided.dsum,"base.strided.dsum( N, x, stride )" -base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N, x, stride, offset )" +base.strided.dstdevtk,"base.strided.dstdevtk( N, correction, x, strideX )" +base.strided.dstdevtk.ndarray,"base.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dstdevwd,"base.strided.dstdevwd( N, correction, x, strideX )" +base.strided.dstdevwd.ndarray,"base.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dstdevyc,"base.strided.dstdevyc( N, correction, x, strideX )" +base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dsum,"base.strided.dsum( N, x, strideX )" +base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N, x, strideX, offsetX )" base.strided.dsumkbn,"base.strided.dsumkbn( N, x, strideX )" base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N, x, strideX, offsetX )" -base.strided.dsumkbn2,"base.strided.dsumkbn2( N, x, stride )" -base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N, x, stride, offset )" -base.strided.dsumors,"base.strided.dsumors( N, x, stride )" -base.strided.dsumors.ndarray,"base.strided.dsumors.ndarray( N, x, stride, offset )" -base.strided.dsumpw,"base.strided.dsumpw( N, x, stride )" -base.strided.dsumpw.ndarray,"base.strided.dsumpw.ndarray( N, x, stride, offset )" +base.strided.dsumkbn2,"base.strided.dsumkbn2( N, x, strideX )" +base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )" +base.strided.dsumors,"base.strided.dsumors( N, x, strideX )" +base.strided.dsumors.ndarray,"base.strided.dsumors.ndarray( N, x, strideX, offsetX )" +base.strided.dsumpw,"base.strided.dsumpw( N, x, strideX )" +base.strided.dsumpw.ndarray,"base.strided.dsumpw.ndarray( N, x, strideX, offsetX )" base.strided.dsvariance,"base.strided.dsvariance( N, correction, x, stride )" base.strided.dsvariance.ndarray,"base.strided.dsvariance.ndarray( N, correction, x, stride, offset )" base.strided.dsvariancepn,"base.strided.dsvariancepn( N, correction, x, stride )" @@ -1993,38 +1995,38 @@ base.strided.dtypeResolveStr,"base.strided.dtypeResolveStr( dtype )" base.strided.dtypeStr2Enum,"base.strided.dtypeStr2Enum( dtype )" base.strided.dvariance,"base.strided.dvariance( N, correction, x, stride )" base.strided.dvariance.ndarray,"base.strided.dvariance.ndarray( N, correction, x, stride, offset )" -base.strided.dvariancech,"base.strided.dvariancech( N, correction, x, stride )" -base.strided.dvariancech.ndarray,"base.strided.dvariancech.ndarray( N, correction, x, stride, offset )" +base.strided.dvariancech,"base.strided.dvariancech( N, correction, x, strideX )" +base.strided.dvariancech.ndarray,"base.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )" base.strided.dvariancepn,"base.strided.dvariancepn( N, correction, x, stride )" base.strided.dvariancepn.ndarray,"base.strided.dvariancepn.ndarray( N, correction, x, stride, offset )" -base.strided.dvariancetk,"base.strided.dvariancetk( N, correction, x, stride )" -base.strided.dvariancetk.ndarray,"base.strided.dvariancetk.ndarray( N, correction, x, stride, offset )" -base.strided.dvariancewd,"base.strided.dvariancewd( N, correction, x, stride )" -base.strided.dvariancewd.ndarray,"base.strided.dvariancewd.ndarray( N, correction, x, stride, offset )" -base.strided.dvarianceyc,"base.strided.dvarianceyc( N, correction, x, stride )" -base.strided.dvarianceyc.ndarray,"base.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )" +base.strided.dvariancetk,"base.strided.dvariancetk( N, correction, x, strideX )" +base.strided.dvariancetk.ndarray,"base.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dvariancewd,"base.strided.dvariancewd( N, correction, x, strideX )" +base.strided.dvariancewd.ndarray,"base.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )" +base.strided.dvarianceyc,"base.strided.dvarianceyc( N, correction, x, strideX )" +base.strided.dvarianceyc.ndarray,"base.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )" base.strided.dvarm,"base.strided.dvarm( N, mean, correction, x, stride )" base.strided.dvarm.ndarray,"base.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )" base.strided.dvarmpn,"base.strided.dvarmpn( N, mean, correction, x, stride )" base.strided.dvarmpn.ndarray,"base.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )" -base.strided.dvarmtk,"base.strided.dvarmtk( N, mean, correction, x, stride )" -base.strided.dvarmtk.ndarray,"base.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )" -base.strided.gapx,"base.strided.gapx( N, alpha, x, stride )" -base.strided.gapx.ndarray,"base.strided.gapx.ndarray( N, alpha, x, stride, offset )" -base.strided.gapxsum,"base.strided.gapxsum( N, alpha, x, stride )" -base.strided.gapxsum.ndarray,"base.strided.gapxsum.ndarray( N, alpha, x, stride, offset )" -base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N, alpha, x, stride )" -base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )" -base.strided.gapxsumkbn2,"base.strided.gapxsumkbn2( N, alpha, x, stride )" -base.strided.gapxsumkbn2.ndarray,"base.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )" -base.strided.gapxsumors,"base.strided.gapxsumors( N, alpha, x, stride )" -base.strided.gapxsumors.ndarray,"base.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )" -base.strided.gapxsumpw,"base.strided.gapxsumpw( N, alpha, x, stride )" -base.strided.gapxsumpw.ndarray,"base.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )" +base.strided.dvarmtk,"base.strided.dvarmtk( N, mean, correction, x, strideX )" +base.strided.dvarmtk.ndarray,"base.strided.dvarmtk.ndarray( N, mean, correction, x, strideX, offsetX )" +base.strided.gapx,"base.strided.gapx( N, alpha, x, strideX )" +base.strided.gapx.ndarray,"base.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.gapxsum,"base.strided.gapxsum( N, alpha, x, strideX )" +base.strided.gapxsum.ndarray,"base.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N, alpha, x, strideX )" +base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.gapxsumkbn2,"base.strided.gapxsumkbn2( N, alpha, x, strideX )" +base.strided.gapxsumkbn2.ndarray,"base.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.gapxsumors,"base.strided.gapxsumors( N, alpha, x, strideX )" +base.strided.gapxsumors.ndarray,"base.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.gapxsumpw,"base.strided.gapxsumpw( N, alpha, x, strideX )" +base.strided.gapxsumpw.ndarray,"base.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )" base.strided.gasum,"base.strided.gasum( N, x, stride )" base.strided.gasum.ndarray,"base.strided.gasum.ndarray( N, x, stride, offset )" -base.strided.gasumpw,"base.strided.gasumpw( N, x, stride )" -base.strided.gasumpw.ndarray,"base.strided.gasumpw.ndarray( N, x, stride, offset )" +base.strided.gasumpw,"base.strided.gasumpw( N, x, strideX )" +base.strided.gasumpw.ndarray,"base.strided.gasumpw.ndarray( N, x, strideX, offsetX )" base.strided.gaxpy,"base.strided.gaxpy( N, alpha, x, strideX, y, strideY )" base.strided.gaxpy.ndarray,"base.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )" base.strided.gcopy,"base.strided.gcopy( N, x, strideX, y, strideY )" @@ -2041,26 +2043,26 @@ base.strided.gcusumpw,"base.strided.gcusumpw( N, sum, x, strideX, y, strideY )" base.strided.gcusumpw.ndarray,"base.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )" base.strided.gdot,"base.strided.gdot( N, x, strideX, y, strideY )" base.strided.gdot.ndarray,"base.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" -base.strided.gfill,"base.strided.gfill( N, alpha, x, stride )" -base.strided.gfill.ndarray,"base.strided.gfill.ndarray( N, alpha, x, stride, offset )" -base.strided.gfillBy,"base.strided.gfillBy( N, x, stride, clbk[, thisArg] )" -base.strided.gfillBy.ndarray,"base.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )" +base.strided.gfill,"base.strided.gfill( N, alpha, x, strideX )" +base.strided.gfill.ndarray,"base.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.gfillBy,"base.strided.gfillBy( N, x, strideX, clbk[, thisArg] )" +base.strided.gfillBy.ndarray,"base.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )" base.strided.gnannsumkbn,"base.strided.gnannsumkbn( N, x, strideX, out, strideOut )" base.strided.gnannsumkbn.ndarray,"base.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )" -base.strided.gnansum,"base.strided.gnansum( N, x, stride )" -base.strided.gnansum.ndarray,"base.strided.gnansum.ndarray( N, x, stride, offset )" -base.strided.gnansumkbn,"base.strided.gnansumkbn( N, x, stride )" -base.strided.gnansumkbn.ndarray,"base.strided.gnansumkbn.ndarray( N, x, stride, offset )" -base.strided.gnansumkbn2,"base.strided.gnansumkbn2( N, x, stride )" -base.strided.gnansumkbn2.ndarray,"base.strided.gnansumkbn2.ndarray( N, x, stride, offset )" -base.strided.gnansumors,"base.strided.gnansumors( N, x, stride )" -base.strided.gnansumors.ndarray,"base.strided.gnansumors.ndarray( N, x, stride, offset )" -base.strided.gnansumpw,"base.strided.gnansumpw( N, x, stride )" -base.strided.gnansumpw.ndarray,"base.strided.gnansumpw.ndarray( N, x, stride, offset )" +base.strided.gnansum,"base.strided.gnansum( N, x, strideX )" +base.strided.gnansum.ndarray,"base.strided.gnansum.ndarray( N, x, strideX, offsetX )" +base.strided.gnansumkbn,"base.strided.gnansumkbn( N, x, strideX )" +base.strided.gnansumkbn.ndarray,"base.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )" +base.strided.gnansumkbn2,"base.strided.gnansumkbn2( N, x, strideX )" +base.strided.gnansumkbn2.ndarray,"base.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )" +base.strided.gnansumors,"base.strided.gnansumors( N, x, strideX )" +base.strided.gnansumors.ndarray,"base.strided.gnansumors.ndarray( N, x, strideX, offsetX )" +base.strided.gnansumpw,"base.strided.gnansumpw( N, x, strideX )" +base.strided.gnansumpw.ndarray,"base.strided.gnansumpw.ndarray( N, x, strideX, offsetX )" base.strided.gnrm2,"base.strided.gnrm2( N, x, stride )" base.strided.gnrm2.ndarray,"base.strided.gnrm2.ndarray( N, x, stride, offset )" -base.strided.grev,"base.strided.grev( N, x, stride )" -base.strided.grev.ndarray,"base.strided.grev.ndarray( N, x, stride, offset )" +base.strided.grev,"base.strided.grev( N, x, strideX )" +base.strided.grev.ndarray,"base.strided.grev.ndarray( N, x, strideX, offsetX )" base.strided.gscal,"base.strided.gscal( N, alpha, x, stride )" base.strided.gscal.ndarray,"base.strided.gscal.ndarray( N, alpha, x, stride, offset )" base.strided.gsort2hp,"base.strided.gsort2hp( N, order, x, strideX, y, strideY )" @@ -2077,14 +2079,14 @@ base.strided.gsortsh,"base.strided.gsortsh( N, order, x, stride )" base.strided.gsortsh.ndarray,"base.strided.gsortsh.ndarray( N, order, x, stride, offset )" base.strided.gsum,"base.strided.gsum( N, x, stride )" base.strided.gsum.ndarray,"base.strided.gsum.ndarray( N, x, stride, offset )" -base.strided.gsumkbn,"base.strided.gsumkbn( N, x, stride )" -base.strided.gsumkbn.ndarray,"base.strided.gsumkbn.ndarray( N, x, stride, offset )" -base.strided.gsumkbn2,"base.strided.gsumkbn2( N, x, stride )" -base.strided.gsumkbn2.ndarray,"base.strided.gsumkbn2.ndarray( N, x, stride, offset )" -base.strided.gsumors,"base.strided.gsumors( N, x, stride )" -base.strided.gsumors.ndarray,"base.strided.gsumors.ndarray( N, x, stride, offset )" -base.strided.gsumpw,"base.strided.gsumpw( N, x, stride )" -base.strided.gsumpw.ndarray,"base.strided.gsumpw.ndarray( N, x, stride, offset )" +base.strided.gsumkbn,"base.strided.gsumkbn( N, x, strideX )" +base.strided.gsumkbn.ndarray,"base.strided.gsumkbn.ndarray( N, x, strideX, offsetX )" +base.strided.gsumkbn2,"base.strided.gsumkbn2( N, x, strideX )" +base.strided.gsumkbn2.ndarray,"base.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )" +base.strided.gsumors,"base.strided.gsumors( N, x, strideX )" +base.strided.gsumors.ndarray,"base.strided.gsumors.ndarray( N, x, strideX, offsetX )" +base.strided.gsumpw,"base.strided.gsumpw( N, x, strideX )" +base.strided.gsumpw.ndarray,"base.strided.gsumpw.ndarray( N, x, strideX, offsetX )" base.strided.gswap,"base.strided.gswap( N, x, strideX, y, strideY )" base.strided.gswap.ndarray,"base.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" base.strided.mapBy,"base.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )" @@ -2208,22 +2210,22 @@ base.strided.sabs,"base.strided.sabs( N, x, strideX, y, strideY )" base.strided.sabs.ndarray,"base.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" base.strided.sabs2,"base.strided.sabs2( N, x, strideX, y, strideY )" base.strided.sabs2.ndarray,"base.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" -base.strided.sapx,"base.strided.sapx( N, alpha, x, stride )" -base.strided.sapx.ndarray,"base.strided.sapx.ndarray( N, alpha, x, stride, offset )" -base.strided.sapxsum,"base.strided.sapxsum( N, alpha, x, stride )" -base.strided.sapxsum.ndarray,"base.strided.sapxsum.ndarray( N, alpha, x, stride, offset )" -base.strided.sapxsumkbn,"base.strided.sapxsumkbn( N, alpha, x, stride )" -base.strided.sapxsumkbn.ndarray,"base.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )" -base.strided.sapxsumkbn2,"base.strided.sapxsumkbn2( N, alpha, x, stride )" -base.strided.sapxsumkbn2.ndarray,"base.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )" -base.strided.sapxsumors,"base.strided.sapxsumors( N, alpha, x, stride )" -base.strided.sapxsumors.ndarray,"base.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )" -base.strided.sapxsumpw,"base.strided.sapxsumpw( N, alpha, x, stride )" -base.strided.sapxsumpw.ndarray,"base.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )" +base.strided.sapx,"base.strided.sapx( N, alpha, x, strideX )" +base.strided.sapx.ndarray,"base.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.sapxsum,"base.strided.sapxsum( N, alpha, x, strideX )" +base.strided.sapxsum.ndarray,"base.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.sapxsumkbn,"base.strided.sapxsumkbn( N, alpha, x, strideX )" +base.strided.sapxsumkbn.ndarray,"base.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.sapxsumkbn2,"base.strided.sapxsumkbn2( N, alpha, x, strideX )" +base.strided.sapxsumkbn2.ndarray,"base.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.sapxsumors,"base.strided.sapxsumors( N, alpha, x, strideX )" +base.strided.sapxsumors.ndarray,"base.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )" +base.strided.sapxsumpw,"base.strided.sapxsumpw( N, alpha, x, strideX )" +base.strided.sapxsumpw.ndarray,"base.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )" base.strided.sasum,"base.strided.sasum( N, x, stride )" base.strided.sasum.ndarray,"base.strided.sasum.ndarray( N, x, stride, offset )" -base.strided.sasumpw,"base.strided.sasumpw( N, x, stride )" -base.strided.sasumpw.ndarray,"base.strided.sasumpw.ndarray( N, x, stride, offset )" +base.strided.sasumpw,"base.strided.sasumpw( N, x, strideX )" +base.strided.sasumpw.ndarray,"base.strided.sasumpw.ndarray( N, x, strideX, offsetX )" base.strided.saxpy,"base.strided.saxpy( N, alpha, x, strideX, y, strideY )" base.strided.saxpy.ndarray,"base.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )" base.strided.scbrt,"base.strided.scbrt( N, x, strideX, y, strideY )" @@ -2262,8 +2264,8 @@ base.strided.sdsdot,"base.strided.sdsdot( N, scalar, x, strideX, y, strideY )" base.strided.sdsdot.ndarray,"base.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )" base.strided.sdsmean,"base.strided.sdsmean( N, x, stride )" base.strided.sdsmean.ndarray,"base.strided.sdsmean.ndarray( N, x, stride, offset )" -base.strided.sdsmeanors,"base.strided.sdsmeanors( N, x, stride )" -base.strided.sdsmeanors.ndarray,"base.strided.sdsmeanors.ndarray( N, x, stride, offset )" +base.strided.sdsmeanors,"base.strided.sdsmeanors( N, x, strideX )" +base.strided.sdsmeanors.ndarray,"base.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )" base.strided.sdsnanmean,"base.strided.sdsnanmean( N, x, stride )" base.strided.sdsnanmean.ndarray,"base.strided.sdsnanmean.ndarray( N, x, stride, offset )" base.strided.sdsnanmeanors,"base.strided.sdsnanmeanors( N, x, stride )" @@ -2290,18 +2292,18 @@ base.strided.smax,"base.strided.smax( N, x, strideX )" base.strided.smax.ndarray,"base.strided.smax.ndarray( N, x, strideX, offsetX )" base.strided.smaxabs,"base.strided.smaxabs( N, x, strideX )" base.strided.smaxabs.ndarray,"base.strided.smaxabs.ndarray( N, x, strideX, offsetX )" -base.strided.smaxabssorted,"base.strided.smaxabssorted( N, x, stride )" -base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N, x, stride, offset )" -base.strided.smaxsorted,"base.strided.smaxsorted( N, x, stride )" -base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N, x, stride, offset )" +base.strided.smaxabssorted,"base.strided.smaxabssorted( N, x, strideX )" +base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )" +base.strided.smaxsorted,"base.strided.smaxsorted( N, x, strideX )" +base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N, x, strideX, offsetX )" base.strided.smean,"base.strided.smean( N, x, stride )" base.strided.smean.ndarray,"base.strided.smean.ndarray( N, x, stride, offset )" base.strided.smeankbn,"base.strided.smeankbn( N, x, stride )" base.strided.smeankbn.ndarray,"base.strided.smeankbn.ndarray( N, x, stride, offset )" base.strided.smeankbn2,"base.strided.smeankbn2( N, x, stride )" base.strided.smeankbn2.ndarray,"base.strided.smeankbn2.ndarray( N, x, stride, offset )" -base.strided.smeanli,"base.strided.smeanli( N, x, stride )" -base.strided.smeanli.ndarray,"base.strided.smeanli.ndarray( N, x, stride, offset )" +base.strided.smeanli,"base.strided.smeanli( N, x, strideX )" +base.strided.smeanli.ndarray,"base.strided.smeanli.ndarray( N, x, strideX, offsetX )" base.strided.smeanlipw,"base.strided.smeanlipw( N, x, stride )" base.strided.smeanlipw.ndarray,"base.strided.smeanlipw.ndarray( N, x, stride, offset )" base.strided.smeanors,"base.strided.smeanors( N, x, stride )" @@ -2310,18 +2312,18 @@ base.strided.smeanpn,"base.strided.smeanpn( N, x, stride )" base.strided.smeanpn.ndarray,"base.strided.smeanpn.ndarray( N, x, stride, offset )" base.strided.smeanpw,"base.strided.smeanpw( N, x, stride )" base.strided.smeanpw.ndarray,"base.strided.smeanpw.ndarray( N, x, stride, offset )" -base.strided.smeanwd,"base.strided.smeanwd( N, x, stride )" -base.strided.smeanwd.ndarray,"base.strided.smeanwd.ndarray( N, x, stride, offset )" -base.strided.smediansorted,"base.strided.smediansorted( N, x, stride )" -base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N, x, stride, offset )" +base.strided.smeanwd,"base.strided.smeanwd( N, x, strideX )" +base.strided.smeanwd.ndarray,"base.strided.smeanwd.ndarray( N, x, strideX, offsetX )" +base.strided.smediansorted,"base.strided.smediansorted( N, x, strideX )" +base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N, x, strideX, offsetX )" base.strided.smidrange,"base.strided.smidrange( N, x, strideX )" base.strided.smidrange.ndarray,"base.strided.smidrange.ndarray( N, x, strideX, offsetX )" base.strided.smin,"base.strided.smin( N, x, strideX )" base.strided.smin.ndarray,"base.strided.smin.ndarray( N, x, strideX, offsetX )" base.strided.sminabs,"base.strided.sminabs( N, x, strideX )" base.strided.sminabs.ndarray,"base.strided.sminabs.ndarray( N, x, strideX, offsetX )" -base.strided.sminsorted,"base.strided.sminsorted( N, x, stride )" -base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N, x, stride, offset )" +base.strided.sminsorted,"base.strided.sminsorted( N, x, strideX )" +base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N, x, strideX, offsetX )" base.strided.smskabs,"base.strided.smskabs( N, x, sx, m, sm, y, sy )" base.strided.smskabs.ndarray,"base.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )" base.strided.smskabs2,"base.strided.smskabs2( N, x, sx, m, sm, y, sy )" @@ -2440,12 +2442,12 @@ base.strided.ssqrt,"base.strided.ssqrt( N, x, strideX, y, strideY )" base.strided.ssqrt.ndarray,"base.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" base.strided.sstdev,"base.strided.sstdev( N, correction, x, stride )" base.strided.sstdev.ndarray,"base.strided.sstdev.ndarray( N, correction, x, stride, offset )" -base.strided.sstdevch,"base.strided.sstdevch( N, correction, x, stride )" -base.strided.sstdevch.ndarray,"base.strided.sstdevch.ndarray( N, correction, x, stride, offset )" +base.strided.sstdevch,"base.strided.sstdevch( N, correction, x, strideX )" +base.strided.sstdevch.ndarray,"base.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )" base.strided.sstdevpn,"base.strided.sstdevpn( N, correction, x, stride )" base.strided.sstdevpn.ndarray,"base.strided.sstdevpn.ndarray( N, correction, x, stride, offset )" -base.strided.sstdevtk,"base.strided.sstdevtk( N, correction, x, stride )" -base.strided.sstdevtk.ndarray,"base.strided.sstdevtk.ndarray( N, correction, x, stride, offset )" +base.strided.sstdevtk,"base.strided.sstdevtk( N, correction, x, strideX )" +base.strided.sstdevtk.ndarray,"base.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )" base.strided.sstdevwd,"base.strided.sstdevwd( N, correction, x, stride )" base.strided.sstdevwd.ndarray,"base.strided.sstdevwd.ndarray( N, correction, x, stride, offset )" base.strided.sstdevyc,"base.strided.sstdevyc( N, correction, x, stride )" @@ -2478,16 +2480,16 @@ base.strided.strunc,"base.strided.strunc( N, x, strideX, y, strideY )" base.strided.strunc.ndarray,"base.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )" base.strided.svariance,"base.strided.svariance( N, correction, x, stride )" base.strided.svariance.ndarray,"base.strided.svariance.ndarray( N, correction, x, stride, offset )" -base.strided.svariancech,"base.strided.svariancech( N, correction, x, stride )" -base.strided.svariancech.ndarray,"base.strided.svariancech.ndarray( N, correction, x, stride, offset )" +base.strided.svariancech,"base.strided.svariancech( N, correction, x, strideX )" +base.strided.svariancech.ndarray,"base.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )" base.strided.svariancepn,"base.strided.svariancepn( N, correction, x, stride )" base.strided.svariancepn.ndarray,"base.strided.svariancepn.ndarray( N, correction, x, stride, offset )" -base.strided.svariancetk,"base.strided.svariancetk( N, correction, x, stride )" -base.strided.svariancetk.ndarray,"base.strided.svariancetk.ndarray( N, correction, x, stride, offset )" +base.strided.svariancetk,"base.strided.svariancetk( N, correction, x, strideX )" +base.strided.svariancetk.ndarray,"base.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )" base.strided.svariancewd,"base.strided.svariancewd( N, correction, x, stride )" base.strided.svariancewd.ndarray,"base.strided.svariancewd.ndarray( N, correction, x, stride, offset )" -base.strided.svarianceyc,"base.strided.svarianceyc( N, correction, x, stride )" -base.strided.svarianceyc.ndarray,"base.strided.svarianceyc.ndarray( N, correction, x, stride, offset )" +base.strided.svarianceyc,"base.strided.svarianceyc( N, correction, x, strideX )" +base.strided.svarianceyc.ndarray,"base.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )" base.strided.ternary,"base.strided.ternary( arrays, shape, strides, fcn )" base.strided.ternary.ndarray,"base.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )" base.strided.unary,"base.strided.unary( arrays, shape, strides, fcn )" diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.json b/lib/node_modules/@stdlib/repl/signature/data/data.json index 5774c63cff49..2d2dcaf876ab 100644 --- a/lib/node_modules/@stdlib/repl/signature/data/data.json +++ b/lib/node_modules/@stdlib/repl/signature/data/data.json @@ -1 +1 @@ -[["abs","abs( x[, options] )"],["abs.assign","abs.assign( x, y )"],["acartesianPower","acartesianPower( x, n )"],["acartesianProduct","acartesianProduct( x1, x2 )"],["acartesianSquare","acartesianSquare( x )"],["acronym","acronym( str[, options] )"],["aempty","aempty( length[, dtype] )"],["aemptyLike","aemptyLike( x[, dtype] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length, value[, dtype] )"],["afullLike","afullLike( x[, dtype] )"],["alias2pkg","alias2pkg( alias )"],["alias2related","alias2related( alias )"],["alias2standalone","alias2standalone( alias )"],["aliases","aliases( [namespace] )"],["allocUnsafe","allocUnsafe( size )"],["amskfilter","amskfilter( x, mask )"],["amskput","amskput( x, mask, values[, options] )"],["amskreject","amskreject( x, mask )"],["anans","anans( length[, dtype] 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)"],["isFunction","isFunction( value )"],["isFunctionArray","isFunctionArray( value )"],["isGeneratorObject","isGeneratorObject( value )"],["isGeneratorObjectLike","isGeneratorObjectLike( value )"],["isgzipBuffer","isgzipBuffer( value )"],["isHexString","isHexString( str )"],["isInfinite","isInfinite( value )"],["isInfinite.isPrimitive","isInfinite.isPrimitive( value )"],["isInfinite.isObject","isInfinite.isObject( value )"],["isInheritedProperty","isInheritedProperty( value, property )"],["isInt8Array","isInt8Array( value )"],["isInt16Array","isInt16Array( value )"],["isInt32Array","isInt32Array( value )"],["isInteger","isInteger( value )"],["isInteger.isPrimitive","isInteger.isPrimitive( value )"],["isInteger.isObject","isInteger.isObject( value )"],["isIntegerArray","isIntegerArray( value )"],["isIntegerArray.primitives","isIntegerArray.primitives( value )"],["isIntegerArray.objects","isIntegerArray.objects( value )"],["isIterableLike","isIterableLike( value 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value )"],["isNegativeZero.isPrimitive","isNegativeZero.isPrimitive( value )"],["isNegativeZero.isObject","isNegativeZero.isObject( value )"],["isNodeBuiltin","isNodeBuiltin( str )"],["isNodeDuplexStreamLike","isNodeDuplexStreamLike( value )"],["isNodeReadableStreamLike","isNodeReadableStreamLike( value )"],["isNodeREPL","isNodeREPL()"],["isNodeStreamLike","isNodeStreamLike( value )"],["isNodeTransformStreamLike","isNodeTransformStreamLike( value )"],["isNodeWritableStreamLike","isNodeWritableStreamLike( value )"],["isNonConfigurableProperty","isNonConfigurableProperty( value, property )"],["isNonConfigurablePropertyIn","isNonConfigurablePropertyIn( value, property )"],["isNonEnumerableProperty","isNonEnumerableProperty( value, property )"],["isNonEnumerablePropertyIn","isNonEnumerablePropertyIn( value, property )"],["isNonNegativeFinite","isNonNegativeFinite( value )"],["isNonNegativeFinite.isPrimitive","isNonNegativeFinite.isPrimitive( value 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isSharedArrayBuffer","isSharedArrayBuffer( value )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value )"],["isSlice","isSlice( value )"],["isSnakecase","isSnakecase( value )"],["isSquareMatrix","isSquareMatrix( value )"],["isSquareNumber","isSquareNumber( value )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value )"],["isSquareNumber.isObject","isSquareNumber.isObject( value )"],["isSquareTriangularNumber","isSquareTriangularNumber( value )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value )"],["isStartcase","isStartcase( value )"],["isStrictEqual","isStrictEqual( a, b )"],["isString","isString( value )"],["isString.isPrimitive","isString.isPrimitive( value )"],["isString.isObject","isString.isObject( value )"],["isStringArray","isStringArray( value )"],["isStringArray.primitives","isStringArray.primitives( value )"],["isStringArray.objects","isStringArray.objects( value )"],["isSymbol","isSymbol( value )"],["isSymbolArray","isSymbolArray( value )"],["isSymbolArray.primitives","isSymbolArray.primitives( value )"],["isSymbolArray.objects","isSymbolArray.objects( value )"],["isSymmetricMatrix","isSymmetricMatrix( value )"],["isSyntaxError","isSyntaxError( value )"],["isTriangularNumber","isTriangularNumber( value )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value )"],["isTruthy","isTruthy( value )"],["isTruthyArray","isTruthyArray( value )"],["isTypedArray","isTypedArray( value )"],["isTypedArrayLength","isTypedArrayLength( value )"],["isTypedArrayLike","isTypedArrayLike( value )"],["isTypeError","isTypeError( value )"],["isUint8Array","isUint8Array( value )"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator 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)"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items )"],["iterUntilEach","iterUntilEach( iterator, predicate, fcn[, thisArg] )"],["itervariance","itervariance( iterator[, mean] )"],["iterVercos","iterVercos( iterator )"],["iterVersin","iterVersin( iterator )"],["iterWhileEach","iterWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterZeta","iterZeta( iterator )"],["joinStream","joinStream( [options] )"],["joinStream.factory","joinStream.factory( [options] )"],["joinStream.objectMode","joinStream.objectMode( [options] )"],["kde2d","kde2d( x, y[, options] )"],["kebabcase","kebabcase( str )"],["keyBy","keyBy( collection, fcn[, thisArg] )"],["keyByRight","keyByRight( collection, fcn[, thisArg] )"],["keysIn","keysIn( obj )"],["kruskalTest","kruskalTest( ...x[, options] )"],["kstest","kstest( x, y[, ...params][, options] )"],["last","last( str[, n][, options] )"],["leveneTest","leveneTest( x[, ...y[, options]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start, stop, length[, options] )"],["linspace.assign","linspace.assign( start, stop, out[, options] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a, b[, length] )"],["lowercase","lowercase( str )"],["lowercaseKeys","lowercaseKeys( obj )"],["lowess","lowess( x, y[, options] )"],["lpad","lpad( str, len[, pad] )"],["ltrim","ltrim( str )"],["ltrimN","ltrimN( str, n[, chars] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr, fcn[, thisArg] )"],["map.assign","map.assign( arr, out, fcn[, thisArg] )"],["map2","map2( x, y, fcn[, thisArg] )"],["map2.assign","map2.assign( x, y, out, fcn[, thisArg] )"],["map2d","map2d( arr, fcn[, thisArg] )"],["map2Right","map2Right( x, y, fcn[, thisArg] )"],["map2Right.assign","map2Right.assign( x, y, out, fcn[, thisArg] )"],["map3d","map3d( arr, fcn[, thisArg] )"],["map4d","map4d( arr, fcn[, thisArg] )"],["map5d","map5d( arr, fcn[, thisArg] )"],["mapArguments","mapArguments( fcn, clbk[, thisArg] )"],["mapFun","mapFun( fcn, n[, thisArg] )"],["mapFunAsync","mapFunAsync( fcn, n, [options,] done )"],["mapFunAsync.factory","mapFunAsync.factory( [options,] fcn )"],["mapKeys","mapKeys( obj, transform )"],["mapKeysAsync","mapKeysAsync( obj, [options,] transform, done )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options,] transform )"],["mapReduce","mapReduce( arr, initial, mapper, reducer[, thisArg] )"],["mapReduceRight","mapReduceRight( arr, initial, mapper, reducer[, thisArg] )"],["mapRight","mapRight( arr, fcn[, thisArg] )"],["mapRight.assign","mapRight.assign( arr, out, fcn[, thisArg] )"],["mapValues","mapValues( obj, transform )"],["mapValuesAsync","mapValuesAsync( obj, [options,] transform, done )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options,] transform 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)"],["ndarrayOffset","ndarrayOffset( x )"],["ndarrayOrder","ndarrayOrder( x )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1, dtype2] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype] )"],["ndarrayShape","ndarrayShape( x )"],["ndarrayStride","ndarrayStride( x, dim )"],["ndarrayStrides","ndarrayStrides( x )"],["ndat","ndat( x[, ...indices] )"],["ndempty","ndempty( shape[, options] )"],["ndemptyLike","ndemptyLike( x[, options] )"],["ndfilter","ndfilter( x[, options], predicate[, thisArg] )"],["ndfilterMap","ndfilterMap( x[, options], fcn[, thisArg] )"],["ndforEach","ndforEach( x, fcn[, thisArg] )"],["ndims","ndims( x )"],["ndindex","ndindex( x[, options] )"],["ndindex.free","ndindex.free( id )"],["ndindex.get","ndindex.get( id )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x[, options] )"],["ndindex.linearIndex","ndindex.linearIndex( x[, options] 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dim[, options] )"],["nditerStacks","nditerStacks( x, dims[, options] )"],["nditerSubarrays","nditerSubarrays( x, ndims[, options] )"],["nditerValues","nditerValues( x[, options] )"],["ndmap","ndmap( x[, options], fcn[, thisArg] )"],["ndreject","ndreject( x[, options], predicate[, thisArg] )"],["ndslice","ndslice( x, ...s[, options] )"],["ndsliceAssign","ndsliceAssign( x, y, ...s[, options] )"],["ndsliceDimension","ndsliceDimension( x, dim, slice[, options] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x, dim, start[, options] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x, dim, stop[, options] )"],["ndsliceFrom","ndsliceFrom( x, ...start[, options] )"],["ndsliceTo","ndsliceTo( x, ...stop[, options] )"],["ndzeros","ndzeros( shape[, options] )"],["ndzerosLike","ndzerosLike( x[, options] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str[, fromIndex] )"],["nextTick","nextTick( clbk[, ...args] 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)"],["Object.getOwnPropertyNames","Object.getOwnPropertyNames( obj )"],["Object.getOwnPropertySymbols","Object.getOwnPropertySymbols( obj )"],["Object.getPrototypeOf","Object.getPrototypeOf( obj )"],["Object.hasOwn","Object.hasOwn( obj, p )"],["Object.is","Object.is( value1, value2 )"],["Object.isExtensible","Object.isExtensible( obj )"],["Object.isFrozen","Object.isFrozen( obj )"],["Object.isSealed","Object.isSealed( obj )"],["Object.keys","Object.keys( obj )"],["Object.preventExtensions","Object.preventExtensions( obj )"],["Object.seal","Object.seal( obj )"],["Object.setPrototypeOf","Object.setPrototypeOf( obj, proto )"],["Object.values","Object.values( obj )"],["Object.prototype.toLocaleString","Object.prototype.toLocaleString()"],["Object.prototype.toString","Object.prototype.toString()"],["Object.prototype.valueOf","Object.prototype.valueOf()"],["Object.prototype.hasOwnProperty","Object.prototype.hasOwnProperty( p )"],["Object.prototype.isPrototypeOf","Object.prototype.isPrototypeOf( obj )"],["Object.prototype.propertyIsEnumerable","Object.prototype.propertyIsEnumerable( p )"],["Object.prototype.constructor","Object.prototype.constructor"],["objectEntries","objectEntries( obj )"],["objectEntriesIn","objectEntriesIn( obj )"],["objectFromEntries","objectFromEntries( entries )"],["objectInverse","objectInverse( obj[, options] )"],["objectInverseBy","objectInverseBy( obj, [options,] transform )"],["objectKeys","objectKeys( value )"],["objectValues","objectValues( obj )"],["objectValuesIn","objectValuesIn( obj )"],["omit","omit( obj, keys )"],["omitBy","omitBy( obj, predicate )"],["open","open( path[, flags[, mode]], clbk )"],["open.sync","open.sync( path[, flags[, mode]] )"],["openURL","openURL( url )"],["ordinalize","ordinalize( value[, options] )"],["PACE_BOSTON_HOUSE_PRICES","PACE_BOSTON_HOUSE_PRICES()"],["pad","pad( str, len[, options] )"],["padjust","padjust( pvals, method[, comparisons] 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collection )"],["porterStemmer","porterStemmer( word )"],["prepend","prepend( collection1, collection2 )"],["prevGraphemeClusterBreak","prevGraphemeClusterBreak( str[, fromIndex] )"],["PRIMES_100K","PRIMES_100K()"],["properties","properties( value )"],["propertiesIn","propertiesIn( value )"],["propertyDescriptor","propertyDescriptor( value, property )"],["propertyDescriptorIn","propertyDescriptorIn( value, property )"],["propertyDescriptors","propertyDescriptors( value )"],["propertyDescriptorsIn","propertyDescriptorsIn( value )"],["propertyNames","propertyNames( value )"],["propertyNamesIn","propertyNamesIn( value )"],["propertySymbols","propertySymbols( value )"],["propertySymbolsIn","propertySymbolsIn( value )"],["Proxy","Proxy( target, handlers )"],["Proxy.revocable","Proxy.revocable( target, handlers )"],["push","push( collection, ...items )"],["quarterOfYear","quarterOfYear( [month] )"],["random.array.arcsine","random.array.arcsine( len, a, b[, options] 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search[, position] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs.ndarray","strided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2","strided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs2.ndarray","strided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2By","strided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.abs2By.ndarray","strided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.absBy","strided.absBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.absBy.ndarray","strided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acosBy","strided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.acosBy.ndarray","strided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acoshBy","strided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] 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strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.inv","strided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.inv.ndarray","strided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.mul","strided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.mul.ndarray","strided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.mulBy","strided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.ramp","strided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.ramp.ndarray","strided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.rsqrt","strided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sinBy","strided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sqrt","strided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sqrtBy","strided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sub","strided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.sub.ndarray","strided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.subBy","strided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.trunc","strided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.trunc.ndarray","strided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items 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)"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin[, end]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate[, thisArg] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin[, end]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales[, options]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray )"],["Uint8ClampedArray","Uint8ClampedArray( obj )"],["Uint8ClampedArray","Uint8ClampedArray( buffer[, byteOffset[, length]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src[, map[, thisArg]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0[, element1[, ...elementN]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target, start[, end] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value[, start[, end]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr[, offset] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin[, end]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin[, end]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales[, options]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length )"],["Uint16Array","Uint16Array( typedarray )"],["Uint16Array","Uint16Array( obj )"],["Uint16Array","Uint16Array( buffer[, byteOffset[, length]] )"],["Uint16Array.from","Uint16Array.from( src[, map[, thisArg]] )"],["Uint16Array.of","Uint16Array.of( element0[, element1[, ...elementN]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target, start[, end] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate[, thisArg] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value[, start[, end]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate[, thisArg] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate[, thisArg] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate[, thisArg] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn[, thisArg] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement[, fromIndex] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn[, thisArg] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn[, initialValue] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr[, offset] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin[, end]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate[, thisArg] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin[, end]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales[, options]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length )"],["Uint32Array","Uint32Array( typedarray )"],["Uint32Array","Uint32Array( obj )"],["Uint32Array","Uint32Array( buffer[, byteOffset[, length]] )"],["Uint32Array.from","Uint32Array.from( src[, map[, thisArg]] )"],["Uint32Array.of","Uint32Array.of( element0[, element1[, ...elementN]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target, start[, end] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate[, thisArg] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value[, start[, end]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate[, thisArg] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate[, thisArg] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate[, thisArg] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn[, thisArg] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement[, fromIndex] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn[, thisArg] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn[, initialValue] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr[, offset] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin[, end]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate[, thisArg] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin[, end]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales[, options]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask,] [options] )"],["uncapitalize","uncapitalize( str )"],["uncapitalizeKeys","uncapitalizeKeys( obj )"],["uncurry","uncurry( fcn[, arity, ][thisArg] )"],["uncurryRight","uncurryRight( fcn[, arity, ][thisArg] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data,] [options] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data,] [options] )"],["UnicodeSparkline","UnicodeSparkline( [data,] [options] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data,] [options] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data,] [options] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data,] [options] )"],["unlink","unlink( path, clbk )"],["unlink.sync","unlink.sync( path )"],["unshift","unshift( collection, ...items )"],["until","until( predicate, fcn[, thisArg] )"],["untilAsync","untilAsync( predicate, fcn, done[, thisArg] )"],["untilEach","untilEach( collection, predicate, fcn[, thisArg] )"],["untilEachRight","untilEachRight( collection, predicate, fcn[, thisArg] )"],["unzip","unzip( arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] )"],["wilcoxon","wilcoxon( x[, y][, options] )"],["writableProperties","writableProperties( value )"],["writablePropertiesIn","writablePropertiesIn( value )"],["writablePropertyNames","writablePropertyNames( value )"],["writablePropertyNamesIn","writablePropertyNamesIn( value )"],["writablePropertySymbols","writablePropertySymbols( value )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value )"],["writeFile","writeFile( file, data[, options], clbk )"],["writeFile.sync","writeFile.sync( file, data[, options] )"],["zip","zip( ...arr[, options] )"],["ztest","ztest( x, sigma[, options] )"],["ztest2","ztest2( x, y, sigmax, sigmay[, options] )"]] diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv index 349c10c9e3b3..0d781c300530 100644 --- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv +++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv @@ -244,6 +244,8 @@ base.cinv,"base.cinv( z:Complex128 )" base.clamp,"base.clamp( v:number, min:number, max:number )" base.clampf,"base.clampf( v:number, min:number, max:number )" base.cmul,"base.cmul( z1:Complex128, z2:Complex128 )" +base.cmul.assign,"base.cmul.assign( re1:number, im1:number, re2:number, im2:number, out:ArrayLikeObject, strideOut:integer, offsetOut:integer )" +base.cmul.strided,"base.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, so:integer, oo:integer )" base.cmulf,"base.cmulf( z1:Complex64, z2:Complex64 )" base.cneg,"base.cneg( z )" base.cnegf,"base.cnegf( z )" @@ -1735,26 +1737,26 @@ base.strided.dmax,"base.strided.dmax( N:integer, x:Float64Array, strideX:integer base.strided.dmax.ndarray,"base.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmaxabs,"base.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )" base.strided.dmaxabs.ndarray,"base.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" -base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )" -base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmaxsorted,"base.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )" -base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dmaxsorted,"base.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmean,"base.strided.dmean( N:integer, x:Float64Array, stride:integer )" base.strided.dmean.ndarray,"base.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmeankbn,"base.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )" -base.strided.dmeankbn.ndarray,"base.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmeankbn2,"base.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )" -base.strided.dmeankbn2.ndarray,"base.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmeanli,"base.strided.dmeanli( N:integer, x:Float64Array, stride:integer )" -base.strided.dmeanli.ndarray,"base.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dmeankbn,"base.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmeankbn.ndarray,"base.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dmeankbn2,"base.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmeankbn2.ndarray,"base.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dmeanli,"base.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmeanli.ndarray,"base.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmeanlipw,"base.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )" base.strided.dmeanlipw.ndarray,"base.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmeanors,"base.strided.dmeanors( N:integer, x:Float64Array, stride:integer )" -base.strided.dmeanors.ndarray,"base.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dmeanors,"base.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmeanors.ndarray,"base.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmeanpn,"base.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )" base.strided.dmeanpn.ndarray,"base.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmeanpw,"base.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )" -base.strided.dmeanpw.ndarray,"base.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dmeanpw,"base.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmeanpw.ndarray,"base.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmeanstdev,"base.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )" base.strided.dmeanstdev.ndarray,"base.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )" base.strided.dmeanstdevpn,"base.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )" @@ -1763,18 +1765,18 @@ base.strided.dmeanvar,"base.strided.dmeanvar( N:integer, c:number, x:Float64Arra base.strided.dmeanvar.ndarray,"base.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )" base.strided.dmeanvarpn,"base.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )" base.strided.dmeanvarpn.ndarray,"base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )" -base.strided.dmeanwd,"base.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )" -base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dmediansorted,"base.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )" -base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dmeanwd,"base.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dmediansorted,"base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmidrange,"base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )" base.strided.dmidrange.ndarray,"base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmin,"base.strided.dmin( N:integer, x:Float64Array, strideX:integer )" base.strided.dmin.ndarray,"base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dminabs,"base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )" base.strided.dminabs.ndarray,"base.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" -base.strided.dminsorted,"base.strided.dminsorted( N:integer, x:Float64Array, stride:integer )" -base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dminsorted,"base.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )" +base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmskabs,"base.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )" base.strided.dmskabs.ndarray,"base.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )" base.strided.dmskabs2,"base.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )" @@ -1821,10 +1823,10 @@ base.strided.dnanmeanors,"base.strided.dnanmeanors( N:integer, x:Float64Array, s base.strided.dnanmeanors.ndarray,"base.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" base.strided.dnanmeanpn,"base.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )" base.strided.dnanmeanpn.ndarray,"base.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dnanmeanpw,"base.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )" -base.strided.dnanmeanpw.ndarray,"base.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )" -base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dnanmeanpw,"base.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )" +base.strided.dnanmeanpw.ndarray,"base.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )" +base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dnanmin,"base.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )" base.strided.dnanmin.ndarray,"base.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dnanminabs,"base.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )" @@ -1901,26 +1903,26 @@ base.strided.dsdot,"base.strided.dsdot( N:integer, x:Float32Array, strideX:integ base.strided.dsdot.ndarray,"base.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.dsem,"base.strided.dsem( N:integer, correction:number, x:Float64Array, stride:integer )" base.strided.dsem.ndarray,"base.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsemch,"base.strided.dsemch( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dsemch.ndarray,"base.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" +base.strided.dsemch,"base.strided.dsemch( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dsemch.ndarray,"base.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dsempn,"base.strided.dsempn( N:integer, correction:number, x:Float64Array, stride:integer )" base.strided.dsempn.ndarray,"base.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsemtk,"base.strided.dsemtk( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dsemtk.ndarray,"base.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsemwd,"base.strided.dsemwd( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dsemwd.ndarray,"base.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsemyc,"base.strided.dsemyc( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dsemyc.ndarray,"base.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" +base.strided.dsemtk,"base.strided.dsemtk( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dsemtk.ndarray,"base.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dsemwd,"base.strided.dsemwd( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dsemwd.ndarray,"base.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dsemyc,"base.strided.dsemyc( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dsemyc.ndarray,"base.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dsmean,"base.strided.dsmean( N:integer, x:Float32Array, stride:integer )" base.strided.dsmean.ndarray,"base.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.dsmeanors,"base.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )" -base.strided.dsmeanors.ndarray,"base.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.dsmeanpn,"base.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )" -base.strided.dsmeanpn.ndarray,"base.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.dsmeanpw,"base.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )" -base.strided.dsmeanpw.ndarray,"base.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.dsmeanwd,"base.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )" -base.strided.dsmeanwd.ndarray,"base.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.dsmeanors,"base.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )" +base.strided.dsmeanors.ndarray,"base.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.dsmeanpn,"base.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )" +base.strided.dsmeanpn.ndarray,"base.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.dsmeanpw,"base.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )" +base.strided.dsmeanpw.ndarray,"base.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.dsmeanwd,"base.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )" +base.strided.dsmeanwd.ndarray,"base.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.dsnanmean,"base.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )" base.strided.dsnanmean.ndarray,"base.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" base.strided.dsnanmeanors,"base.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )" @@ -1959,26 +1961,26 @@ base.strided.dssumpw,"base.strided.dssumpw( N:integer, x:Float32Array, strideX:i base.strided.dssumpw.ndarray,"base.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.dstdev,"base.strided.dstdev( N:integer, correction:number, x:Float64Array, stride:integer )" base.strided.dstdev.ndarray,"base.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dstdevch,"base.strided.dstdevch( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dstdevch.ndarray,"base.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" +base.strided.dstdevch,"base.strided.dstdevch( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dstdevch.ndarray,"base.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dstdevpn,"base.strided.dstdevpn( N:integer, correction:number, x:Float64Array, stride:integer )" base.strided.dstdevpn.ndarray,"base.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dstdevtk,"base.strided.dstdevtk( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dstdevtk.ndarray,"base.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dstdevwd,"base.strided.dstdevwd( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dstdevwd.ndarray,"base.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dstdevyc,"base.strided.dstdevyc( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsum,"base.strided.dsum( N:integer, x:Float64Array, stride:integer )" -base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dstdevtk,"base.strided.dstdevtk( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dstdevtk.ndarray,"base.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dstdevwd,"base.strided.dstdevwd( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dstdevwd.ndarray,"base.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dstdevyc,"base.strided.dstdevyc( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dsum,"base.strided.dsum( N:integer, x:Float64Array, strideX:integer )" +base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dsumkbn,"base.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )" base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" -base.strided.dsumkbn2,"base.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )" -base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsumors,"base.strided.dsumors( N:integer, x:Float64Array, stride:integer )" -base.strided.dsumors.ndarray,"base.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" -base.strided.dsumpw,"base.strided.dsumpw( N:integer, x:Float64Array, stride:integer )" -base.strided.dsumpw.ndarray,"base.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )" +base.strided.dsumkbn2,"base.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )" +base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dsumors,"base.strided.dsumors( N:integer, x:Float64Array, strideX:integer )" +base.strided.dsumors.ndarray,"base.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dsumpw,"base.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )" +base.strided.dsumpw.ndarray,"base.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dsvariance,"base.strided.dsvariance( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.dsvariance.ndarray,"base.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" base.strided.dsvariancepn,"base.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, stride:integer )" @@ -1993,38 +1995,38 @@ base.strided.dtypeResolveStr,"base.strided.dtypeResolveStr( dtype:any )" base.strided.dtypeStr2Enum,"base.strided.dtypeStr2Enum( dtype:string )" base.strided.dvariance,"base.strided.dvariance( N:integer, correction:number, x:Float64Array, stride:integer )" base.strided.dvariance.ndarray,"base.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dvariancech,"base.strided.dvariancech( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dvariancech.ndarray,"base.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" +base.strided.dvariancech,"base.strided.dvariancech( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dvariancech.ndarray,"base.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dvariancepn,"base.strided.dvariancepn( N:integer, correction:number, x:Float64Array, stride:integer )" base.strided.dvariancepn.ndarray,"base.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dvariancetk,"base.strided.dvariancetk( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dvariancetk.ndarray,"base.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dvariancewd,"base.strided.dvariancewd( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dvariancewd.ndarray,"base.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dvarianceyc,"base.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, stride:integer )" -base.strided.dvarianceyc.ndarray,"base.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )" +base.strided.dvariancetk,"base.strided.dvariancetk( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dvariancetk.ndarray,"base.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dvariancewd,"base.strided.dvariancewd( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dvariancewd.ndarray,"base.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dvarianceyc,"base.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, strideX:integer )" +base.strided.dvarianceyc.ndarray,"base.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dvarm,"base.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, stride:integer )" base.strided.dvarm.ndarray,"base.strided.dvarm.ndarray( N:integer, mean:number, correction:number, x:Float64Array, stride:integer, offset:integer )" base.strided.dvarmpn,"base.strided.dvarmpn( N:integer, mean:number, correction:number, x:Float64Array, stride:integer )" base.strided.dvarmpn.ndarray,"base.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.dvarmtk,"base.strided.dvarmtk( N:integer, mean:number, correction:number, x:Float64Array, stride:integer )" -base.strided.dvarmtk.ndarray,"base.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, x:Float64Array, stride:integer, offset:integer )" -base.strided.gapx,"base.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" -base.strided.gapx.ndarray,"base.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gapxsum,"base.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" -base.strided.gapxsum.ndarray,"base.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" -base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gapxsumkbn2,"base.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" -base.strided.gapxsumkbn2.ndarray,"base.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gapxsumors,"base.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" -base.strided.gapxsumors.ndarray,"base.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gapxsumpw,"base.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" -base.strided.gapxsumpw.ndarray,"base.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" +base.strided.dvarmtk,"base.strided.dvarmtk( N:integer, mean:number, correction:number, x:Float64Array, strideX:integer )" +base.strided.dvarmtk.ndarray,"base.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.gapx,"base.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )" +base.strided.gapx.ndarray,"base.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gapxsum,"base.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )" +base.strided.gapxsum.ndarray,"base.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )" +base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gapxsumkbn2,"base.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )" +base.strided.gapxsumkbn2.ndarray,"base.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gapxsumors,"base.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )" +base.strided.gapxsumors.ndarray,"base.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gapxsumpw,"base.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )" +base.strided.gapxsumpw.ndarray,"base.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )" base.strided.gasum,"base.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )" base.strided.gasum.ndarray,"base.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gasumpw,"base.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gasumpw.ndarray,"base.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" +base.strided.gasumpw,"base.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gasumpw.ndarray,"base.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" base.strided.gaxpy,"base.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, y:Array|TypedArray, strideY:integer )" base.strided.gaxpy.ndarray,"base.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )" base.strided.gcopy,"base.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, y:ArrayLikeObject, strideY:integer )" @@ -2041,26 +2043,26 @@ base.strided.gcusumpw,"base.strided.gcusumpw( N:integer, sum:number, x:Array|Typ base.strided.gcusumpw.ndarray,"base.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )" base.strided.gdot,"base.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, y:Array|TypedArray, strideY:integer )" base.strided.gdot.ndarray,"base.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )" -base.strided.gfill,"base.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )" -base.strided.gfill.ndarray,"base.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, stride:integer, offset:integer )" -base.strided.gfillBy,"base.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, clbk:Function[, thisArg:any] )" -base.strided.gfillBy.ndarray,"base.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, offset:integer, clbk:Function[, thisArg:any] )" +base.strided.gfill,"base.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )" +base.strided.gfill.ndarray,"base.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer, offsetX:integer )" +base.strided.gfillBy,"base.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, clbk:Function[, thisArg:any] )" +base.strided.gfillBy.ndarray,"base.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )" base.strided.gnannsumkbn,"base.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, out:Array|TypedArray, strideOut:integer )" base.strided.gnannsumkbn.ndarray,"base.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, offsetOut:integer )" -base.strided.gnansum,"base.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gnansum.ndarray,"base.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gnansumkbn,"base.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gnansumkbn.ndarray,"base.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gnansumkbn2,"base.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gnansumkbn2.ndarray,"base.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gnansumors,"base.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gnansumors.ndarray,"base.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gnansumpw,"base.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gnansumpw.ndarray,"base.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" +base.strided.gnansum,"base.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gnansum.ndarray,"base.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gnansumkbn,"base.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gnansumkbn.ndarray,"base.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gnansumkbn2,"base.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gnansumkbn2.ndarray,"base.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gnansumors,"base.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gnansumors.ndarray,"base.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gnansumpw,"base.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gnansumpw.ndarray,"base.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" base.strided.gnrm2,"base.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )" base.strided.gnrm2.ndarray,"base.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.grev,"base.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )" -base.strided.grev.ndarray,"base.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, offset:integer )" +base.strided.grev,"base.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )" +base.strided.grev.ndarray,"base.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, offsetX:integer )" base.strided.gscal,"base.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, stride:integer )" base.strided.gscal.ndarray,"base.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )" base.strided.gsort2hp,"base.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, strideX:integer, y:Array|TypedArray, strideY:integer )" @@ -2077,14 +2079,14 @@ base.strided.gsortsh,"base.strided.gsortsh( N:integer, order:number, x:Array|Typ base.strided.gsortsh.ndarray,"base.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, stride:integer, offset:integer )" base.strided.gsum,"base.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )" base.strided.gsum.ndarray,"base.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gsumkbn,"base.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gsumkbn.ndarray,"base.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gsumkbn2,"base.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gsumkbn2.ndarray,"base.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gsumors,"base.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gsumors.ndarray,"base.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" -base.strided.gsumpw,"base.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )" -base.strided.gsumpw.ndarray,"base.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, offset:integer )" +base.strided.gsumkbn,"base.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gsumkbn.ndarray,"base.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gsumkbn2,"base.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gsumkbn2.ndarray,"base.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gsumors,"base.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gsumors.ndarray,"base.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" +base.strided.gsumpw,"base.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )" +base.strided.gsumpw.ndarray,"base.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, offsetX:integer )" base.strided.gswap,"base.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, y:ArrayLikeObject, strideY:integer )" base.strided.gswap.ndarray,"base.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )" base.strided.mapBy,"base.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, thisArg:any] )" @@ -2208,22 +2210,22 @@ base.strided.sabs,"base.strided.sabs( N:integer, x:Float32Array, strideX:integer base.strided.sabs.ndarray,"base.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.sabs2,"base.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, strideY:integer )" base.strided.sabs2.ndarray,"base.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" -base.strided.sapx,"base.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )" -base.strided.sapx.ndarray,"base.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sapxsum,"base.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )" -base.strided.sapxsum.ndarray,"base.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sapxsumkbn,"base.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, stride:integer )" -base.strided.sapxsumkbn.ndarray,"base.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sapxsumkbn2,"base.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, stride:integer )" -base.strided.sapxsumkbn2.ndarray,"base.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sapxsumors,"base.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, stride:integer )" -base.strided.sapxsumors.ndarray,"base.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sapxsumpw,"base.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, stride:integer )" -base.strided.sapxsumpw.ndarray,"base.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.sapx,"base.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )" +base.strided.sapx.ndarray,"base.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.sapxsum,"base.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )" +base.strided.sapxsum.ndarray,"base.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.sapxsumkbn,"base.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, strideX:integer )" +base.strided.sapxsumkbn.ndarray,"base.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.sapxsumkbn2,"base.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, strideX:integer )" +base.strided.sapxsumkbn2.ndarray,"base.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.sapxsumors,"base.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, strideX:integer )" +base.strided.sapxsumors.ndarray,"base.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.sapxsumpw,"base.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, strideX:integer )" +base.strided.sapxsumpw.ndarray,"base.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.sasum,"base.strided.sasum( N:integer, x:Float32Array, stride:integer )" base.strided.sasum.ndarray,"base.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.sasumpw,"base.strided.sasumpw( N:integer, x:Float32Array, stride:integer )" -base.strided.sasumpw.ndarray,"base.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.sasumpw,"base.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )" +base.strided.sasumpw.ndarray,"base.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.saxpy,"base.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, y:Float32Array, strideY:integer )" base.strided.saxpy.ndarray,"base.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.scbrt,"base.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, strideY:integer )" @@ -2262,8 +2264,8 @@ base.strided.sdsdot,"base.strided.sdsdot( N:integer, scalar:number, x:Float32Arr base.strided.sdsdot.ndarray,"base.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.sdsmean,"base.strided.sdsmean( N:integer, x:Float32Array, stride:integer )" base.strided.sdsmean.ndarray,"base.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.sdsmeanors,"base.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )" -base.strided.sdsmeanors.ndarray,"base.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.sdsmeanors,"base.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )" +base.strided.sdsmeanors.ndarray,"base.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.sdsnanmean,"base.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )" base.strided.sdsnanmean.ndarray,"base.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" base.strided.sdsnanmeanors,"base.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )" @@ -2290,18 +2292,18 @@ base.strided.smax,"base.strided.smax( N:integer, x:Float32Array, strideX:integer base.strided.smax.ndarray,"base.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.smaxabs,"base.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )" base.strided.smaxabs.ndarray,"base.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" -base.strided.smaxabssorted,"base.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )" -base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.smaxsorted,"base.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )" -base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.smaxabssorted,"base.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )" +base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.smaxsorted,"base.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )" +base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.smean,"base.strided.smean( N:integer, x:Float32Array, stride:integer )" base.strided.smean.ndarray,"base.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" base.strided.smeankbn,"base.strided.smeankbn( N:integer, x:Float32Array, stride:integer )" base.strided.smeankbn.ndarray,"base.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" base.strided.smeankbn2,"base.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )" base.strided.smeankbn2.ndarray,"base.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.smeanli,"base.strided.smeanli( N:integer, x:Float32Array, stride:integer )" -base.strided.smeanli.ndarray,"base.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.smeanli,"base.strided.smeanli( N:integer, x:Float32Array, strideX:integer )" +base.strided.smeanli.ndarray,"base.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.smeanlipw,"base.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )" base.strided.smeanlipw.ndarray,"base.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" base.strided.smeanors,"base.strided.smeanors( N:integer, x:Float32Array, stride:integer )" @@ -2310,18 +2312,18 @@ base.strided.smeanpn,"base.strided.smeanpn( N:integer, x:Float32Array, stride:in base.strided.smeanpn.ndarray,"base.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" base.strided.smeanpw,"base.strided.smeanpw( N:integer, x:Float32Array, stride:integer )" base.strided.smeanpw.ndarray,"base.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.smeanwd,"base.strided.smeanwd( N:integer, x:Float32Array, stride:integer )" -base.strided.smeanwd.ndarray,"base.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" -base.strided.smediansorted,"base.strided.smediansorted( N:integer, x:Float32Array, stride:integer )" -base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.smeanwd,"base.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )" +base.strided.smeanwd.ndarray,"base.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" +base.strided.smediansorted,"base.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )" +base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.smidrange,"base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )" base.strided.smidrange.ndarray,"base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.smin,"base.strided.smin( N:integer, x:Float32Array, strideX:integer )" base.strided.smin.ndarray,"base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.sminabs,"base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )" base.strided.sminabs.ndarray,"base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" -base.strided.sminsorted,"base.strided.sminsorted( N:integer, x:Float32Array, stride:integer )" -base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )" +base.strided.sminsorted,"base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )" +base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.smskabs,"base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )" base.strided.smskabs.ndarray,"base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )" base.strided.smskabs2,"base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )" @@ -2440,12 +2442,12 @@ base.strided.ssqrt,"base.strided.ssqrt( N:integer, x:Float32Array, strideX:integ base.strided.ssqrt.ndarray,"base.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.sstdev,"base.strided.sstdev( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.sstdev.ndarray,"base.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sstdevch,"base.strided.sstdevch( N:integer, correction:number, x:Float32Array, stride:integer )" -base.strided.sstdevch.ndarray,"base.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.sstdevch,"base.strided.sstdevch( N:integer, correction:number, x:Float32Array, strideX:integer )" +base.strided.sstdevch.ndarray,"base.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.sstdevpn,"base.strided.sstdevpn( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.sstdevpn.ndarray,"base.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.sstdevtk,"base.strided.sstdevtk( N:integer, correction:number, x:Float32Array, stride:integer )" -base.strided.sstdevtk.ndarray,"base.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.sstdevtk,"base.strided.sstdevtk( N:integer, correction:number, x:Float32Array, strideX:integer )" +base.strided.sstdevtk.ndarray,"base.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.sstdevwd,"base.strided.sstdevwd( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.sstdevwd.ndarray,"base.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" base.strided.sstdevyc,"base.strided.sstdevyc( N:integer, correction:number, x:Float32Array, stride:integer )" @@ -2478,16 +2480,16 @@ base.strided.strunc,"base.strided.strunc( N:integer, x:Float32Array, strideX:int base.strided.strunc.ndarray,"base.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )" base.strided.svariance,"base.strided.svariance( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.svariance.ndarray,"base.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.svariancech,"base.strided.svariancech( N:integer, correction:number, x:Float32Array, stride:integer )" -base.strided.svariancech.ndarray,"base.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.svariancech,"base.strided.svariancech( N:integer, correction:number, x:Float32Array, strideX:integer )" +base.strided.svariancech.ndarray,"base.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.svariancepn,"base.strided.svariancepn( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.svariancepn.ndarray,"base.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.svariancetk,"base.strided.svariancetk( N:integer, correction:number, x:Float32Array, stride:integer )" -base.strided.svariancetk.ndarray,"base.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.svariancetk,"base.strided.svariancetk( N:integer, correction:number, x:Float32Array, strideX:integer )" +base.strided.svariancetk.ndarray,"base.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.svariancewd,"base.strided.svariancewd( N:integer, correction:number, x:Float32Array, stride:integer )" base.strided.svariancewd.ndarray,"base.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" -base.strided.svarianceyc,"base.strided.svarianceyc( N:integer, correction:number, x:Float32Array, stride:integer )" -base.strided.svarianceyc.ndarray,"base.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )" +base.strided.svarianceyc,"base.strided.svarianceyc( N:integer, correction:number, x:Float32Array, strideX:integer )" +base.strided.svarianceyc.ndarray,"base.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, strideX:integer, offsetX:integer )" base.strided.ternary,"base.strided.ternary( arrays:ArrayLikeObject, shape:ArrayLikeObject, strides:ArrayLikeObject, fcn:Function )" base.strided.ternary.ndarray,"base.strided.ternary.ndarray( arrays:ArrayLikeObject, shape:ArrayLikeObject, strides:ArrayLikeObject, offsets:ArrayLikeObject, fcn:Function )" base.strided.unary,"base.strided.unary( arrays:ArrayLikeObject, shape:ArrayLikeObject, strides:ArrayLikeObject, fcn:Function )" diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json index 977c61334136..2fe0fb99a433 100644 --- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json +++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json @@ -1 +1 @@ -[["abs","abs( x:ndarray|ArrayLikeObject|number[, options:Object] )"],["abs.assign","abs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )"],["acartesianPower","acartesianPower( x:ArrayLikeObject, n:integer )"],["acartesianProduct","acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["acartesianSquare","acartesianSquare( x:ArrayLikeObject )"],["acronym","acronym( str:string[, options:Object] )"],["aempty","aempty( length:integer[, dtype:string] )"],["aemptyLike","aemptyLike( x:TypedArray|Array[, dtype:string] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length:integer, value:any[, dtype:string] )"],["afullLike","afullLike( x:TypedArray|Array[, dtype:string] )"],["alias2pkg","alias2pkg( alias:string )"],["alias2related","alias2related( alias:string )"],["alias2standalone","alias2standalone( alias:string )"],["aliases","aliases( [namespace:string] )"],["allocUnsafe","allocUnsafe( size:integer )"],["amskfilter","amskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["amskput","amskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["amskreject","amskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["anans","anans( length:integer[, dtype:string] )"],["anansLike","anansLike( x:TypedArray|Array[, dtype:string] )"],["anova1","anova1( x:Array, factor:Array[, options:Object] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection:Array|TypedArray|Object )"],["anyBy","anyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByAsync","anyByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByAsync.factory","anyByAsync.factory( [options:Object,] predicate:Function )"],["anyByRight","anyByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByRightAsync","anyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options:Object,] predicate:Function )"],["anyInBy","anyInBy( object:Object, predicate:Function[, thisArg:any ] )"],["anyOwnBy","anyOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["aones","aones( length:integer[, dtype:string] )"],["aonesLike","aonesLike( x:TypedArray|Array[, dtype:string] )"],["aoneTo","aoneTo( n:integer[, dtype:string] )"],["aoneToLike","aoneToLike( x:TypedArray|Array[, dtype:string] )"],["APERY","APERY"],["aplace","aplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["append","append( collection1:Array|TypedArray|Object, collection2:Array|TypedArray|Object )"],["aput","aput( x:ArrayLikeObject, indices:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx:integer )"],["ARGV","ARGV"],["array","array( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )"],["array2buffer","array2buffer( arr:Array )"],["array2fancy","array2fancy( x:Array|TypedArray|Object[, options:Object] )"],["array2fancy.factory","array2fancy.factory( [options:Object] )"],["array2fancy.idx","array2fancy.idx( x:Array|TypedArray|Object[, options:Object] )"],["array2iterator","array2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["array2iteratorRight","array2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["ArrayBuffer","ArrayBuffer( size:integer )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr:any )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start:integer[, end:integer]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["arrayCtors","arrayCtors( dtype:string )"],["arrayDataType","arrayDataType( array:any )"],["arrayDataTypes","arrayDataTypes( [kind:string] )"],["ArrayIndex","ArrayIndex( x:Array|TypedArray|Object[, options:Object] )"],["ArrayIndex.free","ArrayIndex.free( id:string )"],["ArrayIndex.get","ArrayIndex.get( id:string )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value:any )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype:any] )"],["arrayNextDataType","arrayNextDataType( [dtype:string] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1:any, dtype2:any] )"],["arraySafeCasts","arraySafeCasts( [dtype:any] )"],["arraySameKindCasts","arraySameKindCasts( [dtype:any] )"],["arrayShape","arrayShape( arr:ArrayLikeObject )"],["arrayStream","arrayStream( src:ArrayLikeObject[, options:Object] )"],["arrayStream.factory","arrayStream.factory( [options:Object] )"],["arrayStream.objectMode","arrayStream.objectMode( src:ArrayLikeObject[, options:Object] )"],["arrayview2iterator","arrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["aslice","aslice( x:ArrayLikeObject[, start:integer[, end:integer]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, options:Object] )"],["azeros","azeros( length:integer[, dtype:string] )"],["azerosLike","azerosLike( x:TypedArray|Array[, dtype:string] )"],["azeroTo","azeroTo( n:integer[, dtype:string] )"],["azeroToLike","azeroToLike( x:TypedArray|Array[, dtype:string] )"],["bartlettTest","bartlettTest( ...x:Array[, options:Object] )"],["base.abs","base.abs( x:number )"],["base.abs2","base.abs2( x:number )"],["base.abs2f","base.abs2f( x:number )"],["base.absdiff","base.absdiff( x:number, y:number )"],["base.absf","base.absf( x:number )"],["base.acartesianPower","base.acartesianPower( x:ArrayLikeObject, n:integer )"],["base.acartesianProduct","base.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["base.acartesianSquare","base.acartesianSquare( x:ArrayLikeObject )"],["base.acos","base.acos( x:number )"],["base.acosd","base.acosd( x:number )"],["base.acosf","base.acosf( x:number )"],["base.acosh","base.acosh( x:number )"],["base.acot","base.acot( x:number )"],["base.acotd","base.acotd( x:number )"],["base.acotf","base.acotf( x:number )"],["base.acoth","base.acoth( x:number )"],["base.acovercos","base.acovercos( x:number )"],["base.acoversin","base.acoversin( x:number )"],["base.acsc","base.acsc( x:number )"],["base.acscd","base.acscd( x:number )"],["base.acscdf","base.acscdf( x:number )"],["base.acscf","base.acscf( x:number )"],["base.acsch","base.acsch( x:number )"],["base.add","base.add( x:number, y:number )"],["base.add3","base.add3( x:number, y:number, z:number )"],["base.add4","base.add4( x:number, y:number, z:number, w:number )"],["base.add5","base.add5( x:number, y:number, z:number, w:number, u:number )"],["base.addf","base.addf( x:number, y:number )"],["base.afilled","base.afilled( value:any, len:integer )"],["base.afilled2d","base.afilled2d( value:any, shape:Array )"],["base.afilled2dBy","base.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )"],["base.afilled3d","base.afilled3d( value:any, shape:Array )"],["base.afilled3dBy","base.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )"],["base.afilled4d","base.afilled4d( value:any, shape:Array )"],["base.afilled4dBy","base.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )"],["base.afilled5d","base.afilled5d( value:any, shape:Array )"],["base.afilled5dBy","base.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )"],["base.afilledBy","base.afilledBy( len:integer, clbk:Function[, thisArg:any] )"],["base.afillednd","base.afillednd( value:any, shape:Array )"],["base.afilledndBy","base.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )"],["base.afilter","base.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )"],["base.afirst","base.afirst( arr:ArrayLikeObject )"],["base.aflatten","base.aflatten( x:Array, shape:Array, colexicographic:boolean )"],["base.aflatten.assign","base.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten2d","base.aflatten2d( x:Array, shape:Array, colexicographic:boolean )"],["base.aflatten2d.assign","base.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten2dBy","base.aflatten2dBy( x:Array, shape:Array, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten2dBy.assign","base.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten3d","base.aflatten3d( x:ArrayLikeObject, shape:Array, colexicographic:boolean )"],["base.aflatten3d.assign","base.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten3dBy","base.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten3dBy.assign","base.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten4d","base.aflatten4d( x:ArrayLikeObject, shape:Array, colexicographic:boolean )"],["base.aflatten4d.assign","base.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten4dBy","base.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten4dBy.assign","base.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten5d","base.aflatten5d( x:ArrayLikeObject, shape:Array, colexicographic:boolean )"],["base.aflatten5d.assign","base.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten5dBy","base.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten5dBy.assign","base.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflattenBy","base.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflattenBy.assign","base.aflattenBy.assign( x:Array, shape:Array, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.afliplr2d","base.afliplr2d( x:ArrayLikeObject )"],["base.afliplr3d","base.afliplr3d( x:ArrayLikeObject )"],["base.afliplr4d","base.afliplr4d( x:ArrayLikeObject )"],["base.afliplr5d","base.afliplr5d( x:ArrayLikeObject )"],["base.aflipud2d","base.aflipud2d( x:ArrayLikeObject )"],["base.aflipud3d","base.aflipud3d( x:ArrayLikeObject )"],["base.aflipud4d","base.aflipud4d( x:ArrayLikeObject )"],["base.aflipud5d","base.aflipud5d( x:ArrayLikeObject )"],["base.ahavercos","base.ahavercos( x:number )"],["base.ahaversin","base.ahaversin( x:number )"],["base.altcase","base.altcase( str:string )"],["base.aones","base.aones( len:integer )"],["base.aones2d","base.aones2d( shape:Array )"],["base.aones3d","base.aones3d( shape:Array )"],["base.aones4d","base.aones4d( shape:Array )"],["base.aones5d","base.aones5d( shape:Array )"],["base.aonesnd","base.aonesnd( shape:Array )"],["base.aoneTo","base.aoneTo( n:number )"],["base.aoneTo.assign","base.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )"],["base.args2multislice","base.args2multislice( args:Array )"],["base.asec","base.asec( x:number )"],["base.asecd","base.asecd( x:number )"],["base.asecdf","base.asecdf( x:number )"],["base.asecf","base.asecf( x:number )"],["base.asech","base.asech( x:number )"],["base.asin","base.asin( x:number )"],["base.asind","base.asind( x:number )"],["base.asindf","base.asindf( x:number )"],["base.asinf","base.asinf( x:number )"],["base.asinh","base.asinh( x:number )"],["base.atan","base.atan( x:number )"],["base.atan2","base.atan2( y:number, x:number )"],["base.atand","base.atand( x:number )"],["base.atanf","base.atanf( x:number )"],["base.atanh","base.atanh( x:number )"],["base.avercos","base.avercos( x:number )"],["base.aversin","base.aversin( x:number )"],["base.azeros","base.azeros( 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x:Float32Array, stride:integer )"],["base.strided.smeanors.ndarray","base.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smeanpn","base.strided.smeanpn( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeanpn.ndarray","base.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smeanpw","base.strided.smeanpw( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeanpw.ndarray","base.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smeanwd","base.strided.smeanwd( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeanwd.ndarray","base.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smediansorted","base.strided.smediansorted( N:integer, x:Float32Array, stride:integer )"],["base.strided.smediansorted.ndarray","base.strided.smediansorted.ndarray( 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om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function 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y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( 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iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, 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start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer 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)"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object 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iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object )"],["iterTrunc10","iterTrunc10( iterator:Object )"],["iterUnion","iterUnion( iter0:Object, ...iterator:Object )"],["iterUnique","iterUnique( iterator:Object )"],["iterUniqueBy","iterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )"],["iterUniqueByHash","iterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterUnitspace","iterUnitspace( start:number[, stop:number] )"],["iterUnshift","iterUnshift( iterator:Object, ...items:any )"],["iterUntilEach","iterUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["itervariance","itervariance( iterator:Object[, mean:number] )"],["iterVercos","iterVercos( iterator:Object )"],["iterVersin","iterVersin( iterator:Object )"],["iterWhileEach","iterWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterZeta","iterZeta( iterator:Object )"],["joinStream","joinStream( [options:Object] )"],["joinStream.factory","joinStream.factory( [options:Object] )"],["joinStream.objectMode","joinStream.objectMode( [options:Object] )"],["kde2d","kde2d( x:Array, y:Array[, options:Object] )"],["kebabcase","kebabcase( str:string )"],["keyBy","keyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keyByRight","keyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keysIn","keysIn( obj:any )"],["kruskalTest","kruskalTest( ...x:Array[, options:Object] )"],["kstest","kstest( x:Array, y:Function|string[, ...params:number][, options:Object] )"],["last","last( str:string[, n:integer][, options:Object] )"],["leveneTest","leveneTest( x:Array[, ...y:Array[, options:Object]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, options:Object] )"],["linspace.assign","linspace.assign( start:number|ComplexLike, stop:number|ComplexLike, out:ArrayLikeObject[, options:Object] 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fcn:Function )"],["mapKeys","mapKeys( obj:Object, transform:Function )"],["mapKeysAsync","mapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options:Object,] transform:Function )"],["mapReduce","mapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapReduceRight","mapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapRight","mapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapRight.assign","mapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapValues","mapValues( obj:Object, transform:Function )"],["mapValuesAsync","mapValuesAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options:Object,] transform:Function 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[month:string|Date|integer[, year:integer]] )"],["minutesInYear","minutesInYear( [value:integer|Date] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source:Object, prop:string, target:Object )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields:Array[, options:Object] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn:Function, arity:integer[, thisArg:any] )"],["nativeClass","nativeClass( value:any )"],["ndarray","ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, shape:ArrayLikeObject, strides:ArrayLikeObject, offset:integer, order:string[, options:Object] 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x:ndarrayLike[, options:Object] )"],["ndarrayMinDataType","ndarrayMinDataType( value:any )"],["ndarrayMostlySafeCasts","ndarrayMostlySafeCasts( [dtype:any] )"],["ndarrayNextDataType","ndarrayNextDataType( [dtype:any] )"],["ndarrayOffset","ndarrayOffset( x:ndarray )"],["ndarrayOrder","ndarrayOrder( x:ndarray )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1:any, dtype2:any] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype:any] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype:any] )"],["ndarrayShape","ndarrayShape( x:ndarray )"],["ndarrayStride","ndarrayStride( x:ndarray, dim:integer )"],["ndarrayStrides","ndarrayStrides( x:ndarray )"],["ndat","ndat( x:ndarray[, ...indices:integer] )"],["ndempty","ndempty( shape:ArrayLikeObject|integer[, options:Object] )"],["ndemptyLike","ndemptyLike( x:ndarray[, options:Object] )"],["ndfilter","ndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndfilterMap","ndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndforEach","ndforEach( x:ndarray, fcn:Function[, thisArg:any] )"],["ndims","ndims( x:ndarray )"],["ndindex","ndindex( x:ndarray[, options:Object] )"],["ndindex.free","ndindex.free( id:string )"],["ndindex.get","ndindex.get( id:string )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x:ndarray[, options:Object] )"],["ndindex.linearIndex","ndindex.linearIndex( x:ndarray[, options:Object] )"],["ndindex.prototype.data","ndindex.prototype.data"],["ndindex.prototype.dtype","ndindex.prototype.dtype"],["ndindex.prototype.id","ndindex.prototype.id"],["ndindex.prototype.isCached","ndindex.prototype.isCached"],["ndindex.prototype.kind","ndindex.prototype.kind"],["ndindex.prototype.type","ndindex.prototype.type"],["ndindex.prototype.toString","ndindex.prototype.toString()"],["ndindex.prototype.toJSON","ndindex.prototype.toJSON()"],["nditerColumnEntries","nditerColumnEntries( x:ndarray[, options:Object] )"],["nditerColumns","nditerColumns( x:ndarray[, options:Object] )"],["nditerEntries","nditerEntries( x:ndarray[, options:Object] )"],["nditerIndices","nditerIndices( shape:Array[, options:Object] )"],["nditerInterleaveSubarrays","nditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )"],["nditerMatrices","nditerMatrices( x:ndarray[, options:Object] )"],["nditerMatrixEntries","nditerMatrixEntries( x:ndarray[, options:Object] )"],["nditerRowEntries","nditerRowEntries( x:ndarray[, options:Object] )"],["nditerRows","nditerRows( x:ndarray[, options:Object] )"],["nditerSelectDimension","nditerSelectDimension( x:ndarray, dim:integer[, options:Object] )"],["nditerStacks","nditerStacks( x:ndarray, dims:Array[, options:Object] )"],["nditerSubarrays","nditerSubarrays( x:ndarray, ndims:integer[, options:Object] )"],["nditerValues","nditerValues( x:ndarray[, options:Object] )"],["ndmap","ndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndreject","ndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndslice","ndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )"],["ndsliceAssign","ndsliceAssign( x:ndarray, y:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )"],["ndsliceDimension","ndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, options:Object] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )"],["ndsliceFrom","ndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )"],["ndsliceTo","ndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )"],["ndzeros","ndzeros( shape:ArrayLikeObject|integer[, options:Object] )"],["ndzerosLike","ndzerosLike( x:ndarray[, options:Object] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str:string[, fromIndex:integer] )"],["nextTick","nextTick( clbk[, ...args] )"],["NIGHTINGALES_ROSE","NIGHTINGALES_ROSE()"],["NINF","NINF"],["NODE_VERSION","NODE_VERSION"],["none","none( collection:Array|TypedArray|Object )"],["noneBy","noneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["noneByAsync","noneByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["noneByAsync.factory","noneByAsync.factory( [options:Object,] predicate:Function )"],["noneByRight","noneByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["noneByRightAsync","noneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["noneByRightAsync.factory","noneByRightAsync.factory( [options:Object,] predicate:Function )"],["noneInBy","noneInBy( object:Object, predicate:Function[, thisArg:any ] )"],["nonEnumerableProperties","nonEnumerableProperties( value:any )"],["nonEnumerablePropertiesIn","nonEnumerablePropertiesIn( value:any )"],["nonEnumerablePropertyNames","nonEnumerablePropertyNames( value:any )"],["nonEnumerablePropertyNamesIn","nonEnumerablePropertyNamesIn( value:any )"],["nonEnumerablePropertySymbols","nonEnumerablePropertySymbols( value:any )"],["nonEnumerablePropertySymbolsIn","nonEnumerablePropertySymbolsIn( value:any )"],["noneOwnBy","noneOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["nonIndexKeys","nonIndexKeys( obj:any )"],["noop","noop()"],["now","now()"],["NUM_CPUS","NUM_CPUS"],["num2words","num2words( value:integer[, options:Object] )"],["Number","Number( value:number )"],["numel","numel( x:ndarray )"],["numelDimension","numelDimension( x:ndarray, dim:integer )"],["numGraphemeClusters","numGraphemeClusters( str:string )"],["Object","Object( value:any )"],["Object.assign","Object.assign( target:Object, ...sources:Object )"],["Object.create","Object.create( prototype:Object, properties:Object )"],["Object.defineProperties","Object.defineProperties( obj:Object, properties:Object )"],["Object.defineProperty","Object.defineProperty( obj:Object, key:string, descriptor:Object )"],["Object.entries","Object.entries( obj:Object )"],["Object.freeze","Object.freeze( obj:Object )"],["Object.getOwnPropertyDescriptor","Object.getOwnPropertyDescriptor( obj:Object, key:string )"],["Object.getOwnPropertyDescriptors","Object.getOwnPropertyDescriptors( obj:Object )"],["Object.getOwnPropertyNames","Object.getOwnPropertyNames( obj:Object )"],["Object.getOwnPropertySymbols","Object.getOwnPropertySymbols( obj:Object )"],["Object.getPrototypeOf","Object.getPrototypeOf( obj:Object )"],["Object.hasOwn","Object.hasOwn( obj:Object, p:string )"],["Object.is","Object.is( value1:any, value2:any )"],["Object.isExtensible","Object.isExtensible( obj:Object )"],["Object.isFrozen","Object.isFrozen( obj:Object )"],["Object.isSealed","Object.isSealed( obj:Object )"],["Object.keys","Object.keys( obj:Object 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][options:Object] )"],["random.streams.t.objectMode","random.streams.t.objectMode( v:number[, options:Object] )"],["random.streams.triangular","random.streams.triangular( a:number, b:number, c:number[, options:Object] )"],["random.streams.triangular.factory","random.streams.triangular.factory( [a:number, b:number, c:number, ][options:Object] )"],["random.streams.triangular.objectMode","random.streams.triangular.objectMode( a:number, b:number, c:number[, options:Object] )"],["random.streams.uniform","random.streams.uniform( a:number, b:number[, options:Object] )"],["random.streams.uniform.factory","random.streams.uniform.factory( [a:number, b:number, ][options:Object] )"],["random.streams.uniform.objectMode","random.streams.uniform.objectMode( a:number, b:number[, options:Object] )"],["random.streams.weibull","random.streams.weibull( k:number, λ:number[, options:Object] )"],["random.streams.weibull.factory","random.streams.weibull.factory( [k:number, λ:number, ][options:Object] 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)"],["random.strided.bernoulli.PRNG","random.strided.bernoulli.PRNG"],["random.strided.bernoulli.seed","random.strided.bernoulli.seed"],["random.strided.bernoulli.seedLength","random.strided.bernoulli.seedLength"],["random.strided.bernoulli.state","random.strided.bernoulli.state"],["random.strided.bernoulli.stateLength","random.strided.bernoulli.stateLength"],["random.strided.bernoulli.byteLength","random.strided.bernoulli.byteLength"],["random.strided.beta","random.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.beta.ndarray","random.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.betaprime","random.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.betaprime.ndarray","random.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.chi","random.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chi.ndarray","random.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chi.factory","random.strided.chi.factory( [options:Object] )"],["random.strided.chi.PRNG","random.strided.chi.PRNG"],["random.strided.chi.seed","random.strided.chi.seed"],["random.strided.chi.seedLength","random.strided.chi.seedLength"],["random.strided.chi.state","random.strided.chi.state"],["random.strided.chi.stateLength","random.strided.chi.stateLength"],["random.strided.chi.byteLength","random.strided.chi.byteLength"],["random.strided.chisquare","random.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chisquare.ndarray","random.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chisquare.factory","random.strided.chisquare.factory( [options:Object] )"],["random.strided.chisquare.PRNG","random.strided.chisquare.PRNG"],["random.strided.chisquare.seed","random.strided.chisquare.seed"],["random.strided.chisquare.seedLength","random.strided.chisquare.seedLength"],["random.strided.chisquare.state","random.strided.chisquare.state"],["random.strided.chisquare.stateLength","random.strided.chisquare.stateLength"],["random.strided.chisquare.byteLength","random.strided.chisquare.byteLength"],["random.strided.cosine","random.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.cosine.ndarray","random.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.discreteUniform","random.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.discreteUniform.ndarray","random.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.exponential","random.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.exponential.ndarray","random.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.exponential.factory","random.strided.exponential.factory( [options:Object] )"],["random.strided.exponential.PRNG","random.strided.exponential.PRNG"],["random.strided.exponential.seed","random.strided.exponential.seed"],["random.strided.exponential.seedLength","random.strided.exponential.seedLength"],["random.strided.exponential.state","random.strided.exponential.state"],["random.strided.exponential.stateLength","random.strided.exponential.stateLength"],["random.strided.exponential.byteLength","random.strided.exponential.byteLength"],["random.strided.gamma","random.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.gamma.ndarray","random.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.geometric","random.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, out:ArrayLikeObject, so:integer )"],["random.strided.geometric.ndarray","random.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, op:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.geometric.factory","random.strided.geometric.factory( [options:Object] )"],["random.strided.geometric.PRNG","random.strided.geometric.PRNG"],["random.strided.geometric.seed","random.strided.geometric.seed"],["random.strided.geometric.seedLength","random.strided.geometric.seedLength"],["random.strided.geometric.state","random.strided.geometric.state"],["random.strided.geometric.stateLength","random.strided.geometric.stateLength"],["random.strided.geometric.byteLength","random.strided.geometric.byteLength"],["random.strided.invgamma","random.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.invgamma.ndarray","random.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.lognormal","random.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.lognormal.ndarray","random.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd","random.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.ndarray","random.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd.normalized","random.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.normalized.ndarray","random.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle","random.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.ndarray","random.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized","random.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized.ndarray","random.strided.minstdShuffle.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937","random.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.ndarray","random.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer )"],["random.strided.rayleigh.ndarray","random.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.rayleigh.factory","random.strided.rayleigh.factory( [options:Object] )"],["random.strided.rayleigh.PRNG","random.strided.rayleigh.PRNG"],["random.strided.rayleigh.seed","random.strided.rayleigh.seed"],["random.strided.rayleigh.seedLength","random.strided.rayleigh.seedLength"],["random.strided.rayleigh.state","random.strided.rayleigh.state"],["random.strided.rayleigh.stateLength","random.strided.rayleigh.stateLength"],["random.strided.rayleigh.byteLength","random.strided.rayleigh.byteLength"],["random.strided.t","random.strided.t( N:integer, v:ArrayLikeObject, sv:integer, out:ArrayLikeObject, so:integer )"],["random.strided.t.ndarray","random.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.t.factory","random.strided.t.factory( [options:Object] )"],["random.strided.t.PRNG","random.strided.t.PRNG"],["random.strided.t.seed","random.strided.t.seed"],["random.strided.t.seedLength","random.strided.t.seedLength"],["random.strided.t.state","random.strided.t.state"],["random.strided.t.stateLength","random.strided.t.stateLength"],["random.strided.t.byteLength","random.strided.t.byteLength"],["random.strided.uniform","random.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.uniform.ndarray","random.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.weibull","random.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.weibull.ndarray","random.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["ranks","ranks( arr:Array[, options:Object] )"],["readDir","readDir( path:string|Buffer, clbk:Function )"],["readDir.sync","readDir.sync( path:string|Buffer )"],["readFile","readFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readFile.sync","readFile.sync( file:string|Buffer|integer[, options:Object|string] )"],["readFileList","readFileList( filepaths:Array[, options:Object|string], clbk:Function )"],["readFileList.sync","readFileList.sync( filepaths:Array[, options:Object|string] )"],["readJSON","readJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readJSON.sync","readJSON.sync( file:string|Buffer|integer[, options:Object|string] )"],["readWASM","readWASM( file:string|Buffer|integer[, options:Object], clbk:Function )"],["readWASM.sync","readWASM.sync( file:string|Buffer|integer[, options:Object] )"],["real","real( z:Complex128 )"],["realarray","realarray( [dtype:string] )"],["realarray","realarray( length:integer[, dtype:string] )"],["realarray","realarray( typedarray:TypedArray[, dtype:string] )"],["realarray","realarray( obj:Object[, dtype:string] )"],["realarray","realarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, dtype:string] )"],["realarrayCtors","realarrayCtors( dtype:string )"],["realarrayDataTypes","realarrayDataTypes()"],["realf","realf( z:Complex64 )"],["realmax","realmax( dtype:string )"],["realmin","realmin( dtype:string )"],["reBasename","reBasename( [platform:string] 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)"],["reDirname.REGEXP","reDirname.REGEXP"],["reDirname.REGEXP_POSIX","reDirname.REGEXP_POSIX"],["reDirname.REGEXP_WIN32","reDirname.REGEXP_WIN32"],["reDirnamePosix","reDirnamePosix()"],["reDirnamePosix.REGEXP","reDirnamePosix.REGEXP"],["reDirnameWindows","reDirnameWindows()"],["reDirnameWindows.REGEXP","reDirnameWindows.REGEXP"],["reduce","reduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, thisArg:any] )"],["reduce2d","reduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, reducer:Function[, thisArg:any] )"],["reduceAsync","reduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] reducer:Function, done:Function )"],["reduceAsync.factory","reduceAsync.factory( [options:Object,] fcn:Function )"],["reduceRight","reduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, thisArg:any] )"],["reduceRightAsync","reduceRightAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] reducer:Function, done:Function )"],["reduceRightAsync.factory","reduceRightAsync.factory( [options:Object,] fcn:Function )"],["reDurationString","reDurationString()"],["reDurationString.REGEXP","reDurationString.REGEXP"],["reEOL","reEOL( [options:Object] )"],["reEOL.REGEXP","reEOL.REGEXP"],["reEOL.REGEXP_CAPTURE","reEOL.REGEXP_CAPTURE"],["reExtendedLengthPath","reExtendedLengthPath()"],["reExtendedLengthPath.REGEXP","reExtendedLengthPath.REGEXP"],["reExtname","reExtname( [platform:string] )"],["reExtname.REGEXP","reExtname.REGEXP"],["reExtname.REGEXP_POSIX","reExtname.REGEXP_POSIX"],["reExtname.REGEXP_WIN32","reExtname.REGEXP_WIN32"],["reExtnamePosix","reExtnamePosix"],["reExtnamePosix.REGEXP","reExtnamePosix.REGEXP"],["reExtnameWindows","reExtnameWindows"],["reExtnameWindows.REGEXP","reExtnameWindows.REGEXP"],["reFilename","reFilename( [platform:string] )"],["reFilename.REGEXP","reFilename.REGEXP"],["reFilename.REGEXP_POSIX","reFilename.REGEXP_POSIX"],["reFilename.REGEXP_WIN32","reFilename.REGEXP_WIN32"],["reFilenamePosix","reFilenamePosix()"],["reFilenamePosix.REGEXP","reFilenamePosix.REGEXP"],["reFilenameWindows","reFilenameWindows()"],["reFilenameWindows.REGEXP","reFilenameWindows.REGEXP"],["reFromString","reFromString( str:string )"],["reFunctionName","reFunctionName()"],["reFunctionName.REGEXP","reFunctionName.REGEXP"],["regexp2json","regexp2json( re:RegExp )"],["reim","reim( z:Complex128 )"],["reimf","reimf( z:Complex64 )"],["rejectArguments","rejectArguments( fcn:Function, predicate:Function[, thisArg:any] )"],["removeFirst","removeFirst( str:string[, n:integer][, options:Object] )"],["removeLast","removeLast( str:string[, n:integer][, options:Object] )"],["removePunctuation","removePunctuation( str:string )"],["removeUTF8BOM","removeUTF8BOM( str:string )"],["removeWords","removeWords( str:string, words:Array[, ignoreCase:boolean] )"],["rename","rename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )"],["rename.sync","rename.sync( oldPath:string|Buffer, newPath:string|Buffer )"],["reNativeFunction","reNativeFunction()"],["reNativeFunction.REGEXP","reNativeFunction.REGEXP"],["reorderArguments","reorderArguments( fcn:Function, indices:Array[, thisArg:any] )"],["repeat","repeat( str:string, n:integer )"],["replace","replace( str:string, search:string|RegExp, newval:string|Function )"],["replaceBefore","replaceBefore( str, search, replacement )"],["reRegExp","reRegExp()"],["reRegExp.REGEXP","reRegExp.REGEXP"],["rescape","rescape( str:string )"],["reSemVer","reSemVer()"],["reSemVer.REGEXP","reSemVer.REGEXP"],["resolveParentPath","resolveParentPath( path:string[, options:Object], clbk:Function )"],["resolveParentPath.sync","resolveParentPath.sync( path:string[, options:Object] )"],["resolveParentPathBy","resolveParentPathBy( path:string[, options:Object], predicate:Function, clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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)"],["scalar2ndarray","scalar2ndarray( value:any[, options:Object] )"],["sdot","sdot( x:ndarray, y:ndarray[, dim:integer] )"],["SECONDS_IN_DAY","SECONDS_IN_DAY"],["SECONDS_IN_HOUR","SECONDS_IN_HOUR"],["SECONDS_IN_MINUTE","SECONDS_IN_MINUTE"],["SECONDS_IN_WEEK","SECONDS_IN_WEEK"],["secondsInMonth","secondsInMonth( [month:string|Date|integer[, year:integer]] )"],["secondsInYear","secondsInYear( [value:integer|Date] )"],["sentencize","sentencize( str:string )"],["seq2slice","seq2slice( str:string, len:integer, strict:boolean )"],["setConfigurableReadOnly","setConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setConfigurableReadOnlyAccessor","setConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setConfigurableReadWriteAccessor","setConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setConfigurableWriteOnlyAccessor","setConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setReadOnly","setReadOnly( obj:Object, prop:string|symbol, value:any )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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)"],["SQRT_EPS","SQRT_EPS"],["SQRT_HALF","SQRT_HALF"],["SQRT_HALF_PI","SQRT_HALF_PI"],["SQRT_PHI","SQRT_PHI"],["SQRT_PI","SQRT_PI"],["SQRT_THREE","SQRT_THREE"],["SQRT_TWO","SQRT_TWO"],["SQRT_TWO_PI","SQRT_TWO_PI"],["SSA_US_BIRTHS_2000_2014","SSA_US_BIRTHS_2000_2014()"],["sswap","sswap( x:ndarray, y:ndarray[, dim:integer] )"],["Stack","Stack()"],["standalone2pkg","standalone2pkg( pkg:string )"],["STANDARD_CARD_DECK","STANDARD_CARD_DECK()"],["startcase","startcase( str:string )"],["startsWith","startsWith( str:string, search:string[, position:integer] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.abs.ndarray","strided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.abs2","strided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, 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clbk:Function[, thisArg:any] )"],["strided.acothBy","strided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy.ndarray","strided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy","strided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy.ndarray","strided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy","strided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy.ndarray","strided.acoversinBy.ndarray( 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)"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ramp.ndarray","strided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.rsqrt","strided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sinBy","strided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrt","strided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sqrtBy","strided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sub","strided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.sub.ndarray","strided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.subBy","strided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.trunc","strided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.trunc.ndarray","strided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["stridedarray2iterator","stridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, offset:integer[, mapFcn:Function[, thisArg:any]] )"],["stridedArrayStream","stridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["stridedArrayStream.factory","stridedArrayStream.factory( [options:Object] 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)"],["base.strided.dmeanstdevpn.ndarray","base.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvar","base.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvar.ndarray","base.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvarpn","base.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvarpn.ndarray","base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanwd","base.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmeanwd.ndarray","base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmediansorted","base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmediansorted.ndarray","base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmidrange","base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmidrange.ndarray","base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmin","base.strided.dmin( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmin.ndarray","base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminabs","base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminabs.ndarray","base.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminsorted","base.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminsorted.ndarray","base.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmskabs","base.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskabs.ndarray","base.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskabs2","base.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskabs2.ndarray","base.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskcbrt","base.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskcbrt.ndarray","base.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskceil","base.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskceil.ndarray","base.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskdeg2rad","base.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskdeg2rad.ndarray","base.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, 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strideX:integer, offsetX:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmean","base.strided.snanmean( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmean.ndarray","base.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanors","base.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanors.ndarray","base.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanpn","base.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanpn.ndarray","base.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanwd","base.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanwd.ndarray","base.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmin","base.strided.snanmin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmin.ndarray","base.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanminabs","base.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanminabs.ndarray","base.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmskmax","base.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmax.ndarray","base.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskmin","base.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmin.ndarray","base.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskrange","base.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskrange.ndarray","base.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanrange","base.strided.snanrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanrange.ndarray","base.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanstdev","base.strided.snanstdev( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdev.ndarray","base.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevch","base.strided.snanstdevch( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevch.ndarray","base.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevpn","base.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevpn.ndarray","base.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevtk","base.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevtk.ndarray","base.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevwd","base.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, stride:integer 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)"],["isNonPositiveFinite.isObject","isNonPositiveFinite.isObject( value:any )"],["isNonPositiveInteger","isNonPositiveInteger( value:any )"],["isNonPositiveInteger.isPrimitive","isNonPositiveInteger.isPrimitive( value:any )"],["isNonPositiveInteger.isObject","isNonPositiveInteger.isObject( value:any )"],["isNonPositiveIntegerArray","isNonPositiveIntegerArray( value:any )"],["isNonPositiveIntegerArray.primitives","isNonPositiveIntegerArray.primitives( value:any )"],["isNonPositiveIntegerArray.objects","isNonPositiveIntegerArray.objects( value:any )"],["isNonPositiveNumber","isNonPositiveNumber( value:any )"],["isNonPositiveNumber.isPrimitive","isNonPositiveNumber.isPrimitive( value:any )"],["isNonPositiveNumber.isObject","isNonPositiveNumber.isObject( value:any )"],["isNonPositiveNumberArray","isNonPositiveNumberArray( value:any )"],["isNonPositiveNumberArray.primitives","isNonPositiveNumberArray.primitives( value:any 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)"],["isPersymmetricMatrix","isPersymmetricMatrix( value:any )"],["isPlainObject","isPlainObject( value:any )"],["isPlainObjectArray","isPlainObjectArray( value:any )"],["isPositiveFinite","isPositiveFinite( value:any )"],["isPositiveFinite.isPrimitive","isPositiveFinite.isPrimitive( value:any )"],["isPositiveFinite.isObject","isPositiveFinite.isObject( value:any )"],["isPositiveInteger","isPositiveInteger( value:any )"],["isPositiveInteger.isPrimitive","isPositiveInteger.isPrimitive( value:any )"],["isPositiveInteger.isObject","isPositiveInteger.isObject( value:any )"],["isPositiveIntegerArray","isPositiveIntegerArray( value:any )"],["isPositiveIntegerArray.primitives","isPositiveIntegerArray.primitives( value:any )"],["isPositiveIntegerArray.objects","isPositiveIntegerArray.objects( value:any )"],["isPositiveNumber","isPositiveNumber( value:any )"],["isPositiveNumber.isPrimitive","isPositiveNumber.isPrimitive( value:any )"],["isPositiveNumber.isObject","isPositiveNumber.isObject( value:any )"],["isPositiveNumberArray","isPositiveNumberArray( value:any )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value:any )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value:any )"],["isPositiveZero","isPositiveZero( value:any )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value:any )"],["isPositiveZero.isObject","isPositiveZero.isObject( value:any )"],["isPrime","isPrime( value:any )"],["isPrime.isPrimitive","isPrime.isPrimitive( value:any )"],["isPrime.isObject","isPrime.isObject( value:any )"],["isPrimitive","isPrimitive( value:any )"],["isPrimitiveArray","isPrimitiveArray( value:any )"],["isPRNGLike","isPRNGLike( value:any )"],["isProbability","isProbability( value:any )"],["isProbability.isPrimitive","isProbability.isPrimitive( value:any )"],["isProbability.isObject","isProbability.isObject( value:any )"],["isProbabilityArray","isProbabilityArray( value:any )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value:any )"],["isProbabilityArray.objects","isProbabilityArray.objects( value:any )"],["isPropertyKey","isPropertyKey( value:any )"],["isPrototypeOf","isPrototypeOf( value:any, proto:Object|Function )"],["isRaggedNestedArray","isRaggedNestedArray( value:any )"],["isRangeError","isRangeError( value:any )"],["isReadableProperty","isReadableProperty( value:any, property:any )"],["isReadablePropertyIn","isReadablePropertyIn( value:any, property:any )"],["isReadOnlyProperty","isReadOnlyProperty( value:any, property:any )"],["isReadOnlyPropertyIn","isReadOnlyPropertyIn( value:any, property:any )"],["isReadWriteProperty","isReadWriteProperty( value:any, property:any )"],["isReadWritePropertyIn","isReadWritePropertyIn( value:any, property:any )"],["isReferenceError","isReferenceError( value:any )"],["isRegExp","isRegExp( value:any )"],["isRegExpString","isRegExpString( value:any )"],["isRelativePath","isRelativePath( value:any )"],["isRelativePath.posix","isRelativePath.posix( value:any )"],["isRelativePath.win32","isRelativePath.win32( value:any )"],["isRelativeURI","isRelativeURI( value:any )"],["isSafeInteger","isSafeInteger( value:any )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value:any )"],["isSafeInteger.isObject","isSafeInteger.isObject( value:any )"],["isSafeIntegerArray","isSafeIntegerArray( value:any )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value:any )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value:any )"],["isSameArray","isSameArray( v1:any, v2:any )"],["isSameArrayLike","isSameArrayLike( v1:any, v2:any )"],["isSameComplex64","isSameComplex64( v1:any, v2:any )"],["isSameComplex64Array","isSameComplex64Array( v1:any, v2:any )"],["isSameComplex128","isSameComplex128( v1:any, v2:any )"],["isSameComplex128Array","isSameComplex128Array( v1:any, v2:any )"],["isSameDateObject","isSameDateObject( d1, d2 )"],["isSameFloat32Array","isSameFloat32Array( v1:any, v2:any )"],["isSameFloat64Array","isSameFloat64Array( v1:any, v2:any )"],["isSameNativeClass","isSameNativeClass( a:any, b:any )"],["isSameType","isSameType( a:any, b:any )"],["isSameValue","isSameValue( a:any, b:any )"],["isSameValueZero","isSameValueZero( a:any, b:any )"],["isSemVer","isSemVer( value:any )"],["isSharedArrayBuffer","isSharedArrayBuffer( value:any )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value:any )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value:any )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value:any )"],["isSlice","isSlice( value:any )"],["isSnakecase","isSnakecase( value:any )"],["isSquareMatrix","isSquareMatrix( value:any )"],["isSquareNumber","isSquareNumber( value:any )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value:any )"],["isSquareNumber.isObject","isSquareNumber.isObject( value:any )"],["isSquareTriangularNumber","isSquareTriangularNumber( value:any )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value:any )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value:any )"],["isStartcase","isStartcase( value:any )"],["isStrictEqual","isStrictEqual( a:any, b:any )"],["isString","isString( value:any )"],["isString.isPrimitive","isString.isPrimitive( value:any )"],["isString.isObject","isString.isObject( value:any )"],["isStringArray","isStringArray( value:any )"],["isStringArray.primitives","isStringArray.primitives( value:any )"],["isStringArray.objects","isStringArray.objects( value:any )"],["isSymbol","isSymbol( value:any )"],["isSymbolArray","isSymbolArray( value:any )"],["isSymbolArray.primitives","isSymbolArray.primitives( value:any )"],["isSymbolArray.objects","isSymbolArray.objects( value:any )"],["isSymmetricMatrix","isSymmetricMatrix( value:any )"],["isSyntaxError","isSyntaxError( value:any )"],["isTriangularNumber","isTriangularNumber( value:any )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value:any )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value:any )"],["isTruthy","isTruthy( value:any )"],["isTruthyArray","isTruthyArray( value:any )"],["isTypedArray","isTypedArray( value:any )"],["isTypedArrayLength","isTypedArrayLength( value:any )"],["isTypedArrayLike","isTypedArrayLike( value:any )"],["isTypeError","isTypeError( value:any )"],["isUint8Array","isUint8Array( value:any )"],["isUint8ClampedArray","isUint8ClampedArray( value:any )"],["isUint16Array","isUint16Array( value:any )"],["isUint32Array","isUint32Array( value:any )"],["isUNCPath","isUNCPath( value:any )"],["isUndefined","isUndefined( value:any )"],["isUndefinedOrNull","isUndefinedOrNull( value:any )"],["isUnityProbabilityArray","isUnityProbabilityArray( value:any )"],["isUppercase","isUppercase( value:any )"],["isURI","isURI( value:any )"],["isURIError","isURIError( value:any )"],["isVectorLike","isVectorLike( value:any )"],["isWebAssemblyMemory","isWebAssemblyMemory( value:any )"],["isWellFormedString","isWellFormedString( str:any )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str:any )"],["isWellFormedString.isObject","isWellFormedString.isObject( str:any )"],["isWhitespace","isWhitespace( str:string )"],["isWritableProperty","isWritableProperty( value:any, property:any )"],["isWritablePropertyIn","isWritablePropertyIn( value:any, property:any )"],["isWriteOnlyProperty","isWriteOnlyProperty( value:any, property:any )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value:any, property:any )"],["iterAbs","iterAbs( iterator:Object )"],["iterAbs2","iterAbs2( iterator:Object )"],["iterAcos","iterAcos( iterator:Object )"],["iterAcosh","iterAcosh( iterator:Object )"],["iterAcot","iterAcot( iterator:Object )"],["iterAcoth","iterAcoth( iterator:Object )"],["iterAcovercos","iterAcovercos( iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object )"],["iterBessely1","iterBessely1( iterator:Object )"],["iterBeta","iterBeta( x:Object|number, y:Object|number )"],["iterBetaln","iterBetaln( x:Object|number, y:Object|number )"],["iterBinet","iterBinet( iterator:Object )"],["iterCbrt","iterCbrt( iterator:Object )"],["iterCeil","iterCeil( iterator:Object )"],["iterCeil2","iterCeil2( iterator:Object )"],["iterCeil10","iterCeil10( iterator:Object )"],["iterCompositesSeq","iterCompositesSeq( [options:Object] )"],["iterConcat","iterConcat( iter0:Object, ...iterator:Object )"],["iterConstant","iterConstant( value:any[, options:Object] )"],["iterContinuedFraction","iterContinuedFraction( iterator:Object[, options:Object] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x:number[, options:Object] )"],["iterCos","iterCos( iterator:Object )"],["iterCosh","iterCosh( iterator:Object )"],["iterCosineWave","iterCosineWave( [options:Object] )"],["iterCosm1","iterCosm1( iterator:Object )"],["iterCospi","iterCospi( iterator:Object )"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object 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out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.discreteUniform.ndarray","random.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.exponential","random.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.exponential.ndarray","random.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.exponential.factory","random.strided.exponential.factory( [options:Object] 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so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, 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clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setReadOnly","setReadOnly( obj:Object, prop:string|symbol, value:any )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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)"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, 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sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, 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)"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ramp.ndarray","strided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.rsqrt","strided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sinBy","strided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrt","strided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, 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)"],["strided.subBy.ndarray","strided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.trunc","strided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.trunc.ndarray","strided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["stridedarray2iterator","stridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, offset:integer[, mapFcn:Function[, thisArg:any]] )"],["stridedArrayStream","stridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["stridedArrayStream.factory","stridedArrayStream.factory( [options:Object] )"],["stridedArrayStream.objectMode","stridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["string2buffer","string2buffer( str:string[, encoding:string] )"],["sub2ind","sub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )"],["substringAfter","substringAfter( str:string, search:string[, fromIndex:integer] )"],["substringAfterLast","substringAfterLast( str:string, search:string[, fromIndex:integer] )"],["substringBefore","substringBefore( str:string, search:string )"],["substringBeforeLast","substringBeforeLast( str:string, search:string )"],["SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()"],["SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()"],["Symbol","Symbol( [description:string] )"],["tabulate","tabulate( collection:Array|TypedArray|Object )"],["tabulateBy","tabulateBy( collection:Array|TypedArray|Object, [options:Object,] indicator:Function 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)"],["typedarraypool","typedarraypool( length:integer[, dtype:string] )"],["typedarraypool","typedarraypool( typedarray:TypedArray[, dtype:string] )"],["typedarraypool","typedarraypool( obj:Object[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( [dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( length:integer[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( typedarray:TypedArray[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( obj:Object[, dtype:string] )"],["typedarraypool.calloc","typedarraypool.calloc( [dtype:string] )"],["typedarraypool.calloc","typedarraypool.calloc( length:integer[, dtype:string] )"],["typedarraypool.free","typedarraypool.free( buf:TypedArray|ArrayBuffer )"],["typedarraypool.clear","typedarraypool.clear()"],["typedarraypool.highWaterMark","typedarraypool.highWaterMark"],["typedarraypool.nbytes","typedarraypool.nbytes"],["typedarraypool.factory","typedarraypool.factory( [options:Object] )"],["typemax","typemax( dtype:string )"],["typemin","typemin( dtype:string )"],["typeOf","typeOf( value:any )"],["UINT8_MAX","UINT8_MAX"],["UINT8_NUM_BYTES","UINT8_NUM_BYTES"],["Uint8Array","Uint8Array()"],["Uint8Array","Uint8Array( length:integer )"],["Uint8Array","Uint8Array( typedarray:TypedArray )"],["Uint8Array","Uint8Array( obj:Object )"],["Uint8Array","Uint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8Array.from","Uint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8Array.of","Uint8Array.of( element0:number[, element1:number[, ...elementN:number]] 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predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.findIndex","Uint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.forEach","Uint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint8Array.prototype.includes","Uint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.indexOf","Uint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.join","Uint8Array.prototype.join( [separator:string] )"],["Uint8Array.prototype.keys","Uint8Array.prototype.keys()"],["Uint8Array.prototype.lastIndexOf","Uint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.map","Uint8Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8Array.prototype.reduce","Uint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8Array.prototype.reduceRight","Uint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8Array.prototype.reverse","Uint8Array.prototype.reverse()"],["Uint8Array.prototype.set","Uint8Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction:Function] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length:integer )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray:TypedArray )"],["Uint8ClampedArray","Uint8ClampedArray( obj:Object )"],["Uint8ClampedArray","Uint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator:string] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction:Function] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length:integer )"],["Uint16Array","Uint16Array( typedarray:TypedArray )"],["Uint16Array","Uint16Array( obj:Object )"],["Uint16Array","Uint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint16Array.from","Uint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint16Array.of","Uint16Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator:string] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction:Function] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length:integer )"],["Uint32Array","Uint32Array( typedarray:TypedArray )"],["Uint32Array","Uint32Array( obj:Object )"],["Uint32Array","Uint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint32Array.from","Uint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint32Array.of","Uint32Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator:string] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction:Function] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask:integer|string,] [options:Object] )"],["uncapitalize","uncapitalize( str:string )"],["uncapitalizeKeys","uncapitalizeKeys( obj:Object )"],["uncurry","uncurry( fcn:Function[, arity:integer, ][thisArg:any] )"],["uncurryRight","uncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeSparkline","UnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["unlink","unlink( path:string|Buffer|integer, clbk:Function )"],["unlink.sync","unlink.sync( path:string|Buffer|integer )"],["unshift","unshift( collection:Array|TypedArray|Object, ...items:any )"],["until","until( predicate:Function, fcn:Function[, thisArg:any] )"],["untilAsync","untilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["untilEach","untilEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["untilEachRight","untilEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["unzip","unzip( arr:Array[, idx:Array] )"],["uppercase","uppercase( str:string )"],["uppercaseKeys","uppercaseKeys( obj:Object )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str:string )"],["vartest","vartest( x:Array, y:Array[, options:Object] )"],["waterfall","waterfall( fcns:Array, clbk:Function[, thisArg:any] )"],["waterfall.factory","waterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor:Object )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta:integer )"],["whileAsync","whileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["whileEach","whileEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whileEachRight","whileEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whilst","whilst( predicate:Function, fcn:Function[, thisArg:any] )"],["wilcoxon","wilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )"],["writableProperties","writableProperties( value:any )"],["writablePropertiesIn","writablePropertiesIn( value:any )"],["writablePropertyNames","writablePropertyNames( value:any )"],["writablePropertyNamesIn","writablePropertyNamesIn( value:any )"],["writablePropertySymbols","writablePropertySymbols( value:any )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value:any )"],["writeFile","writeFile( file:string|Buffer|integer, data:string|Buffer[, options:Object|string], clbk:Function )"],["writeFile.sync","writeFile.sync( file:string|Buffer|integer, data:string|Buffer[, options:Object|string] )"],["zip","zip( ...arr:Array[, options:Object] )"],["ztest","ztest( x:Array, sigma:number[, options:Object] )"],["ztest2","ztest2( x:Array, y:Array, sigmax:number, sigmay:number[, options:Object] )"]] diff --git a/lib/node_modules/@stdlib/slice/base/normalize-multi-slice/README.md b/lib/node_modules/@stdlib/slice/base/normalize-multi-slice/README.md index 1cfa68950015..f94d58d42b2b 100644 --- a/lib/node_modules/@stdlib/slice/base/normalize-multi-slice/README.md +++ b/lib/node_modules/@stdlib/slice/base/normalize-multi-slice/README.md @@ -177,6 +177,12 @@ console.log( '%s => %s', s1.toString(), s2.toString() );
+* * * + +## See Also + +- [`@stdlib/slice/base/normalize-slice`][@stdlib/slice/base/normalize-slice]: normalize a Slice object. +
@@ -187,6 +193,12 @@ console.log( '%s => %s', s1.toString(), s2.toString() ); [@stdlib/slice/multi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/multi + + +[@stdlib/slice/base/normalize-slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/base/normalize-slice + + + diff --git a/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md b/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md index 484deaea2cb1..dd2ec965934b 100644 --- a/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md +++ b/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md @@ -174,6 +174,13 @@ s = seq2multislice( 'foo,bar', [ 10, 10 ], false );
+* * * + +## See Also + +- [`@stdlib/slice/base/seq2slice`][@stdlib/slice/base/seq2slice]: convert a subsequence string to a Slice object. +- [`@stdlib/slice/base/sargs2multislice`][@stdlib/slice/base/sargs2multislice]: create a MultiSlice object from a comma-separated list of string-serialized MultiSlice constructor arguments. +
@@ -186,6 +193,12 @@ s = seq2multislice( 'foo,bar', [ 10, 10 ], false ); [@stdlib/slice/base/seq2slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/base/seq2slice + + +[@stdlib/slice/base/sargs2multislice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/base/sargs2multislice + + + diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md index a885eb9f0a1b..7885d630414b 100644 --- a/lib/node_modules/@stdlib/stats/base/README.md +++ b/lib/node_modules/@stdlib/stats/base/README.md @@ -61,32 +61,31 @@ The namespace contains the following statistical functions: - [`cumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/cumaxabs]: calculate the cumulative maximum absolute value of a strided array. - [`cumin( N, x, strideX, y, strideY )`][@stdlib/stats/base/cumin]: calculate the cumulative minimum of a strided array. - [`cuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/cuminabs]: calculate the cumulative minimum absolute value of a strided array. -- [`dcumax( N, x, strideX, y, strideY )`][@stdlib/stats/base/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. +- [`dcumax( N, x, strideX, y, strideY )`][@stdlib/stats/strided/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. - [`dcumaxabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - [`dcumin( N, x, strideX, y, strideY )`][@stdlib/stats/base/dcumin]: calculate the cumulative minimum of double-precision floating-point strided array elements. - [`dcuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/dcuminabs]: calculate the cumulative minimum absolute value of double-precision floating-point strided array elements. -- [`dmax( N, x, strideX )`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`dmaxabs( N, x, strideX )`][@stdlib/stats/base/dmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array. -- [`dmaxabssorted( N, x, stride )`][@stdlib/stats/base/dmaxabssorted]: calculate the maximum absolute value of a sorted double-precision floating-point strided array. -- [`dmaxsorted( N, x, stride )`][@stdlib/stats/base/dmaxsorted]: calculate the maximum value of a sorted double-precision floating-point strided array. +- [`dmaxabssorted( N, x, strideX )`][@stdlib/stats/base/dmaxabssorted]: calculate the maximum absolute value of a sorted double-precision floating-point strided array. +- [`dmaxsorted( N, x, strideX )`][@stdlib/stats/base/dmaxsorted]: calculate the maximum value of a sorted double-precision floating-point strided array. - [`dmean( N, x, stride )`][@stdlib/stats/base/dmean]: calculate the arithmetic mean of a double-precision floating-point strided array. -- [`dmeankbn( N, x, stride )`][@stdlib/stats/base/dmeankbn]: calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. -- [`dmeankbn2( N, x, stride )`][@stdlib/stats/base/dmeankbn2]: calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. -- [`dmeanli( N, x, stride )`][@stdlib/stats/base/dmeanli]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. +- [`dmeankbn( N, x, strideX )`][@stdlib/stats/base/dmeankbn]: calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. +- [`dmeankbn2( N, x, strideX )`][@stdlib/stats/base/dmeankbn2]: calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. +- [`dmeanli( N, x, strideX )`][@stdlib/stats/base/dmeanli]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dmeanlipw( N, x, stride )`][@stdlib/stats/base/dmeanlipw]: calculate the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. -- [`dmeanors( N, x, stride )`][@stdlib/stats/base/dmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. +- [`dmeanors( N, x, strideX )`][@stdlib/stats/base/dmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. - [`dmeanpn( N, x, stride )`][@stdlib/stats/base/dmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm. -- [`dmeanpw( N, x, stride )`][@stdlib/stats/base/dmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation. +- [`dmeanpw( N, x, strideX )`][@stdlib/stats/base/dmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation. - [`dmeanstdev( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdev]: calculate the mean and standard deviation of a double-precision floating-point strided array. - [`dmeanstdevpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanstdevpn]: calculate the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm. - [`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]: calculate the mean and variance of a double-precision floating-point strided array. - [`dmeanvarpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvarpn]: calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm. -- [`dmeanwd( N, x, stride )`][@stdlib/stats/base/dmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. -- [`dmediansorted( N, x, stride )`][@stdlib/stats/base/dmediansorted]: calculate the median value of a sorted double-precision floating-point strided array. +- [`dmeanwd( N, x, strideX )`][@stdlib/stats/base/dmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. +- [`dmediansorted( N, x, strideX )`][@stdlib/stats/base/dmediansorted]: calculate the median value of a sorted double-precision floating-point strided array. - [`dmidrange( N, x, strideX )`][@stdlib/stats/base/dmidrange]: calculate the mid-range of a double-precision floating-point strided array. - [`dmin( N, x, strideX )`][@stdlib/stats/base/dmin]: calculate the minimum value of a double-precision floating-point strided array. - [`dminabs( N, x, strideX )`][@stdlib/stats/base/dminabs]: calculate the minimum absolute value of a double-precision floating-point strided array. -- [`dminsorted( N, x, stride )`][@stdlib/stats/base/dminsorted]: calculate the minimum value of a sorted double-precision floating-point strided array. +- [`dminsorted( N, x, strideX )`][@stdlib/stats/base/dminsorted]: calculate the minimum value of a sorted double-precision floating-point strided array. - [`dmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask. - [`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask. - [`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskrange]: calculate the range of a double-precision floating-point strided array according to a mask. @@ -95,8 +94,8 @@ The namespace contains the following statistical functions: - [`dnanmean( N, x, stride )`][@stdlib/stats/base/dnanmean]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmeanors( N, x, stride )`][@stdlib/stats/base/dnanmeanors]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation. - [`dnanmeanpn( N, x, stride )`][@stdlib/stats/base/dnanmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. -- [`dnanmeanpw( N, x, stride )`][@stdlib/stats/base/dnanmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. -- [`dnanmeanwd( N, x, stride )`][@stdlib/stats/base/dnanmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. +- [`dnanmeanpw( N, x, strideX )`][@stdlib/stats/base/dnanmeanpw]: calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. +- [`dnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dnanmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. - [`dnanmin( N, x, strideX )`][@stdlib/stats/base/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanminabs( N, x, strideX )`][@stdlib/stats/base/dnanminabs]: calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values. - [`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values. @@ -117,37 +116,37 @@ The namespace contains the following statistical functions: - [`dnanvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/dnanvarianceyc]: calculate the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`drange( N, x, strideX )`][@stdlib/stats/base/drange]: calculate the range of a double-precision floating-point strided array. - [`dsem( N, correction, x, stride )`][@stdlib/stats/base/dsem]: calculate the standard error of the mean of a double-precision floating-point strided array. -- [`dsemch( N, correction, x, stride )`][@stdlib/stats/base/dsemch]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. +- [`dsemch( N, correction, x, strideX )`][@stdlib/stats/base/dsemch]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dsempn( N, correction, x, stride )`][@stdlib/stats/base/dsempn]: calculate the standard error of the mean of a double-precision floating-point strided array using a two-pass algorithm. -- [`dsemtk( N, correction, x, stride )`][@stdlib/stats/base/dsemtk]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm. -- [`dsemwd( N, correction, x, stride )`][@stdlib/stats/base/dsemwd]: calculate the standard error of the mean of a double-precision floating-point strided array using Welford's algorithm. -- [`dsemyc( N, correction, x, stride )`][@stdlib/stats/base/dsemyc]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +- [`dsemtk( N, correction, x, strideX )`][@stdlib/stats/base/dsemtk]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass textbook algorithm. +- [`dsemwd( N, correction, x, strideX )`][@stdlib/stats/base/dsemwd]: calculate the standard error of the mean of a double-precision floating-point strided array using Welford's algorithm. +- [`dsemyc( N, correction, x, strideX )`][@stdlib/stats/base/dsemyc]: calculate the standard error of the mean of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`dsmean( N, x, stride )`][@stdlib/stats/base/dsmean]: calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result. -- [`dsmeanors( N, x, stride )`][@stdlib/stats/base/dsmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. -- [`dsmeanpn( N, x, stride )`][@stdlib/stats/base/dsmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. -- [`dsmeanpw( N, x, stride )`][@stdlib/stats/base/dsmeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. -- [`dsmeanwd( N, x, stride )`][@stdlib/stats/base/dsmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. +- [`dsmeanors( N, x, strideX )`][@stdlib/stats/base/dsmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. +- [`dsmeanpn( N, x, strideX )`][@stdlib/stats/base/dsmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. +- [`dsmeanpw( N, x, strideX )`][@stdlib/stats/base/dsmeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. +- [`dsmeanwd( N, x, strideX )`][@stdlib/stats/base/dsmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. - [`dsnanmean( N, x, stride )`][@stdlib/stats/base/dsnanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using extended accumulation, and returning an extended precision result. - [`dsnanmeanors( N, x, stride )`][@stdlib/stats/base/dsnanmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using ordinary recursive summation with extended accumulation, and returning an extended precision result. - [`dsnanmeanpn( N, x, stride )`][@stdlib/stats/base/dsnanmeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result. - [`dsnanmeanwd( N, x, stride )`][@stdlib/stats/base/dsnanmeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result. - [`dstdev( N, correction, x, stride )`][@stdlib/stats/base/dstdev]: calculate the standard deviation of a double-precision floating-point strided array. -- [`dstdevch( N, correction, x, stride )`][@stdlib/stats/base/dstdevch]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. +- [`dstdevch( N, correction, x, strideX )`][@stdlib/stats/base/dstdevch]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dstdevpn( N, correction, x, stride )`][@stdlib/stats/base/dstdevpn]: calculate the standard deviation of a double-precision floating-point strided array using a two-pass algorithm. -- [`dstdevtk( N, correction, x, stride )`][@stdlib/stats/base/dstdevtk]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. -- [`dstdevwd( N, correction, x, stride )`][@stdlib/stats/base/dstdevwd]: calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm. -- [`dstdevyc( N, correction, x, stride )`][@stdlib/stats/base/dstdevyc]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +- [`dstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/dstdevtk]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. +- [`dstdevwd( N, correction, x, strideX )`][@stdlib/stats/base/dstdevwd]: calculate the standard deviation of a double-precision floating-point strided array using Welford's algorithm. +- [`dstdevyc( N, correction, x, strideX )`][@stdlib/stats/base/dstdevyc]: calculate the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`dsvariance( N, correction, x, stride )`][@stdlib/stats/base/dsvariance]: calculate the variance of a single-precision floating-point strided array using extended accumulation and returning an extended precision result. - [`dsvariancepn( N, correction, x, stride )`][@stdlib/stats/base/dsvariancepn]: calculate the variance of a single-precision floating-point strided array using a two-pass algorithm with extended accumulation and returning an extended precision result. - [`dvariance( N, correction, x, stride )`][@stdlib/stats/base/dvariance]: calculate the variance of a double-precision floating-point strided array. -- [`dvariancech( N, correction, x, stride )`][@stdlib/stats/base/dvariancech]: calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. +- [`dvariancech( N, correction, x, strideX )`][@stdlib/stats/base/dvariancech]: calculate the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. - [`dvariancepn( N, correction, x, stride )`][@stdlib/stats/base/dvariancepn]: calculate the variance of a double-precision floating-point strided array using a two-pass algorithm. -- [`dvariancetk( N, correction, x, stride )`][@stdlib/stats/base/dvariancetk]: calculate the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. -- [`dvariancewd( N, correction, x, stride )`][@stdlib/stats/base/dvariancewd]: calculate the variance of a double-precision floating-point strided array using Welford's algorithm. -- [`dvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/dvarianceyc]: calculate the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +- [`dvariancetk( N, correction, x, strideX )`][@stdlib/stats/base/dvariancetk]: calculate the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. +- [`dvariancewd( N, correction, x, strideX )`][@stdlib/stats/base/dvariancewd]: calculate the variance of a double-precision floating-point strided array using Welford's algorithm. +- [`dvarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/dvarianceyc]: calculate the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`dvarm( N, mean, correction, x, stride )`][@stdlib/stats/base/dvarm]: calculate the variance of a double-precision floating-point strided array provided a known mean. - [`dvarmpn( N, mean, correction, x, stride )`][@stdlib/stats/base/dvarmpn]: calculate the variance of a double-precision floating-point strided array provided a known mean and using Neely's correction algorithm. -- [`dvarmtk( N, mean, correction, x, stride )`][@stdlib/stats/base/dvarmtk]: calculate the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. +- [`dvarmtk( N, mean, correction, x, strideX )`][@stdlib/stats/base/dvarmtk]: calculate the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. - [`maxBy( N, x, stride, clbk[, thisArg] )`][@stdlib/stats/base/max-by]: calculate the maximum value of a strided array via a callback function. - [`max( N, x, stride )`][@stdlib/stats/base/max]: calculate the maximum value of a strided array. - [`maxabs( N, x, stride )`][@stdlib/stats/base/maxabs]: calculate the maximum absolute value of a strided array. @@ -201,27 +200,27 @@ The namespace contains the following statistical functions: - [`scumin( N, x, strideX, y, strideY )`][@stdlib/stats/base/scumin]: calculate the cumulative minimum of single-precision floating-point strided array elements. - [`scuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/scuminabs]: calculate the cumulative minimum absolute value of single-precision floating-point strided array elements. - [`sdsmean( N, x, stride )`][@stdlib/stats/base/sdsmean]: calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation. -- [`sdsmeanors( N, x, stride )`][@stdlib/stats/base/sdsmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. +- [`sdsmeanors( N, x, strideX )`][@stdlib/stats/base/sdsmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. - [`sdsnanmean( N, x, stride )`][@stdlib/stats/base/sdsnanmean]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation. - [`sdsnanmeanors( N, x, stride )`][@stdlib/stats/base/sdsnanmeanors]: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation. - [`smax( N, x, strideX )`][@stdlib/stats/base/smax]: calculate the maximum value of a single-precision floating-point strided array. - [`smaxabs( N, x, strideX )`][@stdlib/stats/base/smaxabs]: calculate the maximum absolute value of a single-precision floating-point strided array. -- [`smaxabssorted( N, x, stride )`][@stdlib/stats/base/smaxabssorted]: calculate the maximum absolute value of a sorted single-precision floating-point strided array. +- [`smaxabssorted( N, x, strideX )`][@stdlib/stats/base/smaxabssorted]: calculate the maximum absolute value of a sorted single-precision floating-point strided array. - [`smaxsorted( N, x, stride )`][@stdlib/stats/base/smaxsorted]: calculate the maximum value of a sorted single-precision floating-point strided array. - [`smean( N, x, stride )`][@stdlib/stats/base/smean]: calculate the arithmetic mean of a single-precision floating-point strided array. - [`smeankbn( N, x, stride )`][@stdlib/stats/base/smeankbn]: calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm. - [`smeankbn2( N, x, stride )`][@stdlib/stats/base/smeankbn2]: calculate the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. -- [`smeanli( N, x, stride )`][@stdlib/stats/base/smeanli]: calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. +- [`smeanli( N, x, strideX )`][@stdlib/stats/base/smeanli]: calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`smeanlipw( N, x, stride )`][@stdlib/stats/base/smeanlipw]: calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. - [`smeanors( N, x, stride )`][@stdlib/stats/base/smeanors]: calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation. - [`smeanpn( N, x, stride )`][@stdlib/stats/base/smeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm. - [`smeanpw( N, x, stride )`][@stdlib/stats/base/smeanpw]: calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation. -- [`smeanwd( N, x, stride )`][@stdlib/stats/base/smeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. -- [`smediansorted( N, x, stride )`][@stdlib/stats/base/smediansorted]: calculate the median value of a sorted single-precision floating-point strided array. +- [`smeanwd( N, x, strideX )`][@stdlib/stats/base/smeanwd]: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. +- [`smediansorted( N, x, strideX )`][@stdlib/stats/base/smediansorted]: calculate the median value of a sorted single-precision floating-point strided array. - [`smidrange( N, x, strideX )`][@stdlib/stats/base/smidrange]: calculate the mid-range of a single-precision floating-point strided array. - [`smin( N, x, strideX )`][@stdlib/stats/base/smin]: calculate the minimum value of a single-precision floating-point strided array. - [`sminabs( N, x, strideX )`][@stdlib/stats/base/sminabs]: calculate the minimum absolute value of a single-precision floating-point strided array. -- [`sminsorted( N, x, stride )`][@stdlib/stats/base/sminsorted]: calculate the minimum value of a sorted single-precision floating-point strided array. +- [`sminsorted( N, x, strideX )`][@stdlib/stats/base/sminsorted]: calculate the minimum value of a sorted single-precision floating-point strided array. - [`smskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmax]: calculate the maximum value of a single-precision floating-point strided array according to a mask. - [`smskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmin]: calculate the minimum value of a single-precision floating-point strided array according to a mask. - [`smskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskrange]: calculate the range of a single-precision floating-point strided array according to a mask. @@ -251,9 +250,9 @@ The namespace contains the following statistical functions: - [`snanvarianceyc( N, correction, x, stride )`][@stdlib/stats/base/snanvarianceyc]: calculate the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - [`srange( N, x, strideX )`][@stdlib/stats/base/srange]: calculate the range of a single-precision floating-point strided array. - [`sstdev( N, correction, x, stride )`][@stdlib/stats/base/sstdev]: calculate the standard deviation of a single-precision floating-point strided array. -- [`sstdevch( N, correction, x, stride )`][@stdlib/stats/base/sstdevch]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. +- [`sstdevch( N, correction, x, strideX )`][@stdlib/stats/base/sstdevch]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`sstdevpn( N, correction, x, stride )`][@stdlib/stats/base/sstdevpn]: calculate the standard deviation of a single-precision floating-point strided array using a two-pass algorithm. -- [`sstdevtk( N, correction, x, stride )`][@stdlib/stats/base/sstdevtk]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. +- [`sstdevtk( N, correction, x, strideX )`][@stdlib/stats/base/sstdevtk]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. - [`sstdevwd( N, correction, x, stride )`][@stdlib/stats/base/sstdevwd]: calculate the standard deviation of a single-precision floating-point strided array using Welford's algorithm. - [`sstdevyc( N, correction, x, stride )`][@stdlib/stats/base/sstdevyc]: calculate the standard deviation of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`stdev( N, correction, x, stride )`][@stdlib/stats/base/stdev]: calculate the standard deviation of a strided array. @@ -263,11 +262,11 @@ The namespace contains the following statistical functions: - [`stdevwd( N, correction, x, stride )`][@stdlib/stats/base/stdevwd]: calculate the standard deviation of a strided array using Welford's algorithm. - [`stdevyc( N, correction, x, stride )`][@stdlib/stats/base/stdevyc]: calculate the standard deviation of a strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`svariance( N, correction, x, stride )`][@stdlib/stats/base/svariance]: calculate the variance of a single-precision floating-point strided array. -- [`svariancech( N, correction, x, stride )`][@stdlib/stats/base/svariancech]: calculate the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. +- [`svariancech( N, correction, x, strideX )`][@stdlib/stats/base/svariancech]: calculate the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. - [`svariancepn( N, correction, x, stride )`][@stdlib/stats/base/svariancepn]: calculate the variance of a single-precision floating-point strided array using a two-pass algorithm. -- [`svariancetk( N, correction, x, stride )`][@stdlib/stats/base/svariancetk]: calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. +- [`svariancetk( N, correction, x, strideX )`][@stdlib/stats/base/svariancetk]: calculate the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. - [`svariancewd( N, correction, x, stride )`][@stdlib/stats/base/svariancewd]: calculate the variance of a single-precision floating-point strided array using Welford's algorithm. -- [`svarianceyc( N, correction, x, stride )`][@stdlib/stats/base/svarianceyc]: calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +- [`svarianceyc( N, correction, x, strideX )`][@stdlib/stats/base/svarianceyc]: calculate the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - [`variance( N, correction, x, stride )`][@stdlib/stats/base/variance]: calculate the variance of a strided array. - [`variancech( N, correction, x, stride )`][@stdlib/stats/base/variancech]: calculate the variance of a strided array using a one-pass trial mean algorithm. - [`variancepn( N, correction, x, stride )`][@stdlib/stats/base/variancepn]: calculate the variance of a strided array using a two-pass algorithm. @@ -332,16 +331,12 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/base/cuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cuminabs -[@stdlib/stats/base/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumax - -[@stdlib/stats/base/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumaxabs +[@stdlib/stats/strided/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumaxabs [@stdlib/stats/base/dcumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumin [@stdlib/stats/base/dcuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcuminabs -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax - [@stdlib/stats/base/dmaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmaxabs [@stdlib/stats/base/dmaxabssorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmaxabssorted diff --git a/lib/node_modules/@stdlib/stats/base/cumax/README.md b/lib/node_modules/@stdlib/stats/base/cumax/README.md index 8fc639da98f0..c567f69b86b0 100644 --- a/lib/node_modules/@stdlib/stats/base/cumax/README.md +++ b/lib/node_modules/@stdlib/stats/base/cumax/README.md @@ -121,7 +121,7 @@ cumax.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); ## Notes - If `N <= 0`, both functions return `y` unchanged. -- Depending on the environment, the typed versions ([`dcumax`][@stdlib/stats/base/dcumax], [`scumax`][@stdlib/stats/base/scumax], etc.) are likely to be significantly more performant. +- Depending on the environment, the typed versions ([`dcumax`][@stdlib/stats/strided/dcumax], [`scumax`][@stdlib/stats/base/scumax], etc.) are likely to be significantly more performant. @@ -174,7 +174,7 @@ console.log( y ); ## See Also - [`@stdlib/stats/base/cumin`][@stdlib/stats/base/cumin]: calculate the cumulative minimum of a strided array. -- [`@stdlib/stats/base/dcumax`][@stdlib/stats/base/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. +- [`@stdlib/stats/strided/dcumax`][@stdlib/stats/strided/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. - [`@stdlib/stats/base/scumax`][@stdlib/stats/base/scumax]: calculate the cumulative maximum of single-precision floating-point strided array elements. @@ -193,7 +193,7 @@ console.log( y ); [@stdlib/stats/base/cumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumin -[@stdlib/stats/base/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumax +[@stdlib/stats/strided/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumax [@stdlib/stats/base/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumax diff --git a/lib/node_modules/@stdlib/stats/base/cumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/cumaxabs/README.md index 876d6b193da2..5c7bee44a499 100644 --- a/lib/node_modules/@stdlib/stats/base/cumaxabs/README.md +++ b/lib/node_modules/@stdlib/stats/base/cumaxabs/README.md @@ -121,7 +121,7 @@ cumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); ## Notes - If `N <= 0`, both functions return `y` unchanged. -- Depending on the environment, the typed versions ([`dcumaxabs`][@stdlib/stats/base/dcumaxabs], [`scumaxabs`][@stdlib/stats/base/scumaxabs], etc.) are likely to be significantly more performant. +- Depending on the environment, the typed versions ([`dcumaxabs`][@stdlib/stats/strided/dcumaxabs], [`scumaxabs`][@stdlib/stats/base/scumaxabs], etc.) are likely to be significantly more performant. @@ -175,7 +175,7 @@ console.log( y ); - [`@stdlib/stats/base/cumax`][@stdlib/stats/base/cumax]: calculate the cumulative maximum of a strided array. - [`@stdlib/stats/base/cuminabs`][@stdlib/stats/base/cuminabs]: calculate the cumulative minimum absolute value of a strided array. -- [`@stdlib/stats/base/dcumaxabs`][@stdlib/stats/base/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. +- [`@stdlib/stats/strided/dcumaxabs`][@stdlib/stats/strided/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - [`@stdlib/stats/base/scumaxabs`][@stdlib/stats/base/scumaxabs]: calculate the cumulative maximum absolute value of single-precision floating-point strided array elements. @@ -196,7 +196,7 @@ console.log( y ); [@stdlib/stats/base/cuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cuminabs -[@stdlib/stats/base/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumaxabs +[@stdlib/stats/strided/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumaxabs [@stdlib/stats/base/scumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumaxabs diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/README.md b/lib/node_modules/@stdlib/stats/base/dcumax/README.md deleted file mode 100644 index d73381291a08..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/README.md +++ /dev/null @@ -1,332 +0,0 @@ - - -# dcumax - -> Calculate the cumulative maximum of double-precision floating-point strided array elements. - -
- -
- - - -
- -## Usage - -```javascript -var dcumax = require( '@stdlib/stats/base/dcumax' ); -``` - -#### dcumax( N, x, strideX, y, strideY ) - -Computes the cumulative maximum of double-precision floating-point strided array elements. - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var y = new Float64Array( x.length ); - -dcumax( x.length, x, 1, y, 1 ); -// y => [ 1.0, 1.0, 2.0 ] -``` - -The function has the following parameters: - -- **N**: number of indexed elements. -- **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: stride length for `x`. -- **y**: output [`Float64Array`][@stdlib/array/float64]. -- **strideY**: stride length for `y`. - -The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative maximum of every other element in `x`, - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var y = new Float64Array( x.length ); - -var v = dcumax( 4, x, 2, y, 1 ); -// y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] -``` - -Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - - - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -// Initial arrays... -var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var y0 = new Float64Array( x0.length ); - -// Create offset views... -var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element - -dcumax( 4, x1, -2, y1, 1 ); -// y0 => [ 0.0, 0.0, 0.0, 4.0, 4.0, 4.0, 4.0, 0.0 ] -``` - -#### dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) - -Computes the cumulative maximum of double-precision floating-point strided array elements using alternative indexing semantics. - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var y = new Float64Array( x.length ); - -dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 ); -// y => [ 1.0, 1.0, 2.0 ] -``` - -The function has the following additional parameters: - -- **offsetX**: starting index for `x`. -- **offsetY**: starting index for `y`. - -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var y = new Float64Array( x.length ); - -dcumax.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); -// y => [ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0, 1.0, 1.0 ] -``` - -
- - - -
- -## Notes - -- If `N <= 0`, both functions return `y` unchanged. - -
- - - -
- -## Examples - - - -```javascript -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); -var Float64Array = require( '@stdlib/array/float64' ); -var dcumax = require( '@stdlib/stats/base/dcumax' ); - -var x = discreteUniform( 10, -50, 50, { - 'dtype': 'float64' -}); -console.log( x ); - -var y = new Float64Array( x.length ); -console.log( y ); - -dcumax( x.length, x, 1, y, -1 ); -console.log( y ); -``` - -
- - - - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/stats/base/dcumax.h" -``` - -#### stdlib_strided_dcumax( N, \*X, strideX, \*Y, strideY ) - -Computes the cumulative maximum of double-precision floating-point strided array elements. - -```c -const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; -double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; - -stdlib_strided_dcumax( 4, x, 2, y, -2 ); -``` - -The function accepts the following arguments: - -- **N**: `[in] CBLAS_INT` number of indexed elements. -- **X**: `[in] double*` input array. -- **strideX**: `[in] CBLAS_INT` stride length for `X`. -- **Y**: `[out] double*` output array. -- **strideY**: `[in] CBLAS_INT` stride length for `Y`. - -```c -void stdlib_strided_dcumax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); -``` - -#### stdlib_strided_dcumax_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) - -Computes the cumulative maximum of double-precision floating-point strided array elements using alternative indexing semantics. - -```c -const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; -double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; - -stdlib_strided_dcumax_ndarray( 4, x, 2, 0, y, -2, 0 ); -``` - -The function accepts the following arguments: - -- **N**: `[in] CBLAS_INT` number of indexed elements. -- **X**: `[in] double*` input array. -- **strideX**: `[in] CBLAS_INT` stride length for `X`. -- **offsetX**: `[in] CBLAS_INT` starting index for `X`. -- **Y**: `[out] double*` output array. -- **strideY**: `[in] CBLAS_INT` stride length for `Y`. -- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. - -```c -void stdlib_strided_dcumax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/stats/base/dcumax.h" -#include - -int main( void ) { - // Create strided arrays: - const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; - double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; - - // Specify the number of elements: - const int N = 4; - - // Specify stride lengths: - const int strideX = 2; - const int strideY = -2; - - // Compute the cumulative maximum: - stdlib_strided_dcumax( N, x, strideX, y, strideY ); - - // Print the result: - for ( int i = 0; i < 8; i++ ) { - printf( "y[ %d ] = %lf\n", i, y[ i ] ); - } -} -``` - -
- - - -
- - - -
- -
- - - - - -
- -* * * - -## See Also - -- [`@stdlib/stats/base/cumax`][@stdlib/stats/base/cumax]: calculate the cumulative maximum of a strided array. -- [`@stdlib/stats/base/dcumin`][@stdlib/stats/base/dcumin]: calculate the cumulative minimum of double-precision floating-point strided array elements. -- [`@stdlib/stats/base/scumax`][@stdlib/stats/base/scumax]: calculate the cumulative maximum of single-precision floating-point strided array elements. - -
- - - - - -
- -[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 - -[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray - - - -[@stdlib/stats/base/cumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumax - -[@stdlib/stats/base/dcumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumin - -[@stdlib/stats/base/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumax - - - -
- - diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/c/benchmark.length.c deleted file mode 100644 index 2b33f132d0de..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/c/benchmark.length.c +++ /dev/null @@ -1,197 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumax.h" -#include -#include -#include -#include -#include - -#define NAME "dcumax" -#define ITERATIONS 1000000 -#define REPEATS 3 -#define MIN 1 -#define MAX 6 - -/** -* Prints the TAP version. -*/ -static void print_version( void ) { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -static void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param iterations number of iterations -* @param elapsed elapsed time in seconds -*/ -static void print_results( int iterations, double elapsed ) { - double rate = (double)iterations / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", iterations ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -static double tic( void ) { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec/1.0e6; -} - -/** -* Generates a random number on the interval [0,1). -* -* @return random number -*/ -static double rand_double( void ) { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @param iterations number of iterations -* @param len array length -* @return elapsed time in seconds -*/ -static double benchmark1( int iterations, int len ) { - double elapsed; - double x[ len ]; - double y[ len ]; - double t; - int i; - - for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; - y[ i ] = 0.0; - } - t = tic(); - for ( i = 0; i < iterations; i++ ) { - x[ 0 ] += 1.0; - stdlib_strided_dcumax( len, x, 1, y, 1 ); - if ( y[ 0 ] != y[ 0 ] ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( y[ len-1 ] != y[ len-1 ] ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Runs a benchmark. -* -* @param iterations number of iterations -* @param len array length -* @return elapsed time in seconds -*/ -static double benchmark2( int iterations, int len ) { - double elapsed; - double x[ len ]; - double y[ len ]; - double t; - int i; - - for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; - y[ i ] = 0.0; - } - t = tic(); - for ( i = 0; i < iterations; i++ ) { - x[ 0 ] += 1.0; - stdlib_strided_dcumax_ndarray( len, x, 1, 0, y, 1, 0 ); - if ( y[ 0 ] != y[ 0 ] ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( y[ len-1 ] != y[ len-1 ] ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int count; - int iter; - int len; - int i; - int j; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - count = 0; - for ( i = MIN; i <= MAX; i++ ) { - len = pow( 10, i ); - iter = ITERATIONS / pow( 10, i-1 ); - for ( j = 0; j < REPEATS; j++ ) { - count += 1; - printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark1( iter, len ); - print_results( iter, elapsed ); - printf( "ok %d benchmark finished\n", count ); - } - } - for ( i = MIN; i <= MAX; i++ ) { - len = pow( 10, i ); - iter = ITERATIONS / pow( 10, i-1 ); - for ( j = 0; j < REPEATS; j++ ) { - count += 1; - printf( "# c::%s:ndarray:len=%d\n", NAME, len ); - elapsed = benchmark2( iter, len ); - print_results( iter, elapsed ); - printf( "ok %d benchmark finished\n", count ); - } - } - print_summary( count, count ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dcumax/docs/repl.txt deleted file mode 100644 index c12c7d753cd3..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/docs/repl.txt +++ /dev/null @@ -1,113 +0,0 @@ - -{{alias}}( N, x, strideX, y, strideY ) - Computes the cumulative maximum of double-precision floating-point strided - array elements. - - The `N` and stride parameters determine which elements in the strided arrays - are accessed at runtime. - - Indexing is relative to the first index. To introduce an offset, use a typed - array view. - - If `N <= 0`, the function returns `y` unchanged. - - Parameters - ---------- - N: integer - Number of indexed elements. - - x: Float64Array - Input array. - - strideX: integer - Stride Length for `x`. - - y: Float64Array - Output array. - - strideY: integer - Stride Length for `y`. - - Returns - ------- - out: Float64Array - Output array. - - Examples - -------- - // Standard Usage: - > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); - > var y = new {{alias:@stdlib/array/float64}}( x.length ); - > {{alias}}( x.length, x, 1, y, 1 ) - [ 1.0, 1.0, 2.0 ] - - // Using `N` and stride parameters: - > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > y = new {{alias:@stdlib/array/float64}}( x.length ); - > {{alias}}( 3, x, 2, y, 2 ) - [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ] - - // Using view offsets: - > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); - > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > {{alias}}( 3, x1, 2, y1, 1 ) - [ -2.0, 2.0, 2.0 ] - > y0 - [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ] - - -{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) - Computes the cumulative maximum of double-precision floating-point strided - array elements using alternative indexing semantics. - - While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. - - Parameters - ---------- - N: integer - Number of indexed elements. - - x: Float64Array - Input array. - - strideX: integer - Stride Length for `x`. - - offsetX: integer - Starting index for `x`. - - y: Float64Array - Output array. - - strideY: integer - Stride Length for `y`. - - offsetY: integer - Starting index for `y`. - - Returns - ------- - out: Float64Array - Output array. - - Examples - -------- - // Standard Usage: - > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); - > var y = new {{alias:@stdlib/array/float64}}( x.length ); - > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) - [ 1.0, 1.0, 2.0 ] - - // Advanced indexing: - > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > y = new {{alias:@stdlib/array/float64}}( x.length ); - > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) - [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ] - - See Also - -------- - diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dcumax/examples/c/example.c deleted file mode 100644 index 90fc82870ad7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/examples/c/example.c +++ /dev/null @@ -1,41 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumax.h" -#include - -int main( void ) { - // Create strided arrays: - const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; - double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; - - // Specify the number of elements: - const int N = 4; - - // Specify stride lengths: - const int strideX = 2; - const int strideY = -2; - - // Compute the cumulative maximum: - stdlib_strided_dcumax( N, x, strideX, y, strideY ); - - // Print the result: - for ( int i = 0; i < 8; i++ ) { - printf( "y[ %d ] = %lf\n", i, y[ i ] ); - } -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/index.js b/lib/node_modules/@stdlib/stats/base/dcumax/lib/index.js deleted file mode 100644 index 597c2f111bb7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/lib/index.js +++ /dev/null @@ -1,70 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Compute the cumulative maximum of double-precision floating-point strided array elements. -* -* @module @stdlib/stats/base/dcumax -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var dcumax = require( '@stdlib/stats/base/dcumax' ); -* -* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var y = new Float64Array( x.length ); -* -* dcumax( x.length, x, 1, y, 1 ); -* // y => [ 1.0, 1.0, 2.0 ] -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var dcumax = require( '@stdlib/stats/base/dcumax' ); -* -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var y = new Float64Array( x.length ); -* -* dcumax.ndarray( 4, x, 2, 1, y, 1, 0 ); -* // y => [ 1.0, 1.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] -*/ - -// MODULES // - -var join = require( 'path' ).join; -var tryRequire = require( '@stdlib/utils/try-require' ); -var isError = require( '@stdlib/assert/is-error' ); -var main = require( './main.js' ); - - -// MAIN // - -var dcumax; -var tmp = tryRequire( join( __dirname, './native.js' ) ); -if ( isError( tmp ) ) { - dcumax = main; -} else { - dcumax = tmp; -} - - -// EXPORTS // - -module.exports = dcumax; - -// exports: { "ndarray": "dcumax.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/package.json b/lib/node_modules/@stdlib/stats/base/dcumax/package.json deleted file mode 100644 index e483fd781d33..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/package.json +++ /dev/null @@ -1,79 +0,0 @@ -{ - "name": "@stdlib/stats/base/dcumax", - "version": "0.0.0", - "description": "Calculate the cumulative maximum of double-precision floating-point strided array elements.", - "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "browser": "./lib/main.js", - "gypfile": true, - "directories": { - "benchmark": "./benchmark", - "doc": "./docs", - "example": "./examples", - "include": "./include", - "lib": "./lib", - "src": "./src", - "test": "./test" - }, - "types": "./docs/types", - "scripts": {}, - "homepage": "https://github.com/stdlib-js/stdlib", - "repository": { - "type": "git", - "url": "git://github.com/stdlib-js/stdlib.git" - }, - "bugs": { - "url": "https://github.com/stdlib-js/stdlib/issues" - }, - "dependencies": {}, - "devDependencies": {}, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], - "keywords": [ - "stdlib", - "stdmath", - "statistics", - "stats", - "mathematics", - "math", - "maximum", - "max", - "range", - "extremes", - "domain", - "extent", - "accumulate", - "cumulative", - "strided", - "strided array", - "typed", - "array", - "float64", - "double", - "float64array" - ], - "__stdlib__": {} -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/src/addon.c b/lib/node_modules/@stdlib/stats/base/dcumax/src/addon.c deleted file mode 100644 index 20e8fa924a4e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/src/addon.c +++ /dev/null @@ -1,64 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumax.h" -#include "stdlib/napi/export.h" -#include "stdlib/napi/argv.h" -#include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_strided_float64array.h" -#include - -/** -* Receives JavaScript callback invocation data. -* -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); - stdlib_strided_dcumax( N, X, strideX, Y, strideY ); - return NULL; -} - -/** -* Receives JavaScript callback invocation data. -* -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon_method( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); - STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_dcumax_ndarray( N, X, strideX, offsetX, Y, strideY, offsetY ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/src/main.c b/lib/node_modules/@stdlib/stats/base/dcumax/src/main.c deleted file mode 100644 index a672c711532b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumax/src/main.c +++ /dev/null @@ -1,91 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumax.h" -#include "stdlib/blas/base/shared.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_positive_zero.h" -#include "stdlib/strided/base/stride2offset.h" - -/** -* Computes the cumulative maximum of double-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void API_SUFFIX(stdlib_strided_dcumax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) { - const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); - const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); - API_SUFFIX(stdlib_strided_dcumax_ndarray)( N, X, strideX, ox, Y, strideY, oy ); - return; -} - -/** -* Computes the cumulative maximum of double-precision floating-point strided array elements using alternative indexing semantics. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param offsetX starting index for X -* @param Y output array -* @param strideY Y stride length -* @param offsetY starting index for Y -*/ -void API_SUFFIX(stdlib_strided_dcumax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { - CBLAS_INT ix; - CBLAS_INT iy; - CBLAS_INT i; - double max; - double v; - - if ( N <= 0 ) { - return; - } - ix = offsetX; - iy = offsetY; - max = X[ ix ]; - Y[ iy ] = max; - - iy += strideY; - i = 1; - if ( !stdlib_base_is_nan( max ) ) { - for (; i < N; i++ ) { - ix += strideX; - v = X[ ix ]; - if ( stdlib_base_is_nan( v ) ) { - max = v; - break; - } - if ( v > max || ( v == max && stdlib_base_is_positive_zero( v ) ) ) { - max = v; - } - Y[ iy ] = max; - iy += strideY; - } - } - if ( stdlib_base_is_nan( max ) ) { - for (; i < N; i++ ) { - Y[ iy ] = max; - iy += strideY; - } - } - return; -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md deleted file mode 100644 index 68619273f235..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md +++ /dev/null @@ -1,214 +0,0 @@ - - -# dcumaxabs - -> Calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - -
- -
- - - -
- -## Usage - -```javascript -var dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' ); -``` - -#### dcumaxabs( N, x, strideX, y, strideY ) - -Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var y = new Float64Array( x.length ); - -dcumaxabs( x.length, x, 1, y, 1 ); -// y => [ 1.0, 2.0, 2.0 ] -``` - -The function has the following parameters: - -- **N**: number of indexed elements. -- **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: index increment for `x`. -- **y**: output [`Float64Array`][@stdlib/array/float64]. -- **strideY**: index increment for `y`. - -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in `x`, - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var y = new Float64Array( x.length ); - -var v = dcumaxabs( 4, x, 2, y, 1 ); -// y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] -``` - -Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - - - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -// Initial arrays... -var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var y0 = new Float64Array( x0.length ); - -// Create offset views... -var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element - -dcumaxabs( 4, x1, -2, y1, 1 ); -// y0 => [ 0.0, 0.0, 0.0, 4.0, 4.0, 4.0, 4.0, 0.0 ] -``` - -#### dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) - -Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics. - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var y = new Float64Array( x.length ); - -dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 ); -// y => [ 1.0, 2.0, 2.0 ] -``` - -The function has the following additional parameters: - -- **offsetX**: starting index for `x`. -- **offsetY**: starting index for `y`. - -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum absolute value of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var y = new Float64Array( x.length ); - -dcumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); -// y => [ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0 ] -``` - -
- - - -
- -## Notes - -- If `N <= 0`, both functions return `y` unchanged. - -
- - - -
- -## Examples - - - -```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' ); - -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} -console.log( x ); -console.log( y ); - -dcumaxabs( x.length, x, 1, y, -1 ); -console.log( y ); -``` - -
- - - -
- -
- - - - - -
- -* * * - -## See Also - -- [`@stdlib/stats/base/cumaxabs`][@stdlib/stats/base/cumaxabs]: calculate the cumulative maximum absolute value of a strided array. -- [`@stdlib/stats/base/dcumax`][@stdlib/stats/base/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. -- [`@stdlib/stats/base/dcuminabs`][@stdlib/stats/base/dcuminabs]: calculate the cumulative minimum absolute value of double-precision floating-point strided array elements. -- [`@stdlib/stats/base/scumaxabs`][@stdlib/stats/base/scumaxabs]: calculate the cumulative maximum absolute value of single-precision floating-point strided array elements. - -
- - - - - -
- -[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 - -[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray - - - -[@stdlib/stats/base/cumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumaxabs - -[@stdlib/stats/base/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumax - -[@stdlib/stats/base/dcuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcuminabs - -[@stdlib/stats/base/scumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumaxabs - - - -
- - diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js deleted file mode 100644 index 76350238b628..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js +++ /dev/null @@ -1,102 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var pkg = require( './../package.json' ).name; -var dcumaxabs = require( './../lib/dcumaxabs.js' ); - - -// FUNCTIONS // - -/** -* Creates a benchmark function. -* -* @private -* @param {PositiveInteger} len - array length -* @returns {Function} benchmark function -*/ -function createBenchmark( len ) { - var y; - var x; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - return benchmark; - - function benchmark( b ) { - var v; - var i; - - for ( i = 0; i < len; i++ ) { - y[ i ] = 0.0; - } - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - x[ 0 ] += 1.0; - v = dcumaxabs( x.length, x, 1, y, 1 ); - if ( isnan( v[ i%len ] ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( v[ i%len ] ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); - } -} - - -// MAIN // - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - var len; - var min; - var max; - var f; - var i; - - min = 1; // 10^min - max = 6; // 10^max - - for ( i = min; i <= max; i++ ) { - len = pow( 10, i ); - f = createBenchmark( len ); - bench( pkg+':len='+len, f ); - } -} - -main(); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js deleted file mode 100644 index eb4a06ac6037..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js +++ /dev/null @@ -1,111 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var resolve = require( 'path' ).resolve; -var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var tryRequire = require( '@stdlib/utils/try-require' ); -var pkg = require( './../package.json' ).name; - - -// VARIABLES // - -var dcumaxabs = tryRequire( resolve( __dirname, './../lib/dcumaxabs.native.js' ) ); -var opts = { - 'skip': ( dcumaxabs instanceof Error ) -}; - - -// FUNCTIONS // - -/** -* Creates a benchmark function. -* -* @private -* @param {PositiveInteger} len - array length -* @returns {Function} benchmark function -*/ -function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - return benchmark; - - function benchmark( b ) { - var v; - var i; - - for ( i = 0; i < len; i++ ) { - y[ i ] = 0.0; - } - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - x[ 0 ] += 1.0; - v = dcumaxabs( x.length, x, 1, y, 1 ); - if ( isnan( v[ i%len ] ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( v[ i%len ] ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); - } -} - - -// MAIN // - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - var len; - var min; - var max; - var f; - var i; - - min = 1; // 10^min - max = 6; // 10^max - - for ( i = min; i <= max; i++ ) { - len = pow( 10, i ); - f = createBenchmark( len ); - bench( pkg+'::native:len='+len, opts, f ); - } -} - -main(); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js deleted file mode 100644 index 480d986ef97d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js +++ /dev/null @@ -1,102 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var pkg = require( './../package.json' ).name; -var dcumaxabs = require( './../lib/ndarray.js' ); - - -// FUNCTIONS // - -/** -* Creates a benchmark function. -* -* @private -* @param {PositiveInteger} len - array length -* @returns {Function} benchmark function -*/ -function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - return benchmark; - - function benchmark( b ) { - var v; - var i; - - for ( i = 0; i < len; i++ ) { - y[ i ] = 0.0; - } - b.tic(); - for ( i = 0; i < b.iterations; i++ ) { - x[ 0 ] += 1.0; - v = dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - if ( isnan( v[ i%len ] ) ) { - b.fail( 'should not return NaN' ); - } - } - b.toc(); - if ( isnan( v[ i%len ] ) ) { - b.fail( 'should not return NaN' ); - } - b.pass( 'benchmark finished' ); - b.end(); - } -} - - -// MAIN // - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - var len; - var min; - var max; - var f; - var i; - - min = 1; // 10^min - max = 6; // 10^max - - for ( i = min; i <= max; i++ ) { - len = pow( 10, i ); - f = createBenchmark( len ); - bench( pkg+':ndarray:len='+len, f ); - } -} - -main(); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c deleted file mode 100644 index a0b0a030c0ff..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c +++ /dev/null @@ -1,152 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumaxabs.h" -#include -#include -#include -#include -#include - -#define NAME "dcumaxabs" -#define ITERATIONS 1000000 -#define REPEATS 3 -#define MIN 1 -#define MAX 6 - -/** -* Prints the TAP version. -*/ -static void print_version( void ) { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -static void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param iterations number of iterations -* @param elapsed elapsed time in seconds -*/ -static void print_results( int iterations, double elapsed ) { - double rate = (double)iterations / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", iterations ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -static double tic( void ) { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec/1.0e6; -} - -/** -* Generates a random number on the interval [0,1). -* -* @return random number -*/ -static double rand_double( void ) { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @param iterations number of iterations -* @param len array length -* @return elapsed time in seconds -*/ -static double benchmark( int iterations, int len ) { - double elapsed; - double x[ len ]; - double y[ len ]; - double t; - int i; - - for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; - y[ i ] = 0.0; - } - t = tic(); - for ( i = 0; i < iterations; i++ ) { - x[ 0 ] += 1.0; - stdlib_strided_dcumaxabs( len, x, 1, y, 1 ); - if ( y[ 0 ] != y[ 0 ] ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( y[ len-1 ] != y[ len-1 ] ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int count; - int iter; - int len; - int i; - int j; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - count = 0; - for ( i = MIN; i <= MAX; i++ ) { - len = pow( 10, i ); - iter = ITERATIONS / pow( 10, i-1 ); - for ( j = 0; j < REPEATS; j++ ) { - count += 1; - printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); - print_results( iter, elapsed ); - printf( "ok %d benchmark finished\n", count ); - } - } - print_summary( count, count ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt deleted file mode 100644 index a636769b4644..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt +++ /dev/null @@ -1,115 +0,0 @@ - -{{alias}}( N, x, strideX, y, strideY ) - Computes the cumulative maximum absolute value of double-precision floating- - point strided array elements. - - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. - - Indexing is relative to the first index. To introduce an offset, use a typed - array view. - - If `N <= 0`, the function returns `y` unchanged. - - Parameters - ---------- - N: integer - Number of indexed elements. - - x: Float64Array - Input array. - - strideX: integer - Index increment for `x`. - - y: Float64Array - Output array. - - strideY: integer - Index increment for `y`. - - Returns - ------- - out: Float64Array - Output array. - - Examples - -------- - // Standard Usage: - > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); - > var y = new {{alias:@stdlib/array/float64}}( x.length ); - > {{alias}}( x.length, x, 1, y, 1 ) - [ 1.0, 2.0, 2.0 ] - - // Using `N` and `stride` parameters: - > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > y = new {{alias:@stdlib/array/float64}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, y, 2 ) - [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ] - - // Using view offsets: - > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); - > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, y1, 1 ) - [ 2.0, 2.0, 2.0 ] - > y0 - [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] - -{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) - Computes the cumulative maximum absolute value of double-precision floating- - point strided array elements using alternative indexing semantics. - - While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a - starting index. - - Parameters - ---------- - N: integer - Number of indexed elements. - - x: Float64Array - Input array. - - strideX: integer - Index increment for `x`. - - offsetX: integer - Starting index for `x`. - - y: Float64Array - Output array. - - strideY: integer - Index increment for `y`. - - offsetY: integer - Starting index for `y`. - - Returns - ------- - out: Float64Array - Output array. - - Examples - -------- - // Standard Usage: - > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); - > var y = new {{alias:@stdlib/array/float64}}( x.length ); - > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) - [ 1.0, 2.0, 2.0 ] - - // Advanced indexing: - > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > y = new {{alias:@stdlib/array/float64}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 ) - [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] - - See Also - -------- - diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c deleted file mode 100644 index 08a88e6495eb..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c +++ /dev/null @@ -1,43 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumaxabs.h" -#include -#include -#include - -int main( void ) { - // Create strided arrays: - double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; - double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; - - // Specify the number of elements: - int64_t N = 4; - - // Specify stride lengths: - int64_t strideX = 2; - int64_t strideY = -2; - - // Compute the cumulative maximum absolute value: - stdlib_strided_dcumaxabs( N, x, strideX, y, strideY ); - - // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %lf\n", i, y[ i ] ); - } -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js deleted file mode 100644 index b256fa90068d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js +++ /dev/null @@ -1,39 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var dcumaxabs = require( './../lib' ); - -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} -console.log( x ); -console.log( y ); - -dcumaxabs( x.length, x, 1, y, -1 ); -console.log( y ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h b/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h deleted file mode 100644 index 2d243d91c3ac..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h +++ /dev/null @@ -1,40 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#ifndef STDLIB_STATS_BASE_DCUMAXABS_H -#define STDLIB_STATS_BASE_DCUMAXABS_H - -#include - -/* -* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. -*/ -#ifdef __cplusplus -extern "C" { -#endif - -/** -* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. -*/ -void stdlib_strided_dcumaxabs( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY ); - -#ifdef __cplusplus -} -#endif - -#endif // !STDLIB_STATS_BASE_DCUMAXABS_H diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js deleted file mode 100644 index 68600c13c717..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js +++ /dev/null @@ -1,101 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); - - -// MAIN // - -/** -* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. -* -* @param {PositiveInteger} N - number of indexed elements -* @param {Float64Array} x - input array -* @param {integer} strideX - `x` stride length -* @param {Float64Array} y - output array -* @param {integer} strideY - `y` stride length -* @returns {Float64Array} output array -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* -* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var y = new Float64Array( x.length ); -* var N = x.length; -* -* var v = dcumaxabs( N, x, 1, y, 1 ); -* // returns [ 1.0, 2.0, 2.0 ] -*/ -function dcumaxabs( N, x, strideX, y, strideY ) { - var max; - var ix; - var iy; - var v; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - max = abs( x[ ix ] ); - y[ iy ] = max; - - iy += strideY; - i = 1; - if ( isnan( max ) === false ) { - for ( i; i < N; i++ ) { - ix += strideX; - v = abs( x[ ix ] ); - if ( isnan( v ) ) { - max = v; - break; - } - if ( v > max ) { - max = v; - } - y[ iy ] = max; - iy += strideY; - } - } - if ( isnan( max ) ) { - for ( i; i < N; i++ ) { - y[ iy ] = max; - iy += strideY; - } - } - return y; -} - - -// EXPORTS // - -module.exports = dcumaxabs; diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js deleted file mode 100644 index c58d8b9ff1f5..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Compute the cumulative maximum absolute value of double-precision floating-point strided array elements. -* -* @module @stdlib/stats/base/dcumaxabs -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' ); -* -* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var y = new Float64Array( x.length ); -* var N = x.length; -* -* dcumaxabs( N, x, 1, y, 1 ); -* // y => [ 1.0, 2.0, 2.0 ] -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); -* var dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' ); -* -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var y = new Float64Array( x.length ); -* var N = floor( x.length / 2 ); -* -* dcumaxabs.ndarray( N, x, 2, 1, y, 1, 0 ); -* // y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] -*/ - -// MODULES // - -var join = require( 'path' ).join; -var tryRequire = require( '@stdlib/utils/try-require' ); -var isError = require( '@stdlib/assert/is-error' ); -var main = require( './main.js' ); - - -// MAIN // - -var dcumaxabs; -var tmp = tryRequire( join( __dirname, './native.js' ) ); -if ( isError( tmp ) ) { - dcumaxabs = main; -} else { - dcumaxabs = tmp; -} - - -// EXPORTS // - -module.exports = dcumaxabs; - -// exports: { "ndarray": "dcumaxabs.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js deleted file mode 100644 index c3199145be6d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js +++ /dev/null @@ -1,97 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); - - -// MAIN // - -/** -* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. -* -* @param {PositiveInteger} N - number of indexed elements -* @param {Float64Array} x - input array -* @param {integer} strideX - `x` stride length -* @param {NonNegativeInteger} offsetX - starting index for `x` -* @param {Float64Array} y - output array -* @param {integer} strideY - `y` stride length -* @param {NonNegativeInteger} offsetY - starting index for `y` -* @returns {Float64Array} output array -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); -* -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var y = new Float64Array( x.length ); -* var N = floor( x.length / 2 ); -* -* var v = dcumaxabs( N, x, 2, 1, y, 1, 0 ); -* // returns [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] -*/ -function dcumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { - var max; - var ix; - var iy; - var v; - var i; - - if ( N <= 0 ) { - return y; - } - ix = offsetX; - iy = offsetY; - - max = abs( x[ ix ] ); - y[ iy ] = max; - - iy += strideY; - i = 1; - if ( isnan( max ) === false ) { - for ( i; i < N; i++ ) { - ix += strideX; - v = abs( x[ ix ] ); - if ( isnan( v ) ) { - max = v; - break; - } - if ( v > max ) { - max = v; - } - y[ iy ] = max; - iy += strideY; - } - } - if ( isnan( max ) ) { - for ( i; i < N; i++ ) { - y[ iy ] = max; - iy += strideY; - } - } - return y; -} - - -// EXPORTS // - -module.exports = dcumaxabs; diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js deleted file mode 100644 index c2fe95eb62bd..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js +++ /dev/null @@ -1,70 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dcumaxabs.native.js' ); - - -// MAIN // - -/** -* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. -* -* @param {PositiveInteger} N - number of indexed elements -* @param {Float64Array} x - input array -* @param {integer} strideX - `x` stride length -* @param {NonNegativeInteger} offsetX - starting index for `x` -* @param {Float64Array} y - output array -* @param {integer} strideY - `y` stride length -* @param {NonNegativeInteger} offsetY - starting index for `y` -* @returns {Float64Array} output array -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); -* -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var y = new Float64Array( x.length ); -* var N = floor( x.length / 2 ); -* -* var v = dcumaxabs( N, x, 2, 1, y, 1, 0 ); -* // returns [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] -*/ -function dcumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideY < 0 ) { - offsetY += (N-1) * strideY; - } - viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewY = new Float64Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len - addon( N, viewX, strideX, viewY, strideY ); - return y; -} - - -// EXPORTS // - -module.exports = dcumaxabs; diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json b/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json deleted file mode 100644 index 25901c023456..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json +++ /dev/null @@ -1,81 +0,0 @@ -{ - "options": { - "task": "build" - }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "src": [ - "./src/dcumaxabs.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/napi/export", - "@stdlib/napi/argv", - "@stdlib/napi/argv-int64", - "@stdlib/napi/argv-strided-float64array" - ] - }, - { - "task": "benchmark", - "src": [ - "./src/dcumaxabs.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nan" - ] - }, - { - "task": "examples", - "src": [ - "./src/dcumaxabs.c" - ], - "include": [ - "./include" - ], - "libraries": [ - "-lm" - ], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nan" - ] - } - ] -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/package.json b/lib/node_modules/@stdlib/stats/base/dcumaxabs/package.json deleted file mode 100644 index 97f454f9d3e4..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/package.json +++ /dev/null @@ -1,82 +0,0 @@ -{ - "name": "@stdlib/stats/base/dcumaxabs", - "version": "0.0.0", - "description": "Calculate the cumulative maximum absolute value of double-precision floating-point strided array elements.", - "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "browser": "./lib/main.js", - "gypfile": true, - "directories": { - "benchmark": "./benchmark", - "doc": "./docs", - "example": "./examples", - "include": "./include", - "lib": "./lib", - "src": "./src", - "test": "./test" - }, - "types": "./docs/types", - "scripts": {}, - "homepage": "https://github.com/stdlib-js/stdlib", - "repository": { - "type": "git", - "url": "git://github.com/stdlib-js/stdlib.git" - }, - "bugs": { - "url": "https://github.com/stdlib-js/stdlib/issues" - }, - "dependencies": {}, - "devDependencies": {}, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], - "keywords": [ - "stdlib", - "stdmath", - "statistics", - "stats", - "mathematics", - "math", - "maximum", - "max", - "abs", - "absolute", - "absolute value", - "range", - "extremes", - "domain", - "extent", - "accumulate", - "cumulative", - "strided", - "strided array", - "typed", - "array", - "float64", - "double", - "float64array" - ], - "__stdlib__": {} -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c deleted file mode 100644 index 7d4b140b720d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c +++ /dev/null @@ -1,44 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumaxabs.h" -#include "stdlib/napi/export.h" -#include "stdlib/napi/argv.h" -#include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_strided_float64array.h" -#include - -/** -* Receives JavaScript callback invocation data. -* -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); - stdlib_strided_dcumaxabs( N, X, strideX, Y, strideY ); - return NULL; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/dcumaxabs.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/dcumaxabs.c deleted file mode 100644 index ea4beb7588d7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/dcumaxabs.c +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumaxabs.h" -#include "stdlib/math/base/assert/is_nan.h" -#include -#include - -/** -* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_dcumaxabs( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY ) { - double max; - int64_t ix; - int64_t iy; - int64_t i; - double v; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - max = fabs( X[ ix ] ); - Y[ iy ] = max; - - iy += strideY; - i = 1; - if ( !stdlib_base_is_nan( max ) ) { - for (; i < N; i++ ) { - ix += strideX; - v = fabs( X[ ix ] ); - if ( stdlib_base_is_nan( v ) ) { - max = v; - break; - } - if ( v > max ) { - max = v; - } - Y[ iy ] = max; - iy += strideY; - } - } - if ( stdlib_base_is_nan( max ) ) { - for (; i < N; i++ ) { - Y[ iy ] = max; - iy += strideY; - } - } - return; -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js deleted file mode 100644 index 64557c688973..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js +++ /dev/null @@ -1,341 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); -var Float64Array = require( '@stdlib/array/float64' ); -var dcumaxabs = require( './../lib/ndarray.js' ); - - -// TESTS // - -tape( 'main export is a function', function test( t ) { - t.ok( true, __filename ); - t.strictEqual( typeof dcumaxabs, 'function', 'main export is a function' ); - t.end(); -}); - -tape( 'the function has an arity of 7', function test( t ) { - t.strictEqual( dcumaxabs.length, 7, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the cumulative maximum absolute value', function test( t ) { - var expected; - var x; - var y; - var i; - - x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] ); - y = new Float64Array( x.length ); - dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - - expected = new Float64Array([ - 1.0, - 2.0, - 3.0, - 4.0, - 5.0 - ]); - t.deepEqual( y, expected, 'returns expected value' ); - - x = new Float64Array( [ -0.0, 0.0, -0.0 ] ); - y = new Float64Array( x.length ); - dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - - expected = new Float64Array([ - 0.0, - 0.0, - 0.0 - ]); - for ( i = 0; i < y.length; i++ ) { - if ( isPositiveZero( expected[ i ] ) ) { - t.strictEqual( isPositiveZero( y[ i ] ), true, 'returns expected value. i: ' + i ); - } else { - t.strictEqual( y[ i ], expected[ i ], true, 'returns expected value. i: ' + i ); - } - } - - x = new Float64Array( [ NaN ] ); - y = new Float64Array( x.length ); - dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - - for ( i = 0; i < y.length; i++ ) { - t.strictEqual( isnan( y[ i ] ), true, 'returns expected value. i: ' + i ); - } - - x = new Float64Array( [ NaN, NaN ] ); - y = new Float64Array( x.length ); - dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - - for ( i = 0; i < y.length; i++ ) { - t.strictEqual( isnan( y[ i ] ), true, 'returns expected value. i: ' + i ); - } - - x = new Float64Array( [ 1.0, NaN, 3.0, NaN ] ); - y = new Float64Array( x.length ); - dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - - expected = new Float64Array([ - 1.0, - NaN, - NaN, - NaN - ]); - for ( i = 0; i < y.length; i++ ) { - if ( isnan( expected[ i ] ) ) { - t.strictEqual( isnan( y[ i ] ), true, 'returns expected value. i: ' + i ); - } else { - t.strictEqual( y[ i ], expected[ i ], true, 'returns expected value. i: ' + i ); - } - } - t.end(); -}); - -tape( 'the function returns a reference to the output array', function test( t ) { - var out; - var x; - var y; - - x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); - y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); - - out = dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); - t.strictEqual( out, y, 'same reference' ); - - t.end(); -}); - -tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { - var expected; - var x; - var y; - - x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); - y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); - - expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); - - dcumaxabs( -1, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns `y` unchanged' ); - - dcumaxabs( 0, x, 1, 0, y, 1, 0 ); - t.deepEqual( y, expected, 'returns `y` unchanged' ); - - t.end(); -}); - -tape( 'the function supports an `x` stride', function test( t ) { - var expected; - var x; - var y; - var N; - - x = new Float64Array([ - 1.0, // 0 - -2.0, - 3.0, // 1 - 4.0, - -5.0 // 2 - ]); - y = new Float64Array([ - 0.0, // 0 - 0.0, // 1 - 0.0, // 2 - 0.0, - 0.0 - ]); - N = 3; - - dcumaxabs( N, x, 2, 0, y, 1, 0 ); - - expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); - t.deepEqual( y, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports a `y` stride', function test( t ) { - var expected; - var x; - var y; - var N; - - x = new Float64Array([ - 1.0, // 0 - -2.0, // 1 - 3.0, // 2 - 4.0, - 5.0 - ]); - y = new Float64Array([ - 0.0, // 0 - 0.0, - 0.0, // 1 - 0.0, - 0.0 // 2 - ]); - N = 3; - - dcumaxabs( N, x, 1, 0, y, 2, 0 ); - - expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); - t.deepEqual( y, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports negative strides', function test( t ) { - var expected; - var x; - var y; - var N; - - x = new Float64Array([ - 1.0, // 2 - -2.0, - 3.0, // 1 - 4.0, - -5.0 // 0 - ]); - y = new Float64Array([ - 0.0, // 2 - 0.0, // 1 - 0.0, // 0 - 0.0, - 0.0 - ]); - N = 3; - - dcumaxabs( N, x, -2, x.length-1, y, -1, 2 ); - - expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); - t.deepEqual( y, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports an `x` offset', function test( t ) { - var expected; - var N; - var x; - var y; - - x = new Float64Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - y = new Float64Array([ - 0.0, // 0 - 0.0, // 1 - 0.0, // 2 - 0.0, // 3 - 0.0, - 0.0, - 0.0, - 0.0 - ]); - N = floor( x.length / 2 ); - - dcumaxabs( N, x, 2, 1, y, 1, 0 ); - - expected = new Float64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); - t.deepEqual( y, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports a `y` offset', function test( t ) { - var expected; - var N; - var x; - var y; - - x = new Float64Array([ - 2.0, // 0 - 1.0, // 1 - 2.0, // 2 - -2.0, // 3 - -2.0, - 2.0, - 3.0, - 4.0 - ]); - y = new Float64Array([ - 0.0, - 0.0, // 0 - 0.0, - 0.0, // 1 - 0.0, - 0.0, // 2 - 0.0, - 0.0 // 3 - ]); - N = floor( x.length / 2 ); - - dcumaxabs( N, x, 1, 0, y, 2, 1 ); - - expected = new Float64Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] ); - t.deepEqual( y, expected, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function supports complex access patterns', function test( t ) { - var expected; - var x; - var y; - var N; - - x = new Float64Array([ - 1.0, // 0 - 2.0, - -3.0, // 1 - 4.0, - 5.0, // 2 - 6.0 - ]); - y = new Float64Array([ - 0.0, // 2 - 0.0, // 1 - 0.0, // 0 - 0.0, - 0.0, - 0.0 - ]); - N = 3; - - dcumaxabs( N, x, 2, 0, y, -1, 2 ); - - expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); - t.deepEqual( y, expected, 'returns expected value' ); - - t.end(); -}); diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/README.md b/lib/node_modules/@stdlib/stats/base/dcumin/README.md index 3439c8de3e3f..dde62b4456a3 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/README.md +++ b/lib/node_modules/@stdlib/stats/base/dcumin/README.md @@ -18,6 +18,8 @@ limitations under the License. --> + + # dcumin > Calculate the cumulative minimum of double-precision floating-point strided array elements. @@ -54,11 +56,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float64Array`][@stdlib/array/float64]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -108,7 +110,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative minimum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -141,21 +143,16 @@ dcumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var dcumin = require( '@stdlib/stats/base/dcumin' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); + +var y = new Float64Array( x.length ); console.log( y ); dcumin( x.length, x, 1, y, -1 ); @@ -166,6 +163,132 @@ console.log( y ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dcumin.h" +``` + +#### stdlib_strided_dcumin( N, \*X, strideX, \*Y, strideY ) + +Computes the cumulative minimum of double-precision floating-point strided array elements. + +```c +const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dcumin( 4, x, 2, y, -2 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_dcumin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_dcumin_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + +Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dcumin_ndarray( 4, x, 2, 0, y, -2, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_dcumin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dcumin.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; + double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative minimum: + stdlib_strided_dcumin( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %lf\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
@@ -181,7 +304,7 @@ console.log( y ); ## See Also - [`@stdlib/stats/base/cumin`][@stdlib/stats/base/cumin]: calculate the cumulative minimum of a strided array. -- [`@stdlib/stats/base/dcumax`][@stdlib/stats/base/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. +- [`@stdlib/stats/strided/dcumax`][@stdlib/stats/strided/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. - [`@stdlib/stats/base/scumin`][@stdlib/stats/base/scumin]: calculate the cumulative minimum of single-precision floating-point strided array elements. @@ -200,7 +323,7 @@ console.log( y ); [@stdlib/stats/base/cumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumin -[@stdlib/stats/base/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumax +[@stdlib/stats/strided/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumax [@stdlib/stats/base/scumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumin diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js index 1dcde9f45060..334eca929bf8 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var dcumin = require( './../lib/dcumin.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var dcumin = require( './../lib/dcumin.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js index f63416764679..1e32c2356cde 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -36,6 +36,9 @@ var dcumin = tryRequire( resolve( __dirname, './../lib/dcumin.native.js' ) ); var opts = { 'skip': ( dcumin instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js index edb7e32a3470..3f097ae0f0c3 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var dcumin = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var dcumin = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js index 6045616a009f..954d6b0c8e9c 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -36,6 +36,9 @@ var dcumin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dcumin instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c index f890722d543c..542f7963e291 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + y[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dcumin_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt index 23e69025e980..ea8d011fce54 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative minimum of double-precision floating-point strided array elements. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,13 +20,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float64Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -44,8 +44,7 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float64}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, y, 2 ) + > {{alias}}( 3, x, 2, y, 2 ) [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ] // Using view offsets: @@ -53,12 +52,12 @@ > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, y1, 1 ) + > {{alias}}( 3, x1, 2, y1, 1 ) [ -2.0, -2.0, -2.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ] + {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics. @@ -76,7 +75,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -85,7 +84,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -106,8 +105,7 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float64}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 ) + > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c index 68aceb555659..ed1876ec1c2e 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/stats/base/dcumin.h" -#include #include -#include int main( void ) { // Create strided arrays: - double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify stride lengths: - int64_t strideX = 2; - int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative minimum: stdlib_strided_dcumin( N, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %lf\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %lf\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js b/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js index 5674c935f426..089eab0aa2b7 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js @@ -18,21 +18,16 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float64Array = require( '@stdlib/array/float64' ); var dcumin = require( './../lib' ); -var y; -var x; -var i; - -x = new Float64Array( 10 ); -y = new Float64Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); + +var y = new Float64Array( x.length ); console.log( y ); dcumin( x.length, x, 1, y, -1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h b/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h index bdf7b4f03623..2072e32aabfb 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h +++ b/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DCUMIN_H #define STDLIB_STATS_BASE_DCUMIN_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative minimum of double-precision floating-point strided array elements. */ -void stdlib_strided_dcumin( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_dcumin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_dcumin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js index 903fcb23e34c..301a08001fa5 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -41,58 +41,14 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float64Array( x.length ); -* var N = x.length; * -* var v = dcumin( N, x, 1, y, 1 ); +* var v = dcumin( x.length, x, 1, y, 1 ); * // returns [ 1.0, -2.0, -2.0 ] */ function dcumin( N, x, strideX, y, strideY ) { - var min; - var ix; - var iy; - var v; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - min = x[ ix ]; - y[ iy ] = min; - - iy += strideY; - i = 1; - if ( isnan( min ) === false ) { - for ( i; i < N; i++ ) { - ix += strideX; - v = x[ ix ]; - if ( isnan( v ) ) { - min = v; - break; - } - if ( v < min || ( v === min && isNegativeZero( v ) ) ) { - min = v; - } - y[ iy ] = min; - iy += strideY; - } - } - if ( isnan( min ) ) { - for ( i; i < N; i++ ) { - y[ iy ] = min; - iy += strideY; - } - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js index 7d8f37a83a13..0700b4a5fd84 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js @@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float64Array( x.length ); -* var N = x.length; * -* var v = dcumin( N, x, 1, y, 1 ); +* var v = dcumin( x.length, x, 1, y, 1 ); * // returns [ 1.0, -2.0, -2.0 ] */ function dcumin( N, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js index 6b07d0f2a275..94872e121c51 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float64Array( x.length ); -* var N = x.length; * -* dcumin( N, x, 1, y, 1 ); +* dcumin( x.length, x, 1, y, 1 ); * // y => [ 1.0, -2.0, -2.0 ] * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dcumin = require( '@stdlib/stats/base/dcumin' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float64Array( x.length ); -* var N = floor( x.length / 2 ); * -* dcumin.ndarray( N, x, 2, 1, y, 1, 0 ); +* dcumin.ndarray( 4, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js index db660dea12f5..49e575254e95 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js @@ -40,13 +40,11 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float64Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = dcumin( N, x, 2, 1, y, 1, 0 ); +* var v = dcumin( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] */ function dcumin( N, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js index c55627c62cf6..99498beff430 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dcumin.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -40,27 +39,15 @@ var addon = require( './dcumin.native.js' ); * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float64Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = dcumin( N, x, 2, 1, y, 1, 0 ); +* var v = dcumin( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] */ function dcumin( N, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideY < 0 ) { - offsetY += (N-1) * strideY; - } - viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewY = new Float64Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len - addon( N, viewX, strideX, viewY, strideY ); + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json b/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json index 35026eba7713..09770f614dd4 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dcumin.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-negative-zero", "@stdlib/math/base/assert/is-nan", "@stdlib/napi/export", @@ -48,34 +50,54 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dcumin.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-negative-zero", "@stdlib/math/base/assert/is-nan" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dcumin.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-negative-zero" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-negative-zero" ] diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c b/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c index 9613a6c56f24..c5486a010e8e 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c @@ -20,6 +20,7 @@ #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/argv_strided_float64array.h" #include @@ -37,8 +38,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); - stdlib_strided_dcumin( N, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_dcumin)( N, X, strideX, Y, strideY ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_dcumin_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/src/dcumin.c b/lib/node_modules/@stdlib/stats/base/dcumin/src/dcumin.c deleted file mode 100644 index 9dacb42a60d7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dcumin/src/dcumin.c +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dcumin.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_negative_zero.h" -#include - -/** -* Computes the cumulative minimum of double-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_dcumin( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY ) { - double min; - int64_t ix; - int64_t iy; - int64_t i; - double v; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - min = X[ ix ]; - Y[ iy ] = min; - - iy += strideY; - i = 1; - if ( !stdlib_base_is_nan( min ) ) { - for (; i < N; i++ ) { - ix += strideX; - v = X[ ix ]; - if ( stdlib_base_is_nan( v ) ) { - min = v; - break; - } - if ( v < min || ( v == min && stdlib_base_is_negative_zero( v ) ) ) { - min = v; - } - Y[ iy ] = min; - iy += strideY; - } - } - if ( stdlib_base_is_nan( min ) ) { - for (; i < N; i++ ) { - Y[ iy ] = min; - iy += strideY; - } - } - return; -} diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/src/main.c b/lib/node_modules/@stdlib/stats/base/dcumin/src/main.c new file mode 100644 index 000000000000..28d84fa6d19a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dcumin/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dcumin.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_negative_zero.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative minimum of double-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void API_SUFFIX(stdlib_strided_dcumin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_dcumin_ndarray)( N, X, strideX, ox, Y, strideY, oy ); + return; +} + +/** +* Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Y output array +* @param strideY Y stride length +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_dcumin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + double min; + double v; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + min = X[ ix ]; + Y[ iy ] = min; + + iy += strideY; + i = 1; + if ( !stdlib_base_is_nan( min ) ) { + for (; i < N; i++ ) { + ix += strideX; + v = X[ ix ]; + if ( stdlib_base_is_nan( v ) ) { + min = v; + break; + } + if ( v < min || ( v == min && stdlib_base_is_negative_zero( v ) ) ) { + min = v; + } + Y[ iy ] = min; + iy += strideY; + } + } + if ( stdlib_base_is_nan( min ) ) { + for (; i < N; i++ ) { + Y[ iy ] = min; + iy += strideY; + } + } + return; +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js index dd37e5768088..4bebc4892aa3 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, y, 1 ); + dcumin( 3, x, 2, y, 1 ); expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumin( N, x, 1, y, 2 ); + dcumin( 3, x, 1, y, 2 ); expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, -2, y, -1 ); + dcumin( 3, x, -2, y, -1 ); expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, y, -1 ); + dcumin( 3, x, 2, y, -1 ); expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float64Array([ @@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - dcumin( N, x1, -2, y1, 1 ); + dcumin( 3, x1, -2, y1, 1 ); expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js index 48b29100dfe4..e4b27dff4459 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, y, 1 ); + dcumin( 3, x, 2, y, 1 ); expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumin( N, x, 1, y, 2 ); + dcumin( 3, x, 1, y, 2 ); expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, -2, y, -1 ); + dcumin( 3, x, -2, y, -1 ); expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, y, -1 ); + dcumin( 3, x, 2, y, -1 ); expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float64Array([ @@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - dcumin( N, x1, -2, y1, 1 ); + dcumin( 3, x1, -2, y1, 1 ); expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js index 7ffcf66cc955..efff7548dc8d 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, 0, y, 1, 0 ); + dcumin( 3, x, 2, 0, y, 1, 0 ); expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumin( N, x, 1, 0, y, 2, 0 ); + dcumin( 3, x, 1, 0, y, 2, 0 ); expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, -2, x.length-1, y, -1, 2 ); + dcumin( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -238,7 +231,6 @@ tape( 'the function supports negative strides', function test( t ) { tape( 'the function supports an `x` offset', function test( t ) { var expected; - var N; var x; var y; @@ -262,9 +254,8 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - dcumin( N, x, 2, 1, y, 1, 0 ); + dcumin( 4, x, 2, 1, y, 1, 0 ); expected = new Float64Array( [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] ); // eslint-disable-line max-len t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports an `x` offset', function test( t ) { tape( 'the function supports a `y` offset', function test( t ) { var expected; - var N; var x; var y; @@ -298,9 +288,8 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - dcumin( N, x, 1, 0, y, 2, 1 ); + dcumin( 4, x, 1, 0, y, 2, 1 ); expected = new Float64Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -312,7 +301,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -330,9 +318,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, 0, y, -1, 2 ); + dcumin( 3, x, 2, 0, y, -1, 2 ); expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js index 15b46090035c..5a1ac760c683 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, 0, y, 1, 0 ); + dcumin( 3, x, 2, 0, y, 1, 0 ); expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumin( N, x, 1, 0, y, 2, 0 ); + dcumin( 3, x, 1, 0, y, 2, 0 ); expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumin( N, x, -2, x.length-1, y, -1, 2 ); + dcumin( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - dcumin( N, x, 2, 1, y, 1, 0 ); + dcumin( 4, x, 2, 1, y, 1, 0 ); expected = new Float64Array( [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] ); // eslint-disable-line max-len t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - dcumin( N, x, 1, 0, y, 2, 1 ); + dcumin( 4, x, 1, 0, y, 2, 1 ); expected = new Float64Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -321,7 +310,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -339,9 +327,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - dcumin( N, x, 2, 0, y, -1, 2 ); + dcumin( 3, x, 2, 0, y, -1, 2 ); expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md b/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md index ff669586b30e..a08dbe4f2a4b 100644 --- a/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md +++ b/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md @@ -18,6 +18,8 @@ limitations under the License. --> + + # dcuminabs > Calculate the cumulative minimum absolute value of double-precision floating-point strided array elements. @@ -108,7 +110,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative minimum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -210,7 +212,7 @@ The function accepts the following arguments: void stdlib_strided_dcuminabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); ``` -#### stdlib_strided_dcuminabs_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY) +#### stdlib_strided_dcuminabs_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) Computes the cumulative minumum absolute value of double-precision floating-point strided array elements using alternative indexing semantics. @@ -302,7 +304,7 @@ int main( void ) { ## See Also - [`@stdlib/stats/base/cuminabs`][@stdlib/stats/base/cuminabs]: calculate the cumulative minimum absolute value of a strided array. -- [`@stdlib/stats/base/dcumaxabs`][@stdlib/stats/base/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. +- [`@stdlib/stats/strided/dcumaxabs`][@stdlib/stats/strided/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - [`@stdlib/stats/base/dcumin`][@stdlib/stats/base/dcumin]: calculate the cumulative minimum of double-precision floating-point strided array elements. - [`@stdlib/stats/base/scuminabs`][@stdlib/stats/base/scuminabs]: calculate the cumulative minimum absolute value of single-precision floating-point strided array elements. @@ -322,7 +324,7 @@ int main( void ) { [@stdlib/stats/base/cuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cuminabs -[@stdlib/stats/base/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumaxabs +[@stdlib/stats/strided/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumaxabs [@stdlib/stats/base/dcumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumin diff --git a/lib/node_modules/@stdlib/stats/base/dcuminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dcuminabs/docs/repl.txt index 6017eaea486a..1a707df56f26 100644 --- a/lib/node_modules/@stdlib/stats/base/dcuminabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dcuminabs/docs/repl.txt @@ -20,13 +20,13 @@ Input array. strideX: integer - Stride Length for `x`. + Stride length for `x`. y: Float64Array Output array. strideY: integer - Stride Length for `y`. + Stride length for `y`. Returns ------- @@ -75,7 +75,7 @@ Input array. strideX: integer - Stride Length for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -84,7 +84,7 @@ Output array. strideY: integer - Stride Length for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/stats/base/dcuminabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dcuminabs/src/addon.c index a9da6026b7f6..f0f270bbdf40 100644 --- a/lib/node_modules/@stdlib/stats/base/dcuminabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dcuminabs/src/addon.c @@ -19,6 +19,7 @@ #include "stdlib/stats/base/dcuminabs.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float64array.h" #include @@ -37,7 +38,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); - stdlib_strided_dcuminabs( N, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_dcuminabs)( N, X, strideX, Y, strideY ); return NULL; } @@ -52,12 +53,12 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); - STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_dcuminabs_ndarray( N, X, strideX, offsetX, Y, strideY, offsetY ); + API_SUFFIX(stdlib_strided_dcuminabs_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); return NULL; } diff --git a/lib/node_modules/@stdlib/stats/base/dcuminabs/src/main.c b/lib/node_modules/@stdlib/stats/base/dcuminabs/src/main.c index 5dc8302c3016..884769fcb53d 100644 --- a/lib/node_modules/@stdlib/stats/base/dcuminabs/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dcuminabs/src/main.c @@ -69,7 +69,7 @@ void API_SUFFIX(stdlib_strided_dcuminabs_ndarray)( const CBLAS_INT N, const doub if ( !stdlib_base_is_nan( min ) ) { for (; i < N; i++ ) { ix += strideX; - v = fabs( X[ ix ] ); + v = stdlib_base_abs( X[ ix ] ); if ( stdlib_base_is_nan( v ) ) { min = v; break; diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.js index 6e3896602ca7..7698df291d3b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.js @@ -22,8 +22,8 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var uniform = require( '@stdlib/random/array/uniform' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniformArray = require( '@stdlib/random/array/uniform' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var cdf = require( './../lib' ); @@ -44,9 +44,9 @@ bench( pkg, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - x[ i ] = ( randu() * 20.0 ) - 10.0; - min[ i ] = ( randu() * 20.0 ) - 20.0; - max[ i ] = min[ i ] + ( randu() * 40.0 ); + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); } b.tic(); @@ -75,7 +75,7 @@ bench( pkg+':factory', function benchmark( b ) { min = -1.5; max = 1.5; mycdf = cdf.factory( min, max ); - x = uniform( 100, -2.0, 2.0 ); + x = uniformArray( 100, -2.0, 2.0 ); b.tic(); for ( i = 0; i < b.iterations; i++ ) { diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.native.js index b25c4c57877c..7e4532a721cb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/cdf/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -52,9 +52,9 @@ bench( pkg+'::native', opts, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - x[ i ] = ( randu() * 20.0 ) - 10.0; - min[ i ] = ( randu() * 20.0 ) - 20.0; - max[ i ] = min[ i ] + ( randu() * 40.0 ); + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/ctor/benchmark/benchmark.js index 7570a5702ded..e1ec6a7311ab 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/ctor/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,15 +33,22 @@ var Arcsine = require( './../lib' ); bench( pkg+'::instantiation', function benchmark( bm ) { var dist; + var len; var a; var b; var i; + len = 100; + a = new Float64Array( len ); + b = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + a[ i ] = uniform( EPS, 10.0 ); + b[ i ] = uniform( a[ i ] + EPS, a[ i ] + 10.0 + EPS ); + } + bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - a = ( randu() * 10.0 ) + EPS; - b = ( randu() * 10.0 ) + a + EPS; - dist = new Arcsine( a, b ); + dist = new Arcsine( a[ i % len ], b[ i % len ] ); if ( !( dist instanceof Arcsine ) ) { bm.fail( 'should return a distribution instance' ); } @@ -81,6 +89,7 @@ bench( pkg+'::get:a', function benchmark( bm ) { bench( pkg+'::set:a', function benchmark( bm ) { var dist; + var len; var a; var b; var y; @@ -89,12 +98,16 @@ bench( pkg+'::set:a', function benchmark( bm ) { a = 20.0; b = 120.0; dist = new Arcsine( a, b ); + len = 100; + y = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + y[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = ( 100.0*randu() ) + EPS; - dist.a = y; - if ( dist.a !== y ) { + dist.a = y[ i % len ]; + if ( dist.a !== y[ i % len ] ) { bm.fail( 'should return set value' ); } } @@ -134,6 +147,7 @@ bench( pkg+'::get:b', function benchmark( bm ) { bench( pkg+'::set:b', function benchmark( bm ) { var dist; + var len; var a; var b; var y; @@ -142,12 +156,16 @@ bench( pkg+'::set:b', function benchmark( bm ) { a = 20.0; b = 40.0; dist = new Arcsine( a, b ); + len = 100; + y = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + y[ i ] = uniform( a + EPS, a + 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - y = ( 100.0*randu() ) + a + EPS; - dist.b = y; - if ( dist.b !== y ) { + dist.b = y[ i % len ]; + if ( dist.b !== y[ i % len ] ) { bm.fail( 'should return set value' ); } } @@ -161,6 +179,8 @@ bench( pkg+'::set:b', function benchmark( bm ) { bench( pkg+':entropy', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -169,10 +189,15 @@ bench( pkg+':entropy', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.entropy; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -188,6 +213,8 @@ bench( pkg+':entropy', function benchmark( bm ) { bench( pkg+':kurtosis', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -196,10 +223,15 @@ bench( pkg+':kurtosis', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.kurtosis; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -215,6 +247,8 @@ bench( pkg+':kurtosis', function benchmark( bm ) { bench( pkg+':mean', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -223,10 +257,15 @@ bench( pkg+':mean', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.mean; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -242,6 +281,8 @@ bench( pkg+':mean', function benchmark( bm ) { bench( pkg+':median', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -250,10 +291,15 @@ bench( pkg+':median', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.median; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -269,6 +315,8 @@ bench( pkg+':median', function benchmark( bm ) { bench( pkg+':mode', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -277,10 +325,15 @@ bench( pkg+':mode', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 1.0 + EPS, 101.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + 1.0 + EPS; + dist.a = x[ i % len ]; y = dist.mode; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -296,6 +349,8 @@ bench( pkg+':mode', function benchmark( bm ) { bench( pkg+':skewness', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -304,10 +359,15 @@ bench( pkg+':skewness', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.skewness; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -323,6 +383,8 @@ bench( pkg+':skewness', function benchmark( bm ) { bench( pkg+':stdev', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -331,10 +393,15 @@ bench( pkg+':stdev', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.stdev; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -350,6 +417,8 @@ bench( pkg+':stdev', function benchmark( bm ) { bench( pkg+':variance', function benchmark( bm ) { var dist; + var len; + var x; var a; var b; var y; @@ -358,10 +427,15 @@ bench( pkg+':variance', function benchmark( bm ) { a = 20.0; b = 140.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( EPS, 100.0 + EPS ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - dist.a = ( 100.0*randu() ) + EPS; + dist.a = x[ i % len ]; y = dist.variance; if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); @@ -377,6 +451,7 @@ bench( pkg+':variance', function benchmark( bm ) { bench( pkg+':cdf', function benchmark( bm ) { var dist; + var len; var a; var b; var x; @@ -386,11 +461,15 @@ bench( pkg+':cdf', function benchmark( bm ) { a = 20.0; b = 40.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - x = randu(); - y = dist.cdf( x ); + y = dist.cdf( x[ i % len ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -405,6 +484,7 @@ bench( pkg+':cdf', function benchmark( bm ) { bench( pkg+':logpdf', function benchmark( bm ) { var dist; + var len; var a; var b; var x; @@ -414,11 +494,15 @@ bench( pkg+':logpdf', function benchmark( bm ) { a = 20.0; b = 40.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - x = randu(); - y = dist.logpdf( x ); + y = dist.logpdf( x[ i % len ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -433,6 +517,7 @@ bench( pkg+':logpdf', function benchmark( bm ) { bench( pkg+':pdf', function benchmark( bm ) { var dist; + var len; var a; var b; var x; @@ -442,11 +527,15 @@ bench( pkg+':pdf', function benchmark( bm ) { a = 20.0; b = 40.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - x = randu(); - y = dist.pdf( x ); + y = dist.pdf( x[ i % len ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } @@ -461,6 +550,7 @@ bench( pkg+':pdf', function benchmark( bm ) { bench( pkg+':quantile', function benchmark( bm ) { var dist; + var len; var a; var b; var x; @@ -470,11 +560,15 @@ bench( pkg+':quantile', function benchmark( bm ) { a = 20.0; b = 40.0; dist = new Arcsine( a, b ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } bm.tic(); for ( i = 0; i < bm.iterations; i++ ) { - x = randu(); - y = dist.quantile( x ); + y = dist.quantile( x[ i % len ] ); if ( isnan( y ) ) { bm.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/README.md index 098f5034ba16..7fc6fd3878c7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/README.md @@ -211,8 +211,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - a = random_uniform( 0, 20 ); - b = random_uniform( 0, 20 ) + a; + a = random_uniform( 0.0, 20.0 ); + b = random_uniform( 20.0, a ); y = stdlib_base_dists_arcsine_entropy( a, b ); printf( "x: %lf, a: %lf, b: %lf, h(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.js index 3cc3cabd688c..6ff89647fa04 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var entropy = require( './../lib' ); @@ -41,8 +41,8 @@ bench( pkg, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - min[ i ] = randu() * 20.0; - max[ i ] = ( randu() * 20.0 ) + min[ i ]; + min[ i ] = uniform( 0.0, 20.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 20.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.native.js index 85e0f6e0cb25..3d0052873c55 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/benchmark.native.js @@ -24,7 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; @@ -50,8 +50,8 @@ bench( pkg+'::native', opts, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - min[ i ] = randu() * 20.0; - max[ i ] = ( randu() * 20.0 ) + min[ i ]; + min[ i ] = uniform( 0.0, 20.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 20.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/c/benchmark.c index 69c3c8df0740..1be8843eee4d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { a[ i ] = random_uniform( 0.0, 20.0 ); - b[ i ] = random_uniform( 0.0, 20.0 ) + a[ i ]; + b[ i ] = random_uniform( a[ i ], 40.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/examples/c/example.c index 097c4c30458d..32d9f2487c3c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/entropy/examples/c/example.c @@ -32,8 +32,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - a = random_uniform( 0, 20 ); - b = random_uniform( 0, 20 ) + a; + a = random_uniform( 0.0, 20.0 ); + b = random_uniform( a, a+20.0 ); y = stdlib_base_dists_arcsine_entropy( a, b ); printf( "a: %lf, b: %lf, h(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/README.md index d92276ea2d09..b7cf0b6b862f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/README.md @@ -211,7 +211,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { a = random_uniform( 0.0, 20.0 ); - b = random_uniform( 0.0, 20.0 ) + a; + b = random_uniform( a, a+20.0 ); y = stdlib_base_dists_arcsine_kurtosis( a, b ); printf( "a: %lf, b: %lf, Kurt(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.js index 83c785aa5d25..b4566635424e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var kurtosis = require( './../lib' ); @@ -41,8 +41,8 @@ bench( pkg, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - min[ i ] = randu() * 20.0; - max[ i ] = ( randu() * 20.0 ) + min[ i ]; + min[ i ] = uniform( 0.0, 20.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 20.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.native.js index 194d36a24129..4b3d986776c3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/benchmark.native.js @@ -24,7 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; @@ -50,8 +50,8 @@ bench( pkg+'::native', opts, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - min[ i ] = randu() * 20.0; - max[ i ] = ( randu() * 20.0 ) + min[ i ]; + min[ i ] = uniform( 0.0, 20.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 20.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/c/benchmark.c index 64abbaa56e7b..9a2295450e8f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { min[ i ] = random_uniform( 0.0, 20.0 ); - max[ i ] = random_uniform( 0.0, 20.0 ) + min[ i ]; + max[ i ] = random_uniform( min[ i ], min[ i ]+20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/examples/c/example.c index 95ec09f5991a..77a64b9096b1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/kurtosis/examples/c/example.c @@ -33,7 +33,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { a = random_uniform( 0.0, 20.0 ); - b = random_uniform( 0.0, 20.0 ) + a; + b = random_uniform( a, a+20.0 ); y = stdlib_base_dists_arcsine_kurtosis( a, b ); printf( "a: %lf, b: %lf, Kurt(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js index f8b8531dc0e9..ae59fb57b333 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var logcdf = require( './../lib' ); @@ -32,16 +33,24 @@ var logcdf = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 20.0 ) - 10.0; - min = ( randu() * 20.0 ) - 20.0; - max = min + ( randu() * 40.0 ); - y = logcdf( x, min, max ); + y = logcdf( x[ i % len ], min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -58,6 +67,7 @@ bench( pkg+':factory', function benchmark( b ) { var mylogcdf; var min; var max; + var len; var x; var y; var i; @@ -65,11 +75,15 @@ bench( pkg+':factory', function benchmark( b ) { min = -1.5; max = 1.5; mylogcdf = logcdf.factory( min, max ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -2.0, 0.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) - 2.0; - y = mylogcdf( x ); + y = mylogcdf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.js index 949dce94fed0..77dceabd73fb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var logpdf = require( './../lib' ); @@ -32,16 +33,24 @@ var logpdf = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 20.0 ) - 10.0; - min = ( randu() * 20.0 ) - 20.0; - max = min + ( randu() * 40.0 ); - y = logpdf( x, min, max ); + y = logpdf( x[ i % len ], min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -58,6 +67,7 @@ bench( pkg+':factory', function benchmark( b ) { var mylogpdf; var min; var max; + var len; var x; var y; var i; @@ -65,11 +75,15 @@ bench( pkg+':factory', function benchmark( b ) { min = -1.5; max = 1.5; mylogpdf = logpdf.factory( min, max ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -2.0, 0.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) - 2.0; - y = mylogpdf( x ); + y = mylogpdf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.native.js index 30ca6ca83112..53c1f36a7b19 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/logpdf/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -52,9 +52,9 @@ bench( pkg+'::native', opts, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - x[ i ] = ( randu() * 20.0 ) - 10.0; - min[ i ] = ( randu() * 20.0 ) - 20.0; - max[ i ] = min[ i ] + ( randu() * 40.0 ); + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mean/benchmark/benchmark.js index 4b5fbad67902..a0e74ae28201 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mean/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var mean = require( './../lib' ); @@ -32,14 +33,21 @@ var mean = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = ( randu()*10.0 ); - max = ( randu()*10.0 ) + min; - y = mean( min, max ); + y = mean( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/median/benchmark/benchmark.js index fe0c91f29a36..f30b14fd4fe2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/median/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var median = require( './../lib' ); @@ -32,14 +33,21 @@ var median = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = ( randu()*10.0 ); - max = ( randu()*10.0 ) + min; - y = median( min, max ); + y = median( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md index a91f37f5b608..20d4b13c6e66 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md @@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/dists/arcsine/mode.h" +``` + +#### stdlib_base_dists_arcsine_mode( a, b ) + +Returns the [mode][mode] of an [arcsine][arcsine-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_arcsine_mode( 4.0, 12.0 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **a**: `[in] double` minimum support. +- **b**: `[in] double` maximum support. + +```c +double stdlib_base_dists_arcsine_mode( const double a, const double b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/arcsine/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double a; + double b; + double m; + int i; + + for ( i = 0; i < 10; i++ ) { + a = random_uniform( -20.0, 0.0 ); + b = random_uniform( a, a + 40.0 ); + m = stdlib_base_dists_arcsine_mode( a, b ); + printf( "a: %lf, b: %lf, mode(X;a,b): %lf\n", a, b, m ); + } +} +``` + +
+ + + +
+ + + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.js index 8a3d5a7733d1..842b91150aee 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var mode = require( './../lib' ); @@ -32,14 +33,21 @@ var mode = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = ( randu()*10.0 ); - max = ( randu()*10.0 ) + min; - y = mode( min, max ); + y = mode( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e5e87787542e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var min; + var max; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..652c44cb6718 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/benchmark/c/benchmark.c @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/arcsine/mode.h" +#include +#include +#include +#include +#include + +#define NAME "arcsine-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double a[ 100 ]; + double b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = random_uniform( -20.0, 0.0 ); + b[ i ] = random_uniform( a[ i ], a[ i ] + 40.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_arcsine_mode( a[ i % 100 ], b[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/examples/c/example.c new file mode 100644 index 000000000000..6231db3a02cf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/arcsine/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double a; + double b; + double m; + int i; + + for ( i = 0; i < 10; i++ ) { + a = random_uniform( -20.0, 0.0 ); + b = random_uniform( a, a + 40.0 ); + m = stdlib_base_dists_arcsine_mode( a, b ); + printf( "a: %lf, b: %lf, mode(X;a,b): %lf\n", a, b, m ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= b ) { + return 0.0 / 0.0; // NaN + } + return a; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/test/test.native.js new file mode 100644 index 000000000000..e08d8d7506c2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/test/test.native.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mode, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v = mode( NaN, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = mode( 10.0, NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `a >= b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = mode( 3.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mode( 2.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mode( NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mode( PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the mode of an arcsine distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = mode( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.js index d7c0efeb2f9d..c558df0912c1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var pdf = require( './../lib' ); @@ -32,16 +33,24 @@ var pdf = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 20.0 ) - 10.0; - min = ( randu() * 20.0 ) - 20.0; - max = min + ( randu() * 40.0 ); - y = pdf( x, min, max ); + y = pdf( x[ i % len ], min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -58,6 +67,7 @@ bench( pkg+':factory', function benchmark( b ) { var mypdf; var min; var max; + var len; var x; var y; var i; @@ -65,11 +75,15 @@ bench( pkg+':factory', function benchmark( b ) { min = -1.5; max = 1.5; mypdf = pdf.factory( min, max ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -2.0, 0.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) - 2.0; - y = mypdf( x ); + y = mypdf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.native.js index 2bd2df14d18f..b8b4b3ff3152 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/pdf/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -52,9 +52,9 @@ bench( pkg+'::native', opts, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - x[ i ] = ( randu() * 20.0 ) - 10.0; - min[ i ] = ( randu() * 20.0 ) - 20.0; - max[ i ] = min[ i ] + ( randu() * 40.0 ); + x[ i ] = uniform( -10.0, 10.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/benchmark/benchmark.js index b88f69fd2e63..04bbc05c00c2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var quantile = require( './../lib' ); @@ -32,16 +33,24 @@ var quantile = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + min[ i ] = uniform( -20.0, 0.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 40.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - min = ( randu() * 20.0 ) - 20.0; - max = min + ( randu() * 40.0 ); - y = quantile( p, min, max ); + y = quantile( p[ i % len ], min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -58,6 +67,7 @@ bench( pkg+':factory', function benchmark( b ) { var myquantile; var min; var max; + var len; var p; var y; var i; @@ -65,11 +75,15 @@ bench( pkg+':factory', function benchmark( b ) { min = -1.5; max = 1.5; myquantile = quantile.factory( min, max ); + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - y = myquantile( p ); + y = myquantile( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md index 2fea75c2beb1..364e16362e2f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md @@ -131,6 +131,101 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/arcsine/skewness.h" +``` + +#### stdlib_base_dists_arcsine_skewness( a, b ) + +Returns the [skewness][skewness] of an [arcsine][arcsine-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_arcsine_skewness( 4.0, 12.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **a**: `[in] double` minimum support. +- **b**: `[in] double` maximum support. + +```c +double stdlib_base_dists_arcsine_skewness( const double a, const double b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/arcsine/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double a; + double b; + double s; + int i; + + for ( i = 0; i < 10; i++ ) { + a = random_uniform( -20.0, 0.0 ); + b = random_uniform( a, a + 40.0 ); + s = stdlib_base_dists_arcsine_skewness( a, b ); + printf( "a: %lf, b: %lf, skew(X;a,b): %lf\n", a, b, s ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.js index 58aef356eebe..5bad52f28691 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var skewness = require( './../lib' ); @@ -32,14 +33,21 @@ var skewness = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = ( randu()*10.0 ); - max = ( randu()*10.0 ) + min; - y = skewness( min, max ); + y = skewness( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..144d0f0bf25e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var min; + var max; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..2b6eef8c0cf7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/arcsine/skewness.h" +#include +#include +#include +#include + +#define NAME "arcsine-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v* ( max - min ) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double a[ 100 ]; + double b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = random_uniform( -20.0, 0.0 ); + b[ i ] = random_uniform( a[ i ], a[ i ] + 40.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_arcsine_skewness( a[ i % 100 ], b[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/examples/c/example.c new file mode 100644 index 000000000000..41e2ee8395de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/arcsine/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double a; + double b; + double s; + int i; + + for ( i = 0; i < 10; i++ ) { + a = random_uniform( -20.0, 0.0 ); + b = random_uniform( a, a + 40.0 ); + s = stdlib_base_dists_arcsine_skewness( a, b ); + printf( "a: %lf, b: %lf, skew(X;a,b): %lf\n", a, b, s ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= b ) { + return 0.0 / 0.0; // NaN + } + return 0.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/test/test.native.js new file mode 100644 index 000000000000..6c188bb2ed4c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/test/test.native.js @@ -0,0 +1,89 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var randu = require( '@stdlib/random/base/randu' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof skewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v = skewness( NaN, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = skewness( 10.0, NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `a >= b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = skewness( 3.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = skewness( 2.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = skewness( NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = skewness( PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns `0.0` as the skewness of an arcsine distribution ', opts, function test( t ) { + var a; + var b; + var i; + var v; + + for ( i = 0; i < 10; i++ ) { + a = ( randu()*10.0 ); + b = ( randu()*10.0 ) + a; + v = skewness( a, b ); + t.equal( v, 0.0, 'returns 0.0' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/README.md index 8fa83b0c8201..66dae41d9a83 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/README.md @@ -131,6 +131,101 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/arcsine/stdev.h" +``` + +#### stdlib_base_dists_arcsine_stdev( a, b ) + +Returns the [standard deviation][stdev] of an [arcsine][arcsine-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_arcsine_stdev( 4.0, 12.0 ); +// returns ~2.828 +``` + +The function accepts the following arguments: + +- **a**: `[in] double` minimum support. +- **b**: `[in] double` maximum support. + +```c +double stdlib_base_dists_arcsine_stdev( const double a, const double b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/arcsine/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double a; + double b; + double s; + int i; + + for ( i = 0; i < 10; i++ ) { + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a, a + 10.0 ); + s = stdlib_base_dists_arcsine_stdev( a, b ); + printf( "a: %lf, b: %lf, SD(X;a,b): %lf\n", a, b, s ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.js index 595f68a56f57..ad52e8c50044 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var stdev = require( './../lib' ); @@ -32,14 +33,21 @@ var stdev = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = ( randu()*10.0 ); - max = ( randu()*10.0 ) + min; - y = stdev( min, max ); + y = stdev( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..84a8af3bb340 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var min; + var max; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..d86eb678a6f0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/arcsine/stdev.h" +#include +#include +#include +#include + +#define NAME "arcsine-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double a[ 100 ]; + double b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = random_uniform( -20.0, 0.0 ); + b[ i ] = random_uniform( a[ i ], a[ i ] + 40.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_arcsine_stdev( a[ i % 100 ], b[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/examples/c/example.c new file mode 100644 index 000000000000..16fe8fe0e107 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/arcsine/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double a; + double b; + double s; + int i; + + for ( i = 0; i < 10; i++ ) { + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a, a + 10.0 ); + s = stdlib_base_dists_arcsine_stdev( a, b ); + printf( "a: %lf, b: %lf, SD(X;a,b): %lf\n", a, b, s ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= b ) { + return 0.0 / 0.0; // NaN + } + return SQRT1OVER8 * ( b - a ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/test/test.native.js new file mode 100644 index 000000000000..d4571519c9fb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/stdev/test/test.native.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof stdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v = stdev( NaN, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = stdev( 10.0, NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `a >= b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = stdev( 3.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = stdev( 2.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = stdev( NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = stdev( PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the standard deviation of an arcsine distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = stdev( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/README.md index 83b7566f1cf3..706f1b28833a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/README.md @@ -211,7 +211,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { a = random_uniform( 0.0, 10.0 ); - b = random_uniform( 0.0, 10.0 ) + a; + b = random_uniform( a, a+10.0 ); y = stdlib_base_dists_arcsine_variance( a, b ); printf( "a: %lf, b: %lf, Var(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.js index a822b9084a07..bee3bb83b132 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var variance = require( './../lib' ); @@ -41,8 +41,8 @@ bench( pkg, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - min[ i ] = ( randu() * 10.0 ); - max[ i ] = ( randu() * 10.0 ) + min[ i ]; + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.native.js index d427c38060a3..ea895ca8e9fa 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/benchmark.native.js @@ -24,7 +24,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var tryRequire = require( '@stdlib/utils/try-require' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; @@ -50,8 +50,8 @@ bench( pkg+'::native', opts, function benchmark( b ) { min = new Float64Array( len ); max = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - min[ i ] = ( randu() * 10.0 ); - max[ i ] = ( randu() * 10.0 ) + min[ i ]; + min[ i ] = uniform( 0.0, 10.0 ); + max[ i ] = uniform( min[ i ], min[ i ] + 10.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/c/benchmark.c index f32d9a273b29..7feb1a071c71 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { min[ i ] = random_uniform( 0.0, 10.0 ); - max[ i ] = random_uniform( 0.0, 10.0 ) + min[ i ]; + max[ i ] = random_uniform( min[ i ], min[ i ] + 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/examples/c/example.c index 607e8e4c95ac..81058cd1cd2c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/variance/examples/c/example.c @@ -33,7 +33,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { a = random_uniform( 0.0, 10.0 ); - b = random_uniform( 0.0, 10.0 ) + a; + b = random_uniform( a, a+10.0 ); y = stdlib_base_dists_arcsine_variance( a, b ); printf( "a: %lf, b: %lf, Var(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/cdf/benchmark/benchmark.js index a8e6ab48ee60..a19bc1f5be82 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/cdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/cdf/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var cdf = require( './../lib' ); @@ -30,16 +31,23 @@ var cdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var x; var y; var i; + len = 100; + p = new Float64Array( len ); + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -1.0, 2.0 ); + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*3.0 ) - 1.0; - p = randu(); - y = cdf( x, p ); + y = cdf( x[ i % len ], p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -54,6 +62,7 @@ bench( pkg, function benchmark( b ) { bench( pkg+':factory', function benchmark( b ) { var mycdf; + var len; var p; var x; var y; @@ -61,11 +70,15 @@ bench( pkg+':factory', function benchmark( b ) { p = 0.3; mycdf = cdf.factory( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -1.0, 2.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*3.0 ) - 1.0; - y = mycdf( x ); + y = mycdf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/ctor/benchmark/benchmark.js index ccc73d6e7059..a316f0e6ab81 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/ctor/benchmark/benchmark.js @@ -21,8 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var ln = require( '@stdlib/math/base/special/ln' ); var pkg = require( './../package.json' ).name; @@ -33,13 +34,19 @@ var Bernoulli = require( './../lib' ); bench( pkg+'::instantiation', function benchmark( b ) { var dist; + var len; var p; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - dist = new Bernoulli( p ); + dist = new Bernoulli( p[ i % len ] ); if ( !( dist instanceof Bernoulli ) ) { b.fail( 'should return a distribution instance' ); } @@ -78,18 +85,23 @@ bench( pkg+'::get:p', function benchmark( b ) { bench( pkg+'::set:p', function benchmark( b ) { var dist; + var len; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + y = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + y[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - y = randu(); - dist.p = y; - if ( dist.p !== y ) { + dist.p = y[ i % len ]; + if ( dist.p !== y[ i % len ] ) { b.fail( 'should return set value' ); } } @@ -103,16 +115,23 @@ bench( pkg+'::set:p', function benchmark( b ) { bench( pkg+':entropy', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.entropy; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -128,16 +147,23 @@ bench( pkg+':entropy', function benchmark( b ) { bench( pkg+':kurtosis', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.kurtosis; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -153,16 +179,23 @@ bench( pkg+':kurtosis', function benchmark( b ) { bench( pkg+':mean', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.mean; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -178,16 +211,23 @@ bench( pkg+':mean', function benchmark( b ) { bench( pkg+':median', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.median; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -203,16 +243,23 @@ bench( pkg+':median', function benchmark( b ) { bench( pkg+':skewness', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.skewness; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -228,16 +275,23 @@ bench( pkg+':skewness', function benchmark( b ) { bench( pkg+':stdev', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.stdev; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -253,16 +307,23 @@ bench( pkg+':stdev', function benchmark( b ) { bench( pkg+':variance', function benchmark( b ) { var dist; + var len; + var x; var p; var y; var i; p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - dist.p = randu(); + dist.p = x[ i % len ]; y = dist.variance; if ( isnan( y ) ) { b.fail( 'should not return NaN' ); @@ -278,6 +339,7 @@ bench( pkg+':variance', function benchmark( b ) { bench( pkg+':cdf', function benchmark( b ) { var dist; + var len; var p; var x; var y; @@ -285,11 +347,15 @@ bench( pkg+':cdf', function benchmark( b ) { p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 6.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = randu() * 6.0; - y = dist.cdf( x ); + y = dist.cdf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -304,6 +370,7 @@ bench( pkg+':cdf', function benchmark( b ) { bench( pkg+':mgf', function benchmark( b ) { var dist; + var len; var p; var x; var y; @@ -311,11 +378,15 @@ bench( pkg+':mgf', function benchmark( b ) { p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, -ln( 1.0-p ) ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = randu() * ( -ln( 1.0-p ) ); - y = dist.mgf( x ); + y = dist.mgf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -330,6 +401,7 @@ bench( pkg+':mgf', function benchmark( b ) { bench( pkg+':pmf', function benchmark( b ) { var dist; + var len; var p; var x; var y; @@ -337,11 +409,15 @@ bench( pkg+':pmf', function benchmark( b ) { p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = discreteUniform( 0, 8 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = round( randu() * 8.0 ); - y = dist.pmf( x ); + y = dist.pmf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -356,6 +432,7 @@ bench( pkg+':pmf', function benchmark( b ) { bench( pkg+':quantile', function benchmark( b ) { var dist; + var len; var p; var x; var y; @@ -363,11 +440,15 @@ bench( pkg+':quantile', function benchmark( b ) { p = 0.54; dist = new Bernoulli( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = randu(); - y = dist.quantile( x ); + y = dist.quantile( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/README.md index 74def01cf3a5..d9dd2457df50 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/README.md @@ -167,7 +167,7 @@ double out = stdlib_base_dists_bernoulli_entropy( 0.1 ); The function accepts the following arguments: -- **p**: `[in] double` success probability +- **p**: `[in] double` success probability. ```c double stdlib_base_dists_bernoulli_entropy( const double p ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.js index 9298ac5cb302..509f5ea88732 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var entropy = require( './../lib' ); @@ -39,7 +39,7 @@ bench( pkg, function benchmark( b ) { len = 100; p = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - p[ i ] = randu(); + p[ i ] = uniform( 0.0, 1.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.native.js index 9adda9e4fda2..169c6b203cae 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/benchmark/benchmark.native.js @@ -39,7 +39,7 @@ var opts = { // MAIN // -bench( pkg, opts, function benchmark( b ) { +bench( pkg+'::native', opts, function benchmark( b ) { var len; var p; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/examples/c/example.c index 7edb0e66fc02..217169924d6c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/examples/c/example.c @@ -28,6 +28,6 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { p = (double)rand() / ( (double)RAND_MAX + 1.0 ); y = stdlib_base_dists_bernoulli_entropy( p ); - printf( "x: %lf , H(X;p): %lf\n", p, y ); + printf( "x: %lf, H(X;p): %lf\n", p, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/lib/native.js index 9a01e2d518c6..576a280bbb01 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/lib/native.js @@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' ); /** * Returns the entropy of a Bernoulli distribution. * +* @private * @param {Probability} p - success probability * @returns {PositiveNumber} entropy * diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/manifest.json index 76cbed47f8cc..de112674bc8a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/entropy/manifest.json @@ -1,79 +1,79 @@ { - "options": { + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { "task": "build", - "wasm": false + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/unary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/ln" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/ln" + ] }, - "fields": [ - { - "field": "src", - "resolve": true, - "relative": true - }, - { - "field": "include", - "resolve": true, - "relative": true - }, - { - "field": "libraries", - "resolve": false, - "relative": false - }, - { - "field": "libpath", - "resolve": true, - "relative": false - } - ], - "confs": [ - { - "task": "build", - "wasm": false, - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/ln" - ] - }, - { - "task": "benchmark", - "wasm": false, - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/ln" - ] - }, - { - "task": "examples", - "wasm": false, - "src": [ - "./src/main.c" - ], - "include": [ - "./include" - ], - "libraries": [], - "libpath": [], - "dependencies": [ - "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/ln" - ] - } - ] - } \ No newline at end of file + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/ln" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/benchmark/benchmark.js index c53005a17531..afbb7e7ec478 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var kurtosis = require( './../lib' ); @@ -30,14 +31,20 @@ var kurtosis = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - y = kurtosis( p ); + y = kurtosis( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/lib/main.js index e57d8bbbb2b4..98f6b4162494 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/kurtosis/lib/main.js @@ -29,7 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); * Returns the excess kurtosis of a Bernoulli distribution. * * @param {Probability} p - success probability -* @returns {PositiveNumber} kurtosis +* @returns {PositiveNumber} excess kurtosis * * @example * var v = kurtosis( 0.1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.js index 3f21a07a88e4..c3660d5ddfda 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -40,7 +40,7 @@ bench( pkg, function benchmark( b ) { len = 100; p = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - p[ i ] = ( randu()*1.0 ) + EPS; + p[ i ] = uniform( EPS, 1.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.native.js index bc1fb7c2475a..8343e06bbeba 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mean/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var EPS = require( '@stdlib/constants/float64/eps' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -49,7 +49,7 @@ bench( pkg+'::native', opts, function benchmark( b ) { len = 100; p = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - p[ i ] = ( randu()*1.0 ) + EPS; + p[ i ] = uniform( EPS, 1.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/median/benchmark/benchmark.js index 504b50bea9b5..d2477293053c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/median/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var median = require( './../lib' ); @@ -30,14 +31,20 @@ var median = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - y = median( p ); + y = median( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mgf/benchmark/benchmark.js index 01dbb093cdad..2abe4e684614 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mgf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mgf/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var mgf = require( './../lib' ); @@ -30,16 +31,23 @@ var mgf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var t; var y; var i; + len = 100; + p = new Float64Array( len ); + t = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + t[ i ] = uniform( 0.0, 3.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - t = randu() * 3.0; - y = mgf( t, p ); + y = mgf( t[ i % len ], p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -54,6 +62,7 @@ bench( pkg, function benchmark( b ) { bench( pkg+':factory', function benchmark( b ) { var mymgf; + var len; var p; var t; var y; @@ -61,11 +70,15 @@ bench( pkg+':factory', function benchmark( b ) { p = 0.3; mymgf = mgf.factory( p ); + len = 100; + t = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = uniform( 0.0, 3.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - t = randu() * 3.0; - y = mymgf( t ); + y = mymgf( t[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.js index c9593b5244c1..2bffbc9405e6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var mode = require( './../lib' ); @@ -39,12 +39,12 @@ bench( pkg, function benchmark( b ) { len = 100; p = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - p[ i ] = randu(); + p[ i ] = uniform( 0.0, 1.0 ); } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - y = mode( p[ i%len ] ); + y = mode( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.native.js index 9f05adb6c77a..7080b2c2811a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/mode/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -48,7 +48,7 @@ bench( pkg+'::native', opts, function benchmark( b ) { len = 100; p = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - p[ i ] = randu(); + p[ i ] = uniform( 0.0, 1.0 ); } b.tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.js index 6a067aebb893..5a1ae4b5e3dd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/pmf/benchmark/benchmark.js @@ -21,8 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var pmf = require( './../lib' ); @@ -31,16 +32,23 @@ var pmf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = discreteUniform( 0, 3 ); + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = round( randu()*3.0 ); - p = randu(); - y = pmf( x, p ); + y = pmf( x[ i % len ], p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -55,6 +63,7 @@ bench( pkg, function benchmark( b ) { bench( pkg+':factory', function benchmark( b ) { var mypmf; + var len; var p; var x; var y; @@ -62,11 +71,15 @@ bench( pkg+':factory', function benchmark( b ) { p = 0.3; mypmf = pmf.factory( p ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = discreteUniform( 0, 3 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = randu() * 3.0; - y = mypmf( x ); + y = mypmf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/quantile/benchmark/benchmark.js index afdccc79cc91..73717f76bdfd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/quantile/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/quantile/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var quantile = require( './../lib' ); @@ -30,16 +31,23 @@ var quantile = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var r; var y; var i; + len = 100; + r = new Float64Array( len ); + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + r[ i ] = uniform( 0.0, 1.0 ); + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - r = randu(); - p = randu(); - y = quantile( r, p ); + y = quantile( r[ i % len ], p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -54,6 +62,7 @@ bench( pkg, function benchmark( b ) { bench( pkg+':factory', function benchmark( b ) { var myquantile; + var len; var p; var r; var y; @@ -61,11 +70,15 @@ bench( pkg+':factory', function benchmark( b ) { p = 0.3; myquantile = quantile.factory( p ); + len = 100; + r = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + r[ i ] = uniform( 0.0, 1.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - r = randu(); - y = myquantile( r ); + y = myquantile( r[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/skewness/benchmark/benchmark.js index e9cf3043fd80..edada70ad347 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/skewness/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var skewness = require( './../lib' ); @@ -30,14 +31,20 @@ var skewness = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - y = skewness( p ); + y = skewness( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/benchmark/benchmark.js index 5bf35c5265ec..b3d395bab1c2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/stdev/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var Float64Array = require( '@stdlib/array/float64' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var stdev = require( './../lib' ); @@ -39,7 +39,7 @@ bench( pkg, function benchmark( b ) { len = 100; p = new Float64Array( len ); for ( i = 0; i < len; i++ ) { - p[ i ] = randu(); + p[ i ] = uniform( 0.0, 1.0 ); } b.tic(); for ( i = 0; i < b.iterations; i++ ) { diff --git a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/variance/benchmark/benchmark.js index 06540cf44d99..d995fd0aaa03 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bernoulli/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bernoulli/variance/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var variance = require( './../lib' ); @@ -30,14 +31,20 @@ var variance = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = uniform( 0.0, 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = randu(); - y = variance( p ); + y = variance( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/README.md index ea03ac0bfaa1..0db0320bdcef 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/README.md @@ -185,7 +185,7 @@ The function accepts the following arguments: - **beta**: `[in] double` second shape parameter. ```c -double stdlib_base_dists_beta_mean( const double a, const double b ); +double stdlib_base_dists_beta_mean( const double alpha, const double beta ); ```
@@ -222,7 +222,7 @@ int main( void ) { double beta; double y; int i; - + for ( i = 0; i < 25; i++ ) { alpha = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/benchmark/c/benchmark.c index e3edbbc4c3a1..b897091c5782 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - alpha[ i ] = random_uniform( -20.0, 0.0 ); - beta[ i ] = random_uniform( alpha[ i ], alpha[ i ]+40.0 ); + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/examples/c/example.c index 909e188999a6..7e8975167622 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_mean( alpha, beta ); printf( "alpha: %lf, beta: %lf, E(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.js index 24f2f4625c0f..bdd0befe7b0b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.js @@ -112,7 +112,7 @@ tape( 'the function returns the mean of a beta distribution', function test( t ) t.equal( y, expected[i], 'alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { delta = abs( y - expected[ i ] ); - tol = 15.0 * EPS * abs( expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); t.ok( delta <= tol, 'within tolerance. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.native.js index 77f0e8be87bd..57625311b7c0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/test/test.native.js @@ -121,7 +121,7 @@ tape( 'the function returns the mean of a beta distribution', opts, function tes t.equal( y, expected[i], 'alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { delta = abs( y - expected[ i ] ); - tol = 15.0 * EPS * abs( expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); t.ok( delta <= tol, 'within tolerance. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/README.md index 8237c0d26668..19105307ba46 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/README.md @@ -124,7 +124,6 @@ v = mode( 1.0, -1.0 ); ```javascript var randu = require( '@stdlib/random/base/randu' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var mode = require( '@stdlib/stats/base/dists/beta/mode' ); var alpha; @@ -133,8 +132,8 @@ var v; var i; for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*10.0 ) + 1.0 + EPS; - beta = ( randu()*10.0 ) + 1.0 + EPS; + alpha = ( randu()*10.0 ) + 1.0; + beta = ( randu()*10.0 ) + 1.0; v = mode( alpha, beta ); console.log( 'α: %d, β: %d, mode(X;α,β): %d', alpha.toFixed( 4 ), beta.toFixed( 4 ), v.toFixed( 4 ) ); } @@ -208,7 +207,6 @@ double stdlib_base_dists_beta_mode( const double alpha, const double beta ); ```c #include "stdlib/stats/base/dists/beta/mode.h" -#include "stdlib/constants/float64/eps.h" #include #include @@ -223,8 +221,8 @@ int main( void ) { double y; int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( 1.0, 11.0 ); + beta = random_uniform( 1.0, 11.0 ); y = stdlib_base_dists_beta_mode( alpha, beta ); printf( "alpha: %lf, beta: %lf, mode(X;alpha,beta): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/benchmark/c/benchmark.c index 596b62f117a9..64f955b20f67 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/benchmark/c/benchmark.c @@ -17,7 +17,6 @@ */ #include "stdlib/stats/base/dists/beta/mode.h" -#include "stdlib/constants/float64/eps.h" #include #include #include @@ -101,8 +100,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - alpha[ i ] = random_uniform( 0.0, 10.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; - beta[ i ] = random_uniform( 0.0, 10.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; + alpha[ i ] = random_uniform( 1.0, 11.0 ); + beta[ i ] = random_uniform( 1.0, 11.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/c/example.c index bdc2edcf7dd0..69fedd9681dc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/c/example.c @@ -17,7 +17,6 @@ */ #include "stdlib/stats/base/dists/beta/mode.h" -#include "stdlib/constants/float64/eps.h" #include #include @@ -33,8 +32,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( 1.0, 11.0 ); + beta = random_uniform( 1.0, 11.0 ); y = stdlib_base_dists_beta_mode( alpha, beta ); printf( "alpha: %lf, beta: %lf, mode(X;alpha,beta): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/index.js index 7cef404be3b3..3bd49be780b5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/examples/index.js @@ -19,7 +19,6 @@ 'use strict'; var randu = require( '@stdlib/random/base/randu' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var mode = require( './../lib' ); var alpha; @@ -28,8 +27,8 @@ var v; var i; for ( i = 0; i < 10; i++ ) { - alpha = ( randu()*10.0 ) + 1.0 + EPS; - beta = ( randu()*10.0 ) + 1.0 + EPS; + alpha = ( randu()*10.0 ) + 1.0; + beta = ( randu()*10.0 ) + 1.0; v = mode( alpha, beta ); console.log( 'α: %d, β: %d, mode(X;α,β): %d', alpha.toFixed( 4 ), beta.toFixed( 4 ), v.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/manifest.json index 6dffb0b312d7..7fe023978775 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/manifest.json @@ -53,9 +53,7 @@ ], "libraries": [], "libpath": [], - "dependencies": [ - "@stdlib/constants/float64/eps" - ] + "dependencies": [] }, { "task": "examples", @@ -68,9 +66,7 @@ ], "libraries": [], "libpath": [], - "dependencies": [ - "@stdlib/constants/float64/eps" - ] + "dependencies": [] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/README.md index cb0fb898cda2..6f86669b2f16 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_skewness( alpha, beta ); printf( "α: %lf, β: %lf, skew(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/benchmark/c/benchmark.c index 02f12224a5a9..4f62eadab4f3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - alpha[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/examples/c/example.c index 770032a9b5d1..aabe4c58f3e5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_skewness( alpha, beta ); printf( "α: %lf, β: %lf, skew(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/README.md index 5c9d114811c8..534e9bf16e77 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_stdev( alpha, beta ); printf( "alpha: %lf, beta: %lf, F(X;a,b): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/benchmark/c/benchmark.c index 06d783ff7429..0ce618c3655b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - alpha[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/examples/c/example.c index a468a307f65c..a4ec222e7b5d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_stdev( alpha, beta ); printf( "alpha: %lf, beta: %lf, F(X;alpha,beta): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/README.md index 0cc77f663ed6..d20b94af7969 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/README.md @@ -223,8 +223,8 @@ int main( void ) { double y; int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_variance( alpha, beta ); printf( "α: %lf, β: %lf, Var(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/benchmark/c/benchmark.c index 04e002221e7c..7e05d282cb83 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - alpha[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/examples/c/example.c index f58464e38525..2c37d17a7966 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - beta = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_beta_variance( alpha, beta ); printf( "α: %lf, β: %lf, Var(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/README.md index 3fd20aa7dc22..11251bc0fe49 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/README.md @@ -226,8 +226,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - a = random_uniform( 0, 20 ); - b = random_uniform( 0, 20 ) + 4.0; + a = random_uniform( 0.0, 20.0 ); + b = random_uniform( 4.0, 24.0 ); y = stdlib_base_dists_betaprime_kurtosis( a, b ); printf( "α: %lf, β: %lf, Kurt(X;α,β): %lf", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/benchmark/c/benchmark.c index 1970129c92cd..6e88c04e3374 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { alpha[ i ] = random_uniform( 0.0, 20.0 ); - beta[ i ] = random_uniform( 0.0, 20.0 ) + 4.0; + beta[ i ] = random_uniform( 4.0, 24.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/examples/c/example.c index e36363aaf35d..cfec2d70d0bc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/examples/c/example.c @@ -32,8 +32,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0, 20 ); - beta = random_uniform( 0, 20 ) + 4.0; + alpha = random_uniform( 0.0, 20.0 ); + beta = random_uniform( 4.0, 24.0 ); y = stdlib_base_dists_betaprime_kurtosis( alpha, beta ); printf( "α: %lf, β: %lf, Kurt(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/main.js index d4cd33b4811f..0ba33e6f75b3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/main.js @@ -30,7 +30,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); * * @param {PositiveNumber} alpha - first shape parameter * @param {PositiveNumber} beta - second shape parameter -* @returns {number} kurtosis +* @returns {number} excess kurtosis * * @example * var v = kurtosis( 2.0, 6.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/native.js index 354c44abb481..f86f35701da8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/kurtosis/lib/native.js @@ -31,7 +31,7 @@ var addon = require( './../src/addon.node' ); * @private * @param {PositiveNumber} alpha - first shape parameter * @param {PositiveNumber} beta - second shape parameter -* @returns {number} kurtosis +* @returns {number} excess kurtosis * * @example * var v = kurtosis( 2.0, 6.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/README.md index 4813e7abb813..052fe87e58ac 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/README.md @@ -226,8 +226,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0, 20 ); - beta = random_uniform( 0, 20 ) + 3.0; + alpha = random_uniform( 0.0, 20.0 ); + beta = random_uniform( 3.0, 23.0 ); y = stdlib_base_dists_betaprime_skewness( alpha, beta ); printf( "α: %lf, β: %lf, skew(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/benchmark/c/benchmark.c index 6bc9883d3368..8669b929a76e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { alpha[ i ] = random_uniform( 0.0, 20.0 ); - beta[ i ] = random_uniform( 0.0, 20.0 ) + 3.0; + beta[ i ] = random_uniform( 3.0, 23.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/examples/c/example.c index 0fe281e78e22..fd7fb8dafc42 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/skewness/examples/c/example.c @@ -32,8 +32,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0, 20 ); - beta = random_uniform( 0, 20 ) + 3.0; + alpha = random_uniform( 0.0, 20.0 ); + beta = random_uniform( 3.0, 23.0 ); y = stdlib_base_dists_betaprime_skewness( alpha, beta ); printf( "α: %lf, β: %lf, skew(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/README.md index 2f2076e535d9..365f83a5cb12 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/README.md @@ -227,7 +227,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { alpha = random_uniform( 0.0, 20.0 ); - beta = random_uniform( 0.0, 20.0 ) + 2.0; + beta = random_uniform( 2.0, 22.0 ); y = stdlib_base_dists_betaprime_stdev( alpha, beta ); printf( "α: %lf, β: %lf, SD(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/benchmark/c/benchmark.c index a2c76ca232d2..73ceef40ab1d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { alpha[ i ] = random_uniform( 0.0, 20.0 ); - beta[ i ] = random_uniform( 0.0, 20.0 ) + 2.0; + beta[ i ] = random_uniform( 2.0, 22.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/examples/c/example.c index ce37e56223a3..f4b329b58734 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/stdev/examples/c/example.c @@ -32,8 +32,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0, 20 ); - beta = random_uniform( 0, 20 ) + 2.0; + alpha = random_uniform( 0.0, 20.0 ); + beta = random_uniform( 2.0, 22.0 ); y = stdlib_base_dists_betaprime_stdev( alpha, beta ); printf( "α: %lf, β: %lf, SD(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/README.md index e8c299063aaf..bb826be883f3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/README.md @@ -226,8 +226,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0, 20 ); - beta = random_uniform( 0, 20 ) + 2.0; + alpha = random_uniform( 0.0, 20.0 ); + beta = random_uniform( 2.0, 22.0 ); y = stdlib_base_dists_betaprime_variance( alpha, beta ); printf( "α: %lf, β: %lf, Var(X;α,β): %lf", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/benchmark/c/benchmark.c index 660565d44606..5463f4c85040 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { alpha[ i ] = random_uniform( 0.0, 20.0 ); - beta[ i ] = random_uniform( 0.0, 20.0 ) + 2.0; + beta[ i ] = random_uniform( 2.0, 22.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/c/example.c index f3186f8e0ea8..b52bc1612c2b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/c/example.c @@ -32,8 +32,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - alpha = random_uniform( 0, 20 ); - beta = random_uniform( 0, 20 ) + 2.0; + alpha = random_uniform( 0.0, 20.0 ); + beta = random_uniform( 2.0, 22.0 ); y = stdlib_base_dists_betaprime_variance( alpha, beta ); printf( "α: %lf, β: %lf, Var(X;α,β): %lf\n", alpha, beta, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/index.js index 050cbce9b599..4e3658843ad2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/examples/index.js @@ -29,7 +29,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*10.0 ) + EPS; - beta = ( randu()*10.0 ) + 2.0 + EPS; + beta = ( randu()*10.0 ) + 2.0; v = variance( alpha, beta ); console.log( 'α: %d, β: %d, Var(X;α,β): %d', alpha.toFixed( 4 ), beta.toFixed( 4 ), v.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts index 74a8dcb67d58..1c2274f57bfb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts @@ -110,7 +110,7 @@ interface Namespace { entropy: typeof entropy; /** - * Returns the kurtosis of a binomial distribution. + * Returns the excess kurtosis of a binomial distribution. * * ## Notes * diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/docs/types/index.d.ts index 6822cea9c135..8e4e5a328a27 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/docs/types/index.d.ts @@ -19,7 +19,7 @@ // TypeScript Version: 4.1 /** -* Returns the kurtosis of a binomial distribution. +* Returns the excess kurtosis of a binomial distribution. * * ## Notes * diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/lib/main.js index 57206683326b..4f8d59195179 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/kurtosis/lib/main.js @@ -28,7 +28,7 @@ var PINF = require( '@stdlib/constants/float64/pinf' ); // MAIN // /** -* Returns the kurtosis of a binomial distribution. +* Returns the excess kurtosis of a binomial distribution. * * @param {NonNegativeInteger} n - number of trials * @param {Probability} p - success probability diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/README.md index e82d7c4f8654..1ec9316424ba 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/README.md @@ -141,6 +141,101 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/binomial/mode.h" +``` + +#### stdlib_base_dists_binomial_mode( n, p ) + +Returns the [mode][mode] of a [binomial][binomial-distribution] distribution with number of trials `n` and success probability `p`. + +```c +double out = stdlib_base_dists_binomial_mode( 100, 0.1 ); +// returns 10 +``` + +The function accepts the following arguments: + +- **n**: `[in] int32_t` number of trials. +- **p**: `[in] double` success probability. + +```c +double stdlib_base_dists_binomial_mode( const int32_t n, const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/binomial/mode.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + int32_t n; + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + n = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_binomial_mode( n, p ); + printf( "n: %d, p: %lf, mode(X;n,p): %lf\n", n, p, y ); + } + + return 0; +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.js index 03f4de76544b..df21b4a84188 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.js @@ -22,6 +22,8 @@ var bench = require( '@stdlib/bench' ); var ceil = require( '@stdlib/math/base/special/ceil' ); +var Int32Array = require( '@stdlib/array/int32' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; @@ -31,16 +33,23 @@ var mode = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var n; var p; var y; var i; + len = 100; + n = new Int32Array( len ); + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + n[ i ] = ceil( randu() * 100.0 ); + p[ i ] = randu(); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - n = ceil( randu()*100.0 ); - p = randu(); - y = mode( n, p ); + y = mode( n[ i%len ], p[ i%len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..6b7fe0d32f25 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/benchmark.native.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Int32Array = require( '@stdlib/array/int32' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var n; + var p; + var y; + var i; + + len = 100; + n = new Int32Array( len ); + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + n[ i ] = ceil( randu() * 100.0 ); + p[ i ] = randu(); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( n[ i % len ], p[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..6bf8f38080bd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/mode.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include +#include +#include + +#define NAME "binomial-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t n[ 100 ]; + double p[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + n[ i ] = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p[ i ] = random_uniform( 0.0, 1.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_binomial_mode( n[ i % 100 ], p[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/examples/c/example.c new file mode 100644 index 000000000000..3af5f76f027d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/mode.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + int32_t n; + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + n = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_binomial_mode( n, p ); + printf( "n: %d, p: %lf, mode(X;n,p): %lf\n", n, p, y ); + } + + return 0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the mode of a binomial distribution with number of trials `n` and success probability `p`. +*/ +double stdlib_base_dists_binomial_mode( const int32_t n, const double p ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_BINOMIAL_MODE_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/lib/native.js new file mode 100644 index 000000000000..0cde101efecb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/lib/native.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the mode of a binomial distribution. +* +* @private +* @param {NonNegativeInteger} n - number of trials +* @param {Probability} p - success probability +* @returns {NonNegativeInteger} mode +* +* @example +* var v = mode( 100, 0.1 ); +* // returns 10 +* +* @example +* var v = mode( 20, 0.5 ); +* // returns 10 +* +* @example +* var v = mode( 20, 1.1 ); +* // returns NaN +* +* @example +* var v = mode( 20, NaN ); +* // returns NaN +*/ +function mode( n, p ) { + return addon( n, p ); +} + + +// EXPORTS // + +module.exports = mode; diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/manifest.json new file mode 100644 index 000000000000..e0a9cc89e011 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/manifest.json @@ -0,0 +1,78 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/special/floor" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/ceil", + "@stdlib/math/base/special/floor" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/ceil", + "@stdlib/math/base/special/floor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/package.json b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/package.json index 2067d0e037dd..b5ab61c569b5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/addon.c new file mode 100644 index 000000000000..e15489565890 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/mode.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_ID_D( stdlib_base_dists_binomial_mode ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/main.c new file mode 100644 index 000000000000..d82d7c21408d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/src/main.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/mode.h" +#include "stdlib/math/base/special/floor.h" + +/** +* Returns the mode of a binomial distribution. +* +* @param n number of trials +* @param p success probability +* @return mode +* +* @example +* double y = stdlib_base_dists_binomial_mode( 100, 0.1 ); +* // returns 10.0 +*/ +double stdlib_base_dists_binomial_mode( const int32_t n, const double p ) { + if ( + n < 0 || + p < 0.0 || + p > 1.0 + ) { + return 0.0 / 0.0; + } + return stdlib_base_floor( ( n + 1.0 ) * p ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/test/test.native.js new file mode 100644 index 000000000000..3ec23aa8fb48 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/mode/test/test.native.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var randu = require( '@stdlib/random/base/randu' ); +var floor = require( '@stdlib/math/base/special/floor' ); + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mode, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v; + + v = mode( 10, NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided an `n` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) { + var v; + + v = mode( -2, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = mode( -1, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a success probability `p` outside of `[0,1]`, the function returns `NaN`', opts, function test( t ) { + var v; + + v = mode( 20, -1.0 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = mode( 20, 1.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the mode of a binomial distribution', opts, function test( t ) { + var n; + var p; + var y; + var i; + + for ( i = 0; i < 10; i++ ) { + n = floor( randu() * 100.0 ); + p = randu(); + y = mode( n, p ); + t.equal( y, floor( ( n+1 ) * p ), 'returns mode' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/README.md index 5aefba7068f3..2871357efc75 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/README.md @@ -141,6 +141,103 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/binomial/variance.h" +``` + +#### stdlib_base_dists_binomial_variance( n, p ) + +Returns the [variance][variance] of a [binomial][binomial-distribution] distribution with number of trials `n` and success probability `p`. + +```c +double out = stdlib_base_dists_binomial_variance( 100, 0.1 ); +// returns 9.0 +``` + +The function accepts the following arguments: + +- **n**: `[in] int32_t` number of trials. +- **p**: `[in] double` success probability. + +```c +double stdlib_base_dists_binomial_variance( const int32_t n, const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/binomial/variance.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + int32_t n; + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + n = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_binomial_variance( n, p ); + printf( "n: %d, p: %lf, Var(X;n,p): %lf\n", n, p, y ); + } + + return 0; +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.js index b2a911db5609..a16c2394eb68 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.js @@ -22,6 +22,8 @@ var bench = require( '@stdlib/bench' ); var ceil = require( '@stdlib/math/base/special/ceil' ); +var Int32Array = require( '@stdlib/array/int32' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; @@ -31,16 +33,23 @@ var variance = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var n; var p; var y; var i; + len = 100; + n = new Int32Array( len ); + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + n[ i ] = ceil( randu() * 100.0 ); + p[ i ] = randu(); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - n = ceil( randu()*100.0 ); - p = randu(); - y = variance( n, p ); + y = variance( n[ i%len ], p[ i%len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.native.js new file mode 100644 index 000000000000..4bff698fa4aa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/benchmark.native.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Int32Array = require( '@stdlib/array/int32' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var n; + var p; + var y; + var i; + + len = 100; + n = new Int32Array( len ); + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + n[ i ] = ceil( randu() * 100.0 ); + p[ i ] = randu(); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( n[ i % len ], p[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/c/benchmark.c new file mode 100644 index 000000000000..130f87131f7d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/variance.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include +#include +#include + +#define NAME "binomial-variance" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t n[ 100 ]; + double p[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + n[ i ] = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p[ i ] = random_uniform( 0.0, 1.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_binomial_variance( n[ i % 100 ], p[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/examples/c/example.c new file mode 100644 index 000000000000..72b727c335b9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/variance.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + int32_t n; + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + n = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_binomial_variance( n, p ); + printf( "n: %d, p: %lf, Var(X;n,p): %lf\n", n, p, y ); + } + + return 0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the variance of a binomial distribution with number of trials `n` and success probability `p`. +*/ +double stdlib_base_dists_binomial_variance( const int32_t n, const double p ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_BINOMIAL_VARIANCE_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/lib/native.js new file mode 100644 index 000000000000..8e66bdfcf5bd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/lib/native.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the variance of a binomial distribution. +* +* @private +* @param {NonNegativeInteger} n - number of trials +* @param {Probability} p - success probability +* @returns {PositiveNumber} variance +* +* @example +* var v = variance( 100, 0.1 ); +* // returns 9.0 +* +* @example +* var v = variance( 20, 0.5 ); +* // returns 5.0 +* +* @example +* var v = variance( 20, 1.1 ); +* // returns NaN +* +* @example +* var v = variance( 20, NaN ); +* // returns NaN +*/ +function variance( n, p ) { + return addon( n, p ); +} + + +// EXPORTS // + +module.exports = variance; diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/manifest.json new file mode 100644 index 000000000000..30c3a89fc163 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/manifest.json @@ -0,0 +1,81 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-nonnegative-integer" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/math/base/special/ceil" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/math/base/special/ceil" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/package.json b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/package.json index 01d3a4b7c97d..d953ca93cbf8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/addon.c new file mode 100644 index 000000000000..1bb3ef3f1e6e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/variance.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_ID_D( stdlib_base_dists_binomial_variance ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/main.c new file mode 100644 index 000000000000..0889a36e8baf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/src/main.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/variance.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_nonnegative_integer.h" +#include + +/** +* Returns the variance of a binomial distribution. +* +* @param n number of trials +* @param p success probability +* @return variance +* +* @example +* double y = stdlib_base_dists_binomial_variance( 100, 0.1 ); +* // returns 9.0 +*/ +double stdlib_base_dists_binomial_variance( const int32_t n, const double p ) { + if ( + stdlib_base_is_nan( p ) || + n < 0 || + p < 0.0 || + p > 1.0 + ) { + return 0.0 / 0.0; + } + return n * p * (1.0 - p); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/test/test.native.js new file mode 100644 index 000000000000..8f65f6d5ed44 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/variance/test/test.native.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof variance, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v = variance( 10, NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided an `n` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) { + var v; + + v = variance( -2, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = variance( -1, 0.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `p < 0` or `p > 1`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = variance( 10, -0.1 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = variance( 10, 1.1 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the variance of a binomial distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var n; + var p; + var i; + var y; + + expected = data.expected; + n = data.n; + p = data.p; + for ( i = 0; i < expected.length; i++ ) { + y = variance( n[i], p[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/README.md index fa10051c17c8..322154f698d5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/README.md @@ -207,10 +207,10 @@ int main( void ) { double x0; double y; int i; - + for ( i = 0; i < 25; i++ ) { x0 = random_uniform( 0.0, 100.0 ); - gamma = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + gamma = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_cauchy_entropy( x0, gamma ); printf( "x0: %lf, gamma: %lf, F(x0;gamma): %lf\n", x0, gamma, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/benchmark/c/benchmark.c index 181b1a66d90b..f80c1bc50f9b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - x0[ i ] = random_uniform( 0.0, 100.0 ) - 50.0; - gamma[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + x0[ i ] = random_uniform( -50.0, 50.0 ); + gamma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/examples/c/example.c index f3f8c20daa8c..b745c1ffc249 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/entropy/examples/c/example.c @@ -34,7 +34,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { x0 = random_uniform( 0.0, 100.0 ); - gamma = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + gamma = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_cauchy_entropy( x0, gamma ); printf( "x0: %lf, gamma: %lf, F(x0;gamma): %lf\n", x0, gamma, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/README.md index 4ac1af07e9ee..86269e3ed706 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/README.md @@ -129,6 +129,102 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cauchy/median.h" +``` + +#### stdlib_base_dists_cauchy_median( x0, gamma ) + +Evaluates the [median][median] of a [Cauchy][cauchy-distribution] distribution with location parameter `x0` and scale parameter `gamma`. + +```c +double out = stdlib_base_dists_cauchy_median( 10.0, 5.0 ); +// returns 10.0 +``` + +The function accepts the following arguments: + +- **x0**: `[in] double` location parameter. +- **gamma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cauchy_median( const double x0, const double gamma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cauchy/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double gamma; + double x0; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x0 = random_uniform( 0.0, 100.0 ); + gamma = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + y = stdlib_base_dists_cauchy_median( x0, gamma ); + printf( "x0: %lf, gamma: %lf, Median(x0;gamma): %lf\n", x0, gamma, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.js index 836734eab4e7..54586dde21c5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -32,15 +33,22 @@ var median = require( './../lib' ); bench( pkg, function benchmark( b ) { var gamma; + var len; var x0; var y; var i; + len = 100; + x0 = new Float64Array( len ); + gamma = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x0[ i ] = ( randu() * 100.0 ) - 50.0; + gamma[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x0 = ( randu()*100.0 ) - 50.0; - gamma = ( randu()*20.0 ) + EPS; - y = median( x0, gamma ); + y = median( x0[ i % len ], gamma[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.native.js new file mode 100644 index 000000000000..5d792a294774 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var median = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( median instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var gamma; + var len; + var x0; + var y; + var i; + + len = 100; + x0 = new Float64Array( len ); + gamma = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x0[ i ] = ( randu() * 100.0 ) - 50.0; + gamma[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = median( x0[ i % len ], gamma[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/c/benchmark.c new file mode 100644 index 000000000000..d522caca3dab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cauchy/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cauchy-median" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double gamma[ 100 ]; + double x0[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x0[ i ] = random_uniform( -50.0, 50.0 ); + gamma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cauchy_median( x0[ i%100 ], gamma[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/examples/c/example.c new file mode 100644 index 000000000000..85bf300dc062 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cauchy/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double gamma; + double x0; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x0 = random_uniform( 0.0, 100.0 ); + gamma = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + y = stdlib_base_dists_cauchy_median( x0, gamma ); + printf( "x0: %lf, gamma: %lf, Median(x0;gamma): %lf\n", x0, gamma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/median/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' #include #include @@ -100,7 +99,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - k[ i ] = random_uniform( 0.0, 20.0 ) + 1.0 + STDLIB_CONSTANT_FLOAT64_EPS; + k[ i ] = random_uniform( 1.0, 21.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/mode/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/chi/mode/manifest.json index 92e6eeaf5483..546b58881775 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chi/mode/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/chi/mode/manifest.json @@ -56,8 +56,7 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/eps" + "@stdlib/math/base/special/sqrt" ] }, { diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/benchmark/c/benchmark.c index 90e3905fab19..b04d1d26de11 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - x[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.js index ee657d1e28fb..eb3fde92b0e3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.js @@ -62,7 +62,7 @@ tape( 'if provided a degrees of freedom parameter `k` that is not a positive num t.end(); }); -tape( 'the function returns the entropy of a chi-squared distribution', function test( t ) { +tape( 'the function returns the differential entropy of a chi-squared distribution', function test( t ) { var expected; var delta; var tol; diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.native.js index a4728c0c58d6..9afe3dc9f407 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/entropy/test/test.native.js @@ -71,7 +71,7 @@ tape( 'if provided a degrees of freedom parameter `k` that is not a positive num t.end(); }); -tape( 'the function returns the entropy of a chi-squared distribution', opts, function test( t ) { +tape( 'the function returns the differential entropy of a chi-squared distribution', opts, function test( t ) { var expected; var delta; var tol; diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/kurtosis/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/kurtosis/test/test.js index 61fdb2513c72..54f5e7f9ddc2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/kurtosis/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/kurtosis/test/test.js @@ -60,7 +60,7 @@ tape( 'if provided a degrees of freedom parameter `k` that is not a positive num t.end(); }); -tape( 'the function returns the kurtosis of a chi-squared distribution', function test( t ) { +tape( 'the function returns the excess kurtosis of a chi-squared distribution', function test( t ) { var expected; var k; var i; diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/README.md index af9b10e8bc63..51e181782e30 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/README.md @@ -116,6 +116,98 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/chisquare/mean.h" +``` + +#### stdlib_base_dists_chisquare_mean( k ) + +Returns the [expected value][expected-value] of a [chi-squared][chisquare-distribution] distribution with degrees of freedom `k`. + +```c +double out = stdlib_base_dists_chisquare_mean( 9.0 ); +// returns 9.0 +``` + +The function accepts the following arguments: + +- **k**: `[in] double` degrees of freedom. + +```c +double stdlib_base_dists_chisquare_mean( const double k ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/chisquare/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_mean( k ); + printf( "k: %lf, E(X;k): %lf\n", k, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.js index c8f29c68dff5..eec8ad34a92b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -31,14 +32,20 @@ var mean = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var k; var y; var i; + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - k = ( randu()*20.0 ) + EPS; - y = mean( k ); + y = mean( k[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.native.js new file mode 100644 index 000000000000..46d355a33b86 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var k; + var y; + var i; + + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mean( k[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/c/benchmark.c new file mode 100644 index 000000000000..37ef4c25f5be --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/mean.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "chisquare-mean" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double k[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_chisquare_mean( k[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/examples/c/example.c new file mode 100644 index 000000000000..43513bb636d7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_mean( k ); + printf( "k: %lf, E(X;k): %lf\n", k, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mean/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/chisquare/mgf.h" +``` + +#### stdlib_base_dists_chisquare_mgf( t, k ) + +Evaluates the moment-generating function (MGF) for a chi-squared distribution with degrees of freedom `k` at a value `t`. + +```c +double out = stdlib_base_dists_chisquare_mgf( 0.4, 2.0 ); +// returns ~5.0 +``` + +The function accepts the following arguments: + +- **t**: `[in] double` input value. +- **k**: `[in] double` degrees of freedom (must be nonnegative). + +```c +double stdlib_base_dists_chisquare_mgf( const double t, const double k ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/chisquare/mgf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double t; + double k; + int i; + + for ( i = 0; i < 10; i++ ) { + t = random_uniform( -0.5, 0.4 ); + k = random_uniform( 0.1, 10.0 ); + result = stdlib_base_dists_chisquare_mgf( t, k ); + printf( "t: %lf, k: %lf, M_X(t;k): %lf \n", t, k, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d856d25b3835 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mgf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mgf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var t; + var k; + var y; + var i; + + len = 100; + t = new Float64Array( len ); + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = ( randu() * 0.8 ) - 0.4; + k[ i ] = ( randu() * 10.0 ) + 0.1; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mgf( t[ i % len ], k[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..80bcd9e9a958 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/mgf.h" +#include +#include +#include +#include +#include + +#define NAME "chisquare-mgf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double t[ 100 ]; + double k[ 100 ]; + double y; + double start; + int i; + + for ( i = 0; i < 100; i++ ) { + t[ i ] = random_uniform( -0.4, 0.4 ); + k[ i ] = random_uniform( 0.1, 10.0 ); + } + + start = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_chisquare_mgf( t[ i % 100 ], k[ i % 100 ] ); + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - start; + + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/examples/c/example.c new file mode 100644 index 000000000000..bb655596c94c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/mgf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double t; + double k; + int i; + + for ( i = 0; i < 10; i++ ) { + t = random_uniform( -0.5, 0.4 ); + k = random_uniform( 0.1, 10.0 ); + result = stdlib_base_dists_chisquare_mgf( t, k ); + printf( "t: %lf, k: %lf, M_X(t;k): %lf \n", t, k, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= 0.5 ) { + return 0.0 / 0.0; // NaN + } + return stdlib_base_pow( 1.0 - ( 2.0 * t ), -k / 2.0 ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/test/test.native.js new file mode 100644 index 000000000000..e03ca489bc4e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/test/test.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// VARIABLES // + +var mgf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mgf instanceof Error ) +}; + + +// FIXTURES // + +var decimalDecimal = require( './fixtures/julia/decimal_decimal.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mgf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = mgf( NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = mgf( 0.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a negative `k`, the function always returns `NaN`', opts, function test( t ) { + var y; + + y = mgf( 0.4, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mgf( 0.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mgf( 0.4, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `t >= 0.5`, the function always returns `NaN`', opts, function test( t ) { + var y; + + y = mgf( 0.5, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mgf( 1.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = mgf( 10.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function evaluates the MGF for `x` given degrees of freedom `k`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var k; + var y; + var i; + + expected = decimalDecimal.expected; + x = decimalDecimal.x; + k = decimalDecimal.k; + for ( i = 0; i < x.length; i++ ) { + y = mgf( x[i], k[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', k: '+k[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. k: '+k[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/README.md index 630e19bffe34..012931bf8158 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/README.md @@ -116,6 +116,98 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/chisquare/mode.h" +``` + +#### stdlib_base_dists_chisquare_mode( k ) + +Returns the [mode][mode] of a [chi-squared][chisquare-distribution] distribution with degrees of freedom `k`. + +```c +double out = stdlib_base_dists_chisquare_mode( 9.0 ); +// returns 7.0 +``` + +The function accepts the following arguments: + +- **k**: `[in] double` degrees of freedom. + +```c +double stdlib_base_dists_chisquare_mode( const double k ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/chisquare/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_mode( k ); + printf( "k: %lf, mode(X,k): %lf\n", k, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.js index 93347dd8e9ba..fc2ed738c9b4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -31,14 +32,20 @@ var mode = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var k; var y; var i; + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - k = ( randu()*20.0 ) + EPS; - y = mode( k ); + y = mode( k[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e5e816ffdb49 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var k; + var y; + var i; + + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( k[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..6a380cc42493 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "chisquare-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double k[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_chisquare_mode( k[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/examples/c/example.c new file mode 100644 index 000000000000..579720fa2db7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_mode( k ); + printf( "k: %lf, mode(X,k): %lf\n", k, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/chisquare/stdev.h" +``` + +#### stdlib_base_dists_chisquare_stdev( k ) + +Returns the [standard deviation][stdev] of a [chi-squared][chisquare-distribution] distribution with degrees of freedom `k`. + +```c +double out = stdlib_base_dists_chisquare_stdev( 9.0 ); +// returns ~4.243 +``` + +The function accepts the following arguments: + +- **k**: `[in] double` degrees of freedom. + +```c +double stdlib_base_dists_chisquare_stdev( const double k ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/chisquare/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_stdev( k ); + printf( "k: %lf, SD(X;k): %lf\n", k, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.js index aa23a2628ebb..a70381e327b0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,14 +32,20 @@ var stdev = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var k; var y; var i; + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - k = ( randu()*20.0 ) + EPS; - y = stdev( k ); + y = stdev( k[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..2b0c6eb80f0c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var k; + var y; + var i; + + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( k[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..f7be845d4998 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "chisquare-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double k[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_chisquare_stdev( k[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/examples/c/example.c new file mode 100644 index 000000000000..926b2ccb72ea --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_stdev( k ); + printf( "k: %lf, SD(X;k): %lf\n", k, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/chisquare/variance.h" +``` + +#### stdlib_base_dists_chisquare_variance( k ) + +Returns the [variance][variance] of a [chi-squared][chisquare-distribution] distribution with degrees of freedom `k`. + +```c +double out = stdlib_base_dists_chisquare_variance( 9.0 ); +// returns 18.0 +``` + +The function accepts the following arguments: + +- **k**: `[in] double` degrees of freedom. + +```c +double stdlib_base_dists_chisquare_variance( const double k ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/chisquare/variance.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_variance( k ); + printf( "k: %lf, Var(X;k): %lf\n", k, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.js index 02a9630835e7..56d4c8c867a4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -31,14 +32,20 @@ var variance = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var k; var y; var i; + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - k = ( randu()*20.0 ) + EPS; - y = variance( k ); + y = variance( k[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.native.js new file mode 100644 index 000000000000..244976f80e84 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var k; + var y; + var i; + + len = 100; + k = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + k[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( k[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/c/benchmark.c new file mode 100644 index 000000000000..925fd93e5e37 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/variance.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "chisquare-variance" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double k[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_chisquare_variance( k[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/examples/c/example.c new file mode 100644 index 000000000000..1efd424114b5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/chisquare/variance.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double k; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + k = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_chisquare_variance( k ); + printf( "k: %lf, Var(X;k): %lf\n", k, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/variance/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/cdf.h" +``` + +#### stdlib_base_dists_cosine_cdf( x, mu, s ) + +Evaluates the [cumulative distribution function][cdf] (CDF) for a [raised cosine][cosine-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter). + +```c +double out = stdlib_base_dists_cosine_cdf( 0.5, 0.0, 1.0 ); +// returns ~0.909 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_cdf( const double x, const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -100.0, 0.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_cdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, F(x;µ,s): %lf\n", x, mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.js index b41be5be1cab..8ec1efd19217 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +32,26 @@ var cdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 100; - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = cdf( x, mu, s ); + y = cdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..8bd957351a62 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..bcd11b688ef9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double x[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -50.0, 50.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_cdf( x[ i%100 ], mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/examples/c/example.c new file mode 100644 index 000000000000..f8a18f101b43 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_cdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, F(x;µ,s): %lf\n", x, mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= mu + s ) { + return 1.0; + } + const double p = ( x - mu ) / s; + return ( 1.0 + p + ( stdlib_base_sinpi( p ) / STDLIB_CONSTANT_FLOAT64_PI ) ) / 2.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.cdf.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.cdf.js index 185eefbfdd31..0165515a217f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.cdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.cdf.js @@ -90,7 +90,7 @@ tape( 'if provided a negative `s`, the function returns `NaN`', function test( t t.end(); }); -tape( 'if provided `sigma` equals `0`, the function evaluates a degenerate distribution centered at `mu`', function test( t ) { +tape( 'if provided `s` equals `0`, the function evaluates a degenerate distribution centered at `mu`', function test( t ) { var y; y = cdf( 2.0, 2.0, 0.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.factory.js index ddf1fcbd9db1..766c28c7a59a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.factory.js @@ -130,7 +130,7 @@ tape( 'if provided a negative `s`, the created function always returns `NaN`', f t.end(); }); -tape( 'if `sigma` equals `0`, the created function evaluates a degenerate distribution centered at `mu`', function test( t ) { +tape( 'if `s` equals `0`, the created function evaluates a degenerate distribution centered at `mu`', function test( t ) { var cdf; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.native.js new file mode 100644 index 000000000000..1e3ec2da7cff --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/test/test.native.js @@ -0,0 +1,196 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var positiveMean = require( './fixtures/julia/positive_mean.json' ); +var negativeMean = require( './fixtures/julia/negative_mean.json' ); +var largeVariance = require( './fixtures/julia/large_variance.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = cdf( NaN, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = cdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = cdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a finite `mu` and `s`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 0.0, 1.0 ); + t.equal( y, 1.0, 'returns 1' ); + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and a finite `mu` and `s`, the function returns `0`', opts, function test( t ) { + var y = cdf( NINF, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'if provided a negative `s`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = cdf( 0.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = cdf( 2.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = cdf( 2.0, PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = cdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = cdf( 2.0, NaN, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `s` equals `0`, the function evaluates a degenerate distribution centered at `mu`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 2.0, 0.0 ); + t.equal( y, 1.0, 'returns 1 for x equal to mu' ); + + y = cdf( 3.0, 2.0, 0.0 ); + t.equal( y, 1.0, 'returns 1 for x greater than mu' ); + + y = cdf( 1.0, 2.0, 0.0 ); + t.equal( y, 0.0, 'returns 0 for x smaller than mu' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given positive `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = positiveMean.expected; + x = positiveMean.x; + mu = positiveMean.mu; + s = positiveMean.s; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], s[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given negative `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = negativeMean.expected; + x = negativeMean.x; + mu = negativeMean.mu; + s = negativeMean.s; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], s[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large variance ( = large `s` )', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = largeVariance.expected; + x = largeVariance.x; + mu = largeVariance.mu; + s = largeVariance.s; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], s[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/README.md index a1dd9d9a8a32..850c347d8bff 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/README.md @@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/kurtosis.h" +``` + +#### stdlib_base_dists_cosine_kurtosis( mu, s ) + +Returns the [excess kurtosis][kurtosis] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`. + +```c +double out = stdlib_base_dists_cosine_kurtosis( 0.0, 1.0 ); +// returns ~-0.594 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_kurtosis( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/kurtosis.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_kurtosis( mu, s ); + printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.js index 3506be1968fb..c1dacdf36635 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,16 +32,23 @@ var kurtosis = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = kurtosis( mu, s ); + y = kurtosis( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.native.js new file mode 100644 index 000000000000..64a3c7ccf7de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = kurtosis( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/c/benchmark.c new file mode 100644 index 000000000000..9085042ef667 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/kurtosis.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-kurtosis" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_kurtosis( mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c new file mode 100644 index 000000000000..5b6cf05db7c1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/kurtosis.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_kurtosis( mu, s ); + printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/logcdf.h" +``` + +#### stdlib_base_dists_cosine_logcdf( x, mu, s ) + +Evaluates the natural logarithm of the [cumulative distribution function][cdf] (CDF) for a [raised cosine][cosine-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter). + +```c +double out = stdlib_base_dists_cosine_logcdf( 0.5, 0.0, 1.0 ); +// returns ~0.909 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_logcdf( const double x, const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_logcdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, ln(F(x;µ,s)): %lf\n", x, mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.js index c0afb04ced6a..b75221e4999a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +32,26 @@ var logcdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 50.0; - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = logcdf( x, mu, s ); + y = logcdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..7cf0a2c4ee0a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logcdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logcdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logcdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..1f06f4aec168 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/logcdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-logcdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double x[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -50.0, 50.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_logcdf( x[ i%100 ], mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/examples/c/example.c new file mode 100644 index 000000000000..92ea4c2319e3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/logcdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_logcdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, ln(F(x;µ,s)): %lf\n", x, mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' mu + s ) { + return 0.0; + } + const double p = ( x - mu ) / s; + return stdlib_base_ln( ( 1.0 + p + ( stdlib_base_sinpi( p ) / STDLIB_CONSTANT_FLOAT64_PI ) ) / 2.0 ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.factory.js index 41e0e8bed747..8705edb38a8c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.factory.js @@ -130,7 +130,7 @@ tape( 'if provided a negative `s`, the created function always returns `NaN`', f t.end(); }); -tape( 'if `sigma` equals `0`, the created function evaluates a degenerate distribution centered at `mu`', function test( t ) { +tape( 'if `s` equals `0`, the created function evaluates a degenerate distribution centered at `mu`', function test( t ) { var logcdf; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.logcdf.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.logcdf.js index f452f4b496d3..dc3d5b2a872e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.logcdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.logcdf.js @@ -90,7 +90,7 @@ tape( 'if provided a negative `s`, the function returns `NaN`', function test( t t.end(); }); -tape( 'if provided `sigma` equals `0`, the function evaluates a degenerate distribution centered at `mu`', function test( t ) { +tape( 'if provided `s` equals `0`, the function evaluates a degenerate distribution centered at `mu`', function test( t ) { var y; y = logcdf( 2.0, 2.0, 0.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.native.js new file mode 100644 index 000000000000..50c6f14fdfd0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/test/test.native.js @@ -0,0 +1,196 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var positiveMean = require( './fixtures/julia/positive_mean.json' ); +var negativeMean = require( './fixtures/julia/negative_mean.json' ); +var largeVariance = require( './fixtures/julia/large_variance.json' ); + + +// VARIABLES // + +var logcdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logcdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logcdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = logcdf( NaN, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logcdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logcdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a finite `mu` and `s`, the function returns `0`', opts, function test( t ) { + var y = logcdf( PINF, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and a finite `mu` and `s`, the function returns `-infinity`', opts, function test( t ) { + var y = logcdf( NINF, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + t.end(); +}); + +tape( 'if provided a negative `s`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logcdf( 2.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 0.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NaN, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `s` equals `0`, the function evaluates a degenerate distribution centered at `mu`', opts, function test( t ) { + var y; + + y = logcdf( 2.0, 2.0, 0.0 ); + t.equal( y, 0.0, 'returns 0 for x equal to mu' ); + + y = logcdf( 3.0, 2.0, 0.0 ); + t.equal( y, 0.0, 'returns 0 for x greater than mu' ); + + y = logcdf( 1.0, 2.0, 0.0 ); + t.equal( y, NINF, 'returns -infinity for x smaller than mu' ); + + t.end(); +}); + +tape( 'the function evaluates the logcdf for `x` given positive `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = positiveMean.expected; + x = positiveMean.x; + mu = positiveMean.mu; + s = positiveMean.s; + for ( i = 0; i < x.length; i++ ) { + y = logcdf( x[i], mu[i], s[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 600.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the logcdf for `x` given negative `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = negativeMean.expected; + x = negativeMean.x; + mu = negativeMean.mu; + s = negativeMean.s; + for ( i = 0; i < x.length; i++ ) { + y = logcdf( x[i], mu[i], s[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 600.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the logcdf for `x` given large variance ( = large `s` )', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = largeVariance.expected; + x = largeVariance.x; + mu = largeVariance.mu; + s = largeVariance.s; + for ( i = 0; i < x.length; i++ ) { + y = logcdf( x[i], mu[i], s[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 800.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/README.md index 0b74b206266b..8f024abef3cb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/README.md @@ -152,6 +152,113 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/logpdf.h" +``` + +#### stdlib_base_dists_cosine_logpdf( x, mu, s ) + +Evaluates the logarithm of the [probability density function][pdf] (PDF) for a [raised cosine][cosine-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter). + +```c +double out = stdlib_base_dists_cosine_logpdf( 2.0, 0.0, 3.0 ); +// returns ~-2.485 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_logpdf( const double x, const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/logpdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_logpdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, ln(f(x;µ,s)): %lf\n", x, mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.js index d8ab8f01bbbe..036e2443660e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +32,26 @@ var logpdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 100; - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = logpdf( x, mu, s ); + y = logpdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..9983053f6b73 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logpdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..86cc9fb79ed1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/logpdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-logpdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double x[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -50.0, 50.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_logpdf( x[ i%100 ], mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c new file mode 100644 index 000000000000..fa760d11d9a9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/logpdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_logpdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, ln(f(x;µ,s)): %lf\n", x, mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' mu + s + ) { + return STDLIB_CONSTANT_FLOAT64_NINF; + } + const double p = ( x - mu ) / s; + return stdlib_base_ln( 1.0 + stdlib_base_cospi( p ) ) - stdlib_base_ln( 2.0 * s ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.factory.js index 31fe7285ba11..2ed4e0240c3d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.factory.js @@ -77,7 +77,7 @@ tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', t.end(); }); -tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `-infinity` when provided `x` greater than `mu + sigma`', function test( t ) { +tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `-infinity` when provided `x` greater than `mu + s`', function test( t ) { var logpdf; var y; @@ -95,7 +95,7 @@ tape( 'if provided a finite `mu` and `s`, the function returns a function which t.end(); }); -tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `-infinity` when provided `x` smaller than `mu - sigma`', function test( t ) { +tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `-infinity` when provided `x` smaller than `mu - s`', function test( t ) { var logpdf; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.logpdf.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.logpdf.js index 8705230967de..0c8569078272 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.logpdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.logpdf.js @@ -54,7 +54,7 @@ tape( 'if provided `NaN` for any parameter, the function returns `NaN`', functio t.end(); }); -tape( 'if provided `x` greater than `mu + sigma`, the function returns `-infinity`', function test( t ) { +tape( 'if provided `x` greater than `mu + s`, the function returns `-infinity`', function test( t ) { var y = logpdf( PINF, 0.0, 1.0 ); t.equal( y, NINF, 'returns -infinity' ); @@ -67,7 +67,7 @@ tape( 'if provided `x` greater than `mu + sigma`, the function returns `-infinit t.end(); }); -tape( 'if provided `x` smaller than `mu - sigma`, the function returns `-infinity`', function test( t ) { +tape( 'if provided `x` smaller than `mu - s`, the function returns `-infinity`', function test( t ) { var y = logpdf( NINF, 0.0, 1.0 ); t.equal( y, NINF, 'returns -infinity' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.native.js new file mode 100644 index 000000000000..058a1f458376 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/test/test.native.js @@ -0,0 +1,222 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var positiveMean = require( './fixtures/julia/positive_mean.json' ); +var negativeMean = require( './fixtures/julia/negative_mean.json' ); +var largeVariance = require( './fixtures/julia/large_variance.json' ); + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logpdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = logpdf( NaN, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logpdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logpdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided `x` greater than `mu + s`, the function returns `-infinity`', opts, function test( t ) { + var y = logpdf( PINF, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 20.0, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 2.0, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided `x` smaller than `mu - s`, the function returns `-infinity`', opts, function test( t ) { + var y = logpdf( NINF, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + logpdf( -20.0, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + logpdf( -2.0, 0.0, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided a negative `s`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logpdf( 2.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NaN, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `s` equal to `0`, the function evaluates a degenerate distribution centered at `mu`', opts, function test( t ) { + var y; + + y = logpdf( 2.0, 2.0, 0.0 ); + t.equal( y, PINF, 'returns +infinity for x equal to mu' ); + + y = logpdf( 1.0, 2.0, 0.0 ); + t.equal( y, NINF, 'returns -infinity ' ); + + y = logpdf( PINF, 2.0, 0.0 ); + t.equal( y, NINF, 'returns -infinity ' ); + + y = logpdf( NINF, 2.0, 0.0 ); + t.equal( y, NINF, 'returns -infinity ' ); + + y = logpdf( NaN, 2.0, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function evaluates the logpdf for `x` given positive `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = positiveMean.expected; + x = positiveMean.x; + mu = positiveMean.mu; + s = positiveMean.s; + for ( i = 0; i < x.length; i++ ) { + y = logpdf( x[i], mu[i], s[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); + +tape( 'the function evaluates the logpdf for `x` given negative `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = negativeMean.expected; + x = negativeMean.x; + mu = negativeMean.mu; + s = negativeMean.s; + for ( i = 0; i < x.length; i++ ) { + y = logpdf( x[i], mu[i], s[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); + +tape( 'the function evaluates the logpdf for `x` given large variance ( = large `s` )', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = largeVariance.expected; + x = largeVariance.x; + mu = largeVariance.mu; + s = largeVariance.s; + for ( i = 0; i < x.length; i++ ) { + y = logpdf( x[i], mu[i], s[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 15.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md index 01caa20e621e..563b1f47f723 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md @@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/median.h" +``` + +#### stdlib_base_dists_cosine_median( mu, s ) + +Returns the [median][median] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`. + +```c +double out = stdlib_base_dists_cosine_median( 0.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_median( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_median( mu, s ); + printf( "µ: %lf, s: %lf, Median(X;µ,s): %lf\n", mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js index 8e02177c21e0..0d6f60f7dd67 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,16 +32,23 @@ var median = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = median( mu, s ); + y = median( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d73d223ebdbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var median = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( median instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = median( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c new file mode 100644 index 000000000000..459282e40936 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-median" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_median( mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c new file mode 100644 index 000000000000..7d0e4f9ce393 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_median( mu, s ); + printf( "µ: %lf, s: %lf, Median(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/mgf.h" +``` + +#### stdlib_base_dists_cosine_mgf( t, mu, s ) + +Returns the [moment-generating function][mgf] (MGF) for a [raised cosine][cosine-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter). + +```c +double out = stdlib_base_dists_cosine_mgf( 0.5, 0.0, 1.0 ); +// returns ~1.016 +``` + +The function accepts the following arguments: + +- **t**: `[in] double` input value. +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_mgf( const double t, const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/mgf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double t; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + t = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_mgf( t, mu, s ); + printf( "t: %lf, µ: %lf, s: %lf, M_X(t;µ,s): %lf\n", t, mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.js index a8eb484967b8..63582742da3d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +32,26 @@ var mgf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var t; var y; var i; + len = 100; + t = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = ( randu()*10.0 ) + EPS; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - t = ( randu()*10.0 ) + EPS; - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = mgf( t, mu, s ); + y = mgf( t[ i % len ], mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..451cac79ee31 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mgf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mgf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var t; + var y; + var i; + + len = 100; + t = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = ( randu()*10.0 ) + EPS; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mgf( t[ i % len ], mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..607aab549d18 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/mgf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-mgf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double t[ 100 ]; + double s[ 100 ]; + double y; + double tc; + int i; + + for ( i = 0; i < 100; i++ ) { + t[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + tc = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_mgf( t[ i%100 ], mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - tc; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c new file mode 100644 index 000000000000..9ebd0e57739a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/mgf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double t; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + t = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_mgf( t, mu, s ); + printf( "t: %lf, µ: %lf, s: %lf, M_X(t;µ,s): %lf\n", t, mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/mode.h" +``` + +#### stdlib_base_dists_cosine_mode( mu, s ) + +Returns the [mode][mode] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`. + +```c +double out = stdlib_base_dists_cosine_mode( 0.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_mode( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_mode( mu, s ); + printf( "µ: %lf, s: %lf, mode(X;µ,s): %lf\n", mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js index dec66e180c0f..5cf431a76211 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,16 +32,23 @@ var mode = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = mode( mu, s ); + y = mode( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..7fa1ff79dd31 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..04a2dffbb6c2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_mode( mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c new file mode 100644 index 000000000000..be60614eadb3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_mode( mu, s ); + printf( "µ: %lf, s: %lf, mode(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/pdf.h" +``` + +#### stdlib_base_dists_cosine_pdf( x, mu, s ) + +Evaluates the [probability density function][pdf] (PDF) for a [raised cosine][cosine-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter). + +```c +double out = stdlib_base_dists_cosine_pdf( 2.0, 0.0, 3.0 ); +// returns ~0.083 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_pdf( const double x, const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/pdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_pdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, f(x;µ,s): %lf\n", x, mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.js index fe2319ce5b3c..172c602c7e0b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +32,26 @@ var pdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*40.0 ) - 20.0; - mu = ( randu()*20.0 ) - 10.0; - s = ( randu()*5.0 ) + EPS; - y = pdf( x, mu, s ); + y = pdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e778ff70de49 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( pdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu()*100.0 ) - 50.0; + mu[ i ] = ( randu()*20.0 ) - 10.0; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = pdf( x[ i % len ], mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..049edc9bda69 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/pdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-pdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double x[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -50.0, 50.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_pdf( x[ i%100 ], mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c new file mode 100644 index 000000000000..7091f37a104d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/pdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -50.0, 50.0 ); + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_pdf( x, mu, s ); + printf( "x: %lf, µ: %lf, s: %lf, f(x;µ,s): %lf\n", x, mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' mu + s + ) { + return 0.0; + } + const double p = ( x - mu ) / s; + return ( 1.0 + stdlib_base_cospi( p ) ) / ( 2.0 * s ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.factory.js index 9da5edef4bad..0cf25280c611 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.factory.js @@ -77,7 +77,7 @@ tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', t.end(); }); -tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `0` when provided `x` greater than `mu + sigma`', function test( t ) { +tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `0` when provided `x` greater than `mu + s`', function test( t ) { var pdf; var y; @@ -95,7 +95,7 @@ tape( 'if provided a finite `mu` and `s`, the function returns a function which t.end(); }); -tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `0` when provided `x` smaller than `mu - sigma`', function test( t ) { +tape( 'if provided a finite `mu` and `s`, the function returns a function which returns `0` when provided `x` smaller than `mu - s`', function test( t ) { var pdf; var y; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.native.js new file mode 100644 index 000000000000..38d82cc5905b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.native.js @@ -0,0 +1,222 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var positiveMean = require( './fixtures/julia/positive_mean.json' ); +var negativeMean = require( './fixtures/julia/negative_mean.json' ); +var largeVariance = require( './fixtures/julia/large_variance.json' ); + + +// VARIABLES // + +var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( pdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof pdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = pdf( NaN, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = pdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = pdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided `x` greater than `mu + s`, the function returns `0`', opts, function test( t ) { + var y = pdf( PINF, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( 20.0, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( 2.0, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + t.end(); +}); + +tape( 'if provided `x` smaller than `mu - s`, the function returns `0`', opts, function test( t ) { + var y = pdf( NINF, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + pdf( -20.0, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + pdf( -2.0, 0.0, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + t.end(); +}); + +tape( 'if provided a negative `s`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = pdf( 2.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 0.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 2.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 2.0, PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 2.0, NaN, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `s` equal to `0`, the function evaluates a degenerate distribution centered at `mu`', opts, function test( t ) { + var y; + + y = pdf( 2.0, 2.0, 0.0 ); + t.equal( y, PINF, 'returns +infinity for x equal to mu' ); + + y = pdf( 1.0, 2.0, 0.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( PINF, 2.0, 0.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( NINF, 2.0, 0.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( NaN, 2.0, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function evaluates the pdf for `x` given positive `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = positiveMean.expected; + x = positiveMean.x; + mu = positiveMean.mu; + s = positiveMean.s; + for ( i = 0; i < x.length; i++ ) { + y = pdf( x[i], mu[i], s[i] ); + if ( expected[i] !== null && !(expected[i] === 0.0 && y < EPS ) ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 3.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); + +tape( 'the function evaluates the pdf for `x` given negative `mu`', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = negativeMean.expected; + x = negativeMean.x; + mu = negativeMean.mu; + s = negativeMean.s; + for ( i = 0; i < x.length; i++ ) { + y = pdf( x[i], mu[i], s[i] ); + if ( expected[i] !== null && !(expected[i] === 0.0 && y < EPS ) ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 4.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); + +tape( 'the function evaluates the pdf for `x` given large variance ( = large `s` )', opts, function test( t ) { + var expected; + var delta; + var tol; + var mu; + var x; + var s; + var y; + var i; + + expected = largeVariance.expected; + x = largeVariance.x; + mu = largeVariance.mu; + s = largeVariance.s; + for ( i = 0; i < x.length; i++ ) { + y = pdf( x[i], mu[i], s[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 3.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.pdf.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.pdf.js index 87073b289b88..51ac563634d2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.pdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/test/test.pdf.js @@ -54,7 +54,7 @@ tape( 'if provided `NaN` for any parameter, the function returns `NaN`', functio t.end(); }); -tape( 'if provided `x` greater than `mu + sigma`,, the function returns `0`', function test( t ) { +tape( 'if provided `x` greater than `mu + s`, the function returns `0`', function test( t ) { var y = pdf( PINF, 0.0, 1.0 ); t.equal( y, 0.0, 'returns 0' ); @@ -67,7 +67,7 @@ tape( 'if provided `x` greater than `mu + sigma`,, the function returns `0`', fu t.end(); }); -tape( 'if provided `x` smaller than `mu - sigma`, the function returns `0`', function test( t ) { +tape( 'if provided `x` smaller than `mu - s`, the function returns `0`', function test( t ) { var y = pdf( NINF, 0.0, 1.0 ); t.equal( y, 0.0, 'returns 0' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md index b6b352571c29..ddb92593d897 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md @@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/skewness.h" +``` + +#### stdlib_base_dists_cosine_skewness( mu, s ) + +Returns the [skewness][skewness] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`. + +```c +double out = stdlib_base_dists_cosine_skewness( 0.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_skewness( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_skewness( mu, s ); + printf( "µ: %lf, s: %lf, Skew(X;µ,s): %lf\n", mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js index e4313c4a4210..2f3b8471a648 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,16 +32,23 @@ var skewness = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = skewness( mu, s ); + y = skewness( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..87a8210b7071 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..732686297279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_skewness( mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c new file mode 100644 index 000000000000..c2a40bdcf677 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_skewness( mu, s ); + printf( "µ: %lf, s: %lf, skew(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/cosine/stdev.h" +``` + +#### stdlib_base_dists_cosine_stdev( mu, s ) + +Returns the [standard deviation][stdev] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`. + +```c +double out = stdlib_base_dists_cosine_stdev( 0.0, 1.0 ); +// returns ~0.362 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_cosine_stdev( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/cosine/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_stdev( mu, s ); + printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s , y ); + } + + return 0; +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js index 5544fb29feee..8f9f84b7521e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,16 +32,23 @@ var stdev = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = stdev( mu, s ); + y = stdev( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..f929b13622f3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..92aba26ab197 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "cosine-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_cosine_stdev( mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c new file mode 100644 index 000000000000..34c15ce73bef --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/cosine/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_dists_cosine_stdev( mu, s ); + printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/logpdf.h" +``` + +#### stdlib_base_dists_degenerate_logpdf( x, mu ) + +Evaluates the natural logarithm of the probability density function (logPDF) for a degenerate distribution. + +```c +double out = stdlib_base_dists_degenerate_logpdf( 2.0, 3.0 ); +// returns -Infinity +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_logpdf( const double x, const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degerate/logpdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 5.0 ); + mu = random_uniform( 0.0, 5.0 ); + y = stdlib_base_dists_degerate_logpdf( x, mu ); + printf( "x: %lf, µ: %lf, ln(f(x;µ)): %lf\n", x, mu, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.js index 30b89f84b562..8717333d6e9e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var logpdf = require( './../lib' ); @@ -30,16 +31,23 @@ var logpdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu() * 100.0 ) - 100.0; + mu[ i ] = ( randu() * 100.0 ) - 50.0; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 100; - mu = ( randu()*100.0 ) - 50.0; - y = logpdf( x, mu ); + y = logpdf( x[ i % len ], mu[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..fbd1a9de4c5d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu() * 100.0 ) - 100.0; + mu[ i ] = ( randu() * 100.0 ) - 50.0; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logpdf( x[ i % len ], mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..b87ba976df64 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/benchmark/c/benchmark.c @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/logpdf.h" +#include +#include +#include +#include +#include + +#define NAME "degenrate-logpdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double x[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -100.0, 0.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_logpdf( x[ i%100 ], mu[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/examples/c/example.c new file mode 100644 index 000000000000..0951769dc732 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/logpdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 5.0 ); + mu = random_uniform( 0.0, 5.0 ); + y = stdlib_base_dists_degenerate_logpdf( x, mu ); + printf( "x: %lf, µ: %lf, ln(f(x;µ)): %lf\n", x, mu, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/logpmf.h" +``` + +#### stdlib_base_dists_degenerate_logpmf( x, mu ) + +Evaluates the natural logarithm of the [probability mass function][pmf] (PMF) for a [degenerate distribution][degenerate-distribution]. + +```c +double out = stdlib_base_dists_degenerate_logpmf( 2.0, 3.0 ); +// returns -Infinity +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_logpmf( const double x, const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/logpmf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double x; + int i; + + for ( i = 0; i < 10; i++ ) { + x = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_logpmf( x, mu ); + printf( "x: %lf, µ: %lf, ln(P(X=x;µ)): %lf \n", x, mu, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.js index d4570d5632b2..a5d13b4651e3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.js @@ -21,8 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var ceil = require( '@stdlib/math/base/special/ceil' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var logpmf = require( './../lib' ); @@ -31,16 +32,23 @@ var logpmf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ceil( uniform( -100.0, 0.0 ) ); + mu[ i ] = uniform( -50.0, 50.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ceil( ( randu()*100.0 ) - 100.0 ); - mu = ( randu()*100.0 ) - 50.0; - y = logpmf( x, mu ); + y = logpmf( x[ i % len ], mu[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -55,6 +63,7 @@ bench( pkg, function benchmark( b ) { bench( pkg+':factory', function benchmark( b ) { var mypmf; + var len; var mu; var x; var y; @@ -62,11 +71,15 @@ bench( pkg+':factory', function benchmark( b ) { mu = 40.0; mypmf = logpmf.factory( mu ); + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ceil( uniform( -100.0, 0.0 ) ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ceil( randu()*100.0 ); - y = mypmf( x ); + y = mypmf( x[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..170fee14cc0f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logpmf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpmf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ceil( uniform( -100.0, 0.0 ) ); + mu[ i ] = uniform( -50.0, 50.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logpmf( x[ i % len ], mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..3e6d5fdec751 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/logpmf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-logpmf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double mu[ 100 ]; + double x[ 100 ]; + double elapsed; + double start; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = stdlib_base_ceil( random_uniform( -100.0, 0.0 ) ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + start = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_logpmf( x[ i % 100 ], mu[ i % 100 ] ); + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - start; + + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/examples/c/example.c new file mode 100644 index 000000000000..9fe334afb305 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/logpmf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double x; + int i; + + for ( i = 0; i < 10; i++ ) { + x = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_logpmf( x, mu ); + printf( "x: %lf, µ: %lf, ln(P(X=x;µ)): %lf \n", x, mu, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/mean.h" +``` + +#### stdlib_base_dists_degenerate_mean( mu ) + +Returns the [expected value][expected-value] of a [degenerate][degenerate-distribution] distribution with constant value `mu`. + +```c +double out = stdlib_base_dists_degenerate_mean( 0.1 ); +// returns 0.1 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_mean( const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double v; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( 0.0, 1.0 ); + v = stdlib_base_dists_degenerate_mean( mu ); + printf( "µ: %lf, E(X;µ): %lf\n", mu, v ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.js index f7a5122adb77..00c8ab4e94dd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; @@ -30,14 +31,20 @@ var mean = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var y; var i; + len = 100; + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - y = mean( mu ); + y = mean( mu[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.native.js new file mode 100644 index 000000000000..724634a5553e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mean( mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/c/benchmark.c new file mode 100644 index 000000000000..521b442ec019 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/mean.h" +#include +#include +#include +#include +#include + +#define NAME "degenrate-mean" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_mean( mu[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/examples/c/example.c new file mode 100644 index 000000000000..7258bbf4824f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double v; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( 0.0, 1.0 ); + v = stdlib_base_dists_degenerate_mean( mu ); + printf( "µ: %lf, E(X;µ): %lf\n", mu, v ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mean/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/median.h" +``` + +#### stdlib_base_dists_degenerate_median( mu ) + +Returns the [median][median] of a [degenerate][degenerate-distribution] distribution with constant value `mu`. + +```c +double out = stdlib_base_dists_degenerate_median( 0.1 ); +// returns 0.1 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_median( const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/median.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double mu; + double m; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( 0.0, 20.0 ); + m = stdlib_base_dists_degenerate_median( mu ); + printf( "µ: %lf, Median(X;µ): %lf\n", mu, m ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.js index 3948fad31a64..5bb9a4900335 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var median = require( './../lib' ); @@ -36,7 +36,7 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; + mu = uniform( -50.0, 50.0 ); y = median( mu ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.native.js new file mode 100644 index 000000000000..82e583b7f845 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var median = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( median instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = uniform( -50.0, 50.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = median( mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/c/benchmark.c new file mode 100644 index 000000000000..b3c2cb4bc27b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/median.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-median" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double mu[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -20.0, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_median( mu[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/examples/c/example.c new file mode 100644 index 000000000000..05c91f25340e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/median.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double mu; + double m; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( 0.0, 20.0 ); + m = stdlib_base_dists_degenerate_median( mu ); + printf( "µ: %lf, Median(X;µ): %lf\n", mu, m ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/median/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/mgf.h" +``` + +#### stdlib_base_dists_degenerate_mgf( t, mu ) + +Evaluates the moment-generating function ([MGF][mgf]) of a [degenerate][degenerate] distribution with parameter `mu` (mean). + +```c +double out = stdlib_base_dists_degenerate_mgf( 1.0, 1.0 ); +// returns ~2.718 +``` + +The function accepts the following arguments: + +- **t**: `[in] double` input value. +- **mu**: `[in] double` value at which to center the distribution. + +```c +double stdlib_base_dists_degenerate_mgf( const double t, const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/mgf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double t; + int i; + + for ( i = 0; i < 10; i++ ) { + t = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_mgf( t, mu ); + printf( "t: %lf, µ: %lf, M_X(t;µ): %lf\n", t, mu, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.js index 592351adeb95..f8a7503ac17d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.js @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var mgf = require( './../lib' ); @@ -30,16 +31,23 @@ var mgf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var t; var y; var i; + len = 100; + t = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = uniform( -100.0, 0.0 ); + mu[ i ] = uniform( -50.0, 50.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - t = ( randu()*100.0 ) - 100; - mu = ( randu()*100.0 ) - 50.0; - y = mgf( t, mu ); + y = mgf( t[ i % len ], mu[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -54,6 +62,7 @@ bench( pkg, function benchmark( b ) { bench( pkg+':factory', function benchmark( b ) { var mymgf; + var len; var mu; var t; var y; @@ -61,11 +70,15 @@ bench( pkg+':factory', function benchmark( b ) { mu = 40.0; mymgf = mgf.factory( mu ); + len = 100; + t = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = uniform( 0.0, 100.0 ); + } b.tic(); for ( i = 0; i < b.iterations; i++ ) { - t = randu() * 100.0; - y = mymgf( t ); + y = mymgf( t[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..0a70044e869e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mgf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mgf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var t; + var y; + var i; + + len = 100; + t = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = uniform( -100.0, 0.0 ); + mu[ i ] = uniform( -50.0, 50.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mgf( t[ i % len ], mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..984d9f5bd660 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/mgf.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-mgf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double mu[ 100 ]; + double t[ 100 ]; + double elapsed; + double start; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + t[ i ] = random_uniform( -10.0, 0.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + start = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_mgf( t[ i % 100 ], mu[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - start; + + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/examples/c/example.c new file mode 100644 index 000000000000..0545da25f0f0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/mgf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double t; + int i; + + for ( i = 0; i < 10; i++ ) { + t = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_mgf( t, mu ); + printf( "t: %lf, µ: %lf, M_X(t;µ): %lf\n", t, mu, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mgf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/mode.h" +``` + +#### stdlib_base_dists_degenerate_mode( mu ) + +Returns the [mode][mode] of a [degenerate][degenerate-distribution] distribution with constant value `mu`. + +```c +double out = stdlib_base_dists_degenerate_mode( 0.1 ); +// returns 0.1 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_mode( const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double mu; + double m; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( 0.0, 20.0 ); + m = stdlib_base_dists_degenerate_mode( mu ); + printf( "µ: %lf, mode(X;µ): %lf\n", mu, m ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..8ab66c9835f7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 40.0 ) - 20.0; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..0f177a8993e4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/mode.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -20.0, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_mode( mu[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/examples/c/example.c new file mode 100644 index 000000000000..fd2cecdf99e1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double mu; + double m; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( 0.0, 20.0 ); + m = stdlib_base_dists_degenerate_mode( mu ); + printf( "µ: %lf, mode(X;µ): %lf\n", mu, m ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/pdf.h" +``` + +#### stdlib_base_dists_degenerate_pdf( x, mu ) + +Evaluates the [PDF][pdf] of a [degenerate distribution][degenerate-distribution] centered at `mu`. + +```c +double out = stdlib_base_dists_degenerate_pdf( 2.0, 3.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_pdf( const double x, const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/pdf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double x; + int i; + + for ( i = 0; i < 10; i++ ) { + x = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_pdf( x, mu ); + printf( "x: %lf, µ: %lf, f(x;µ): %lf \n", x, mu, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.js index 150506c85e16..412c66891b9a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var pdf = require( './../lib' ); @@ -37,8 +38,8 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*100.0 ) - 100; - mu = ( randu()*100.0 ) - 50.0; + x = uniform( -100.0, 0.0 ); + mu = uniform( -50.0, 50.0 ); y = pdf( x, mu ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..dc67518f01ad --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( pdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( -100.0, 0.0 ); + mu[ i ] = uniform( -50.0, 50.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = pdf( x[ i % len ], mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..5b0b2adf16a5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/pdf.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-pdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double mu[ 100 ]; + double x[ 100 ]; + double elapsed; + double start; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -100.0, 0.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + start = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_pdf( x[ i % 100 ], mu[ i % 100 ] ); + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - start; + + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/examples/c/example.c new file mode 100644 index 000000000000..76c2a1daad55 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/pdf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double x; + int i; + + for ( i = 0; i < 10; i++ ) { + x = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_pdf( x, mu ); + printf( "x: %lf, µ: %lf, f(x;µ): %lf \n", x, mu, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/pmf.h" +``` + +#### stdlib_base_dists_degenerate_pmf( x, mu ) + +Evaluates the [PMF][pmf] of a [degenerate distribution][degenerate-distribution] centered at `mu`. + +```c +double out = stdlib_base_dists_degenerate_pmf( 2.0, 3.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_pmf( const double x, const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/pmf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double x; + int i; + + for ( i = 0; i < 10; i++ ) { + x = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_pmf( x, mu ); + printf( "x: %lf, µ: %lf, P(X=x;µ): %lf \n", x, mu, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.js index 322377266745..130d52485228 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var ceil = require( '@stdlib/math/base/special/ceil' ); var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var pmf = require( './../lib' ); @@ -38,8 +39,8 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ceil( ( randu()*100.0 ) - 100.0 ); - mu = ( randu()*100.0 ) - 50.0; + x = ceil( uniform( -100.0, 0.0 ) ); + mu = uniform( -50.0, 50.0 ); y = pmf( x, mu ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..1f00edca791a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var pmf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( pmf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ceil( uniform( -100.0, 0.0 ) ); + mu[ i ] = uniform( -50.0, 50.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = pmf( x[ i % len ], mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..7a0abc18dab2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/pmf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-pmf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double mu[ 100 ]; + double x[ 100 ]; + double elapsed; + double start; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = stdlib_base_ceil( random_uniform( -100.0, 0.0 ) ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + start = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_pmf( x[ i % 100 ], mu[ i % 100 ] ); + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - start; + + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/examples/c/example.c new file mode 100644 index 000000000000..a2e11a583828 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/pmf.h" +#include "stdlib/math/base/special/round.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double x; + int i; + + for ( i = 0; i < 10; i++ ) { + x = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + mu = stdlib_base_round( random_uniform( 0.0, 5.0 ) ); + result = stdlib_base_dists_degenerate_pmf( x, mu ); + printf( "x: %lf, µ: %lf, P(X=x;µ): %lf \n", x, mu, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/pmf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/quantile.h" +``` + +#### stdlib_base_dists_degenerate_quantile( p, mu ) + +Evaluates the [quantile function][quantile-function] of a [degenerate distribution][degenerate-distribution] centered at `mu`. + +```c +double out = stdlib_base_dists_degenerate_quantile( 0.5, 2.0 ); +// returns 2.0 +``` + +The function accepts the following arguments: + +- **p**: `[in] double` input value (probability). +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_quantile( const double p, const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/quantile.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double p; + int i; + + for ( i = 0; i < 10; i++ ) { + p = random_uniform( 0.0, 1.0 ); + mu = random_uniform( -20.0, 20.0 ); + result = stdlib_base_dists_degenerate_quantile( p, mu ); + printf( "p: %lf, µ: %lf, Q(p;µ): %lf \n", p, mu, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.js index ab818a910db9..d17acf324032 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pkg = require( './../package.json' ).name; var quantile = require( './../lib' ); @@ -38,7 +39,7 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { p = randu(); - mu = ( randu()*100.0 ) - 50.0; + mu = uniform( -50.0, 50.0 ); y = quantile( p, mu ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.native.js new file mode 100644 index 000000000000..7e3e85a76884 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var quantile = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( quantile instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var p; + var y; + var i; + + len = 100; + p = new Float64Array( len ); + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = randu(); + mu[ i ] = uniform( -50.0, 50.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = quantile( p[ i % len ], mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/c/benchmark.c new file mode 100644 index 000000000000..a5e86444a6c6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/quantile.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-quantile" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double mu[ 100 ]; + double p[ 100 ]; + double elapsed; + double start; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + p[ i ] = random_uniform( 0.0, 1.0 ); + mu[ i ] = random_uniform( -50.0, 50.0 ); + } + + start = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_quantile( p[ i % 100 ], mu[ i % 100 ] ); + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - start; + + if ( isnan( y ) ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i + 1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/examples/c/example.c new file mode 100644 index 000000000000..f4a9a709960a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/quantile.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + double p; + int i; + + for ( i = 0; i < 10; i++ ) { + p = random_uniform( 0.0, 1.0 ); + mu = random_uniform( -20.0, 20.0 ); + result = stdlib_base_dists_degenerate_quantile( p, mu ); + printf( "p: %lf, µ: %lf, Q(p;µ): %lf \n", p, mu, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' 1.0 ) { + return 0.0 / 0.0; // NaN + } + return mu; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/test/test.native.js new file mode 100644 index 000000000000..e191e3ae4e8b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/quantile/test/test.native.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// VARIABLES // + +var quantile = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( quantile instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof quantile, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y; + + y = quantile( NaN, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = quantile( 0.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = quantile( NaN, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a number outside the interval `[0,1]` for `p`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = quantile( 1.1, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = quantile( -0.1, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a number on the interval `[0,1]` for `p`, the function returns `mu`', opts, function test( t ) { + var mu; + var y; + + mu = 2.0; + + y = quantile( 0.3, mu ); + t.equal( y, mu, 'returns `mu`' ); + + y = quantile( 0.8, mu ); + t.equal( y, mu, 'returns `mu`' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/README.md index d99f1b79ed9e..27c1264df1e5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/README.md @@ -111,6 +111,98 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/degenerate/stdev.h" +``` + +#### stdlib_base_dists_degenerate_stdev( mu ) + +Returns the [standard deviation][standard-deviation] of a [degenerate][degenerate-distribution] distribution with constant value `mu`. + +```c +double out = stdlib_base_dists_degenerate_stdev( 0.1 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` constant value of the distribution. + +```c +double stdlib_base_dists_degenerate_stdev( const double mu ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/degenerate/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -20.0, 20.0 ); + result = stdlib_base_dists_degenerate_stdev( mu ); + printf( "mu: %lf, SD(X;µ): %lf \n", mu, result ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..712dcb882b7c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 40.0 ) - 20.0; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..9ee8cc9ef2ec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/stdev.h" +#include +#include +#include +#include +#include + +#define NAME "degenerate-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -20.0, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_degenerate_stdev( mu[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/examples/c/example.c new file mode 100644 index 000000000000..8831db155e1f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/degenerate/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double result; + double mu; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -20.0, 20.0 ); + result = stdlib_base_dists_degenerate_stdev( mu ); + printf( "mu: %lf, SD(X;µ): %lf \n", mu, result ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/degenerate/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/cdf.h" +``` + +#### stdlib_base_dists_discrete_uniform_cdf( x, a, b ) + +Evaluates the [cumulative distribution function][cdf] (CDF) for a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_cdf( 9.0, 0, 10 ); +// returns ~0.909 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_cdf( const double x, const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/cdf.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -10.0, 10.0 ); + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( a, a+10.0 ) ); + y = stdlib_base_dists_discrete_uniform_cdf( x, a, b ); + printf( "x:%lf, a: %d, b: %d, F(X;a,b): %lf\n", x, a, b, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.js index c0f98388f13b..6db573ea22d0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,16 +34,24 @@ var cdf = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu() * 20.0 ) - 10.0; + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu() * 20.0 ) - 10.0; - min = round( ( randu() * 20.0 ) - 20.0 ); - max = round( min + ( randu() * 40.0 ) ); - y = cdf( x, min, max ); + y = cdf( x[ i % len ], min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..deca086dd66d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( randu() * 20.0 ) - 10.0; + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % len ], min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..dddba72b1f68 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/benchmark/c/benchmark.c @@ -0,0 +1,144 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/cdf.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double x[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -10.0, 10.0 ); + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_cdf( x[ i%100 ] ,a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/examples/c/example.c new file mode 100644 index 000000000000..e2a0a3757e39 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/cdf.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( -10.0, 10.0 ); + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_cdf( x, a, b ); + printf( "x:%lf, a: %d, b: %d, F(X;a,b): %lf\n", x, a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the cumulative distribution function (CDF) of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_cdf( const double x, const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_CDF_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/lib/native.js new file mode 100644 index 000000000000..d9bbcf6d97af --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/lib/native.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for a discrete uniform distribution with minimum support `a` and maximum support `b` at a value `x`. +* +* @private +* @param {number} x - input value +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {Probability} evaluated CDF +* +* @example +* var y = cdf( 9.0, 0.0, 10.0 ); +* // returns ~0.909 +* +* @example +* var y = cdf( 0.5, 0.0, 2.0 ); +* // returns ~0.333 +* +* @example +* var y = cdf( +Infinity, 2.0, 4.0 ); +* // returns 1.0 +* +* @example +* var y = cdf( -Infinity, 2.0, 4.0 ); +* // returns 0.0 +* +* @example +* var y = cdf( 2.0, 1.0, 0.0 ); +* // returns NaN +*/ +function cdf( x, a, b ) { + return addon( x, a, b ); +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/manifest.json new file mode 100644 index 000000000000..f60b8c621079 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/manifest.json @@ -0,0 +1,81 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/ternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/floor" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/floor" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/floor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/package.json index 883bdd7b0ec3..46d5a397838c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/addon.c new file mode 100644 index 000000000000..8f32244d5d05 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/cdf.h" +#include "stdlib/math/base/napi/ternary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_DII_D( stdlib_base_dists_discrete_uniform_cdf ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/main.c new file mode 100644 index 000000000000..ef57eea341e4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/src/main.c @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/cdf.h" +#include "stdlib/math/base/special/floor.h" +#include "stdlib/math/base/assert/is_nan.h" +#include + +/** +* Evaluates the cumulative distribution function (CDF) for a discrete uniform distribution with minimum support `a` and maximum support `b` at a value `x`. +* +* @param x input value +* @param a minimum support +* @param b maximum support +* @return evaluated CDF +* +* @example +* double y = stdlib_base_dists_discrete_uniform_cdf( 9.0, 0, 10 ); +* // returns ~0.909 +*/ +double stdlib_base_dists_discrete_uniform_cdf( const double x, const int32_t a, const int32_t b ) { + if ( + stdlib_base_is_nan( x ) || + a > b + ) { + return 0.0/0.0; // NaN + } + if ( x < a ) { + return 0.0; + } + if ( x >= b ) { + return 1.0; + } + return ( stdlib_base_floor( x ) - a + 1.0 ) / ( b - a + 1.0 ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/test/test.native.js new file mode 100644 index 000000000000..eec3e728edd1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/cdf/test/test.native.js @@ -0,0 +1,159 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var smallRange = require( './fixtures/julia/small_range.json' ); +var mediumRange = require( './fixtures/julia/medium_range.json' ); +var largeRange = require( './fixtures/julia/large_range.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `Infinity` for `x` and a valid `a` and `b`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 2, 4 ); + t.equal( y, 1.0, 'returns 1' ); + t.end(); +}); + +tape( 'if provided `-Infinity` for `x` and a valid `a` and `b`, the function returns `0`', opts, function test( t ) { + var y = cdf( NINF, 2, 4 ); + t.equal( y, 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 0.0, 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = cdf( 0.0, -2, -3 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given a small range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var y; + var i; + + expected = smallRange.expected; + x = smallRange.x; + a = smallRange.a; + b = smallRange.b; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given a medium range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var y; + var i; + + expected = mediumRange.expected; + x = mediumRange.x; + a = mediumRange.a; + b = mediumRange.b; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given a large range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var y; + var i; + + expected = largeRange.expected; + x = largeRange.x; + a = largeRange.a; + b = largeRange.b; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/README.md index 13bc4c40c93c..a98dfd4bf35d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/README.md @@ -141,6 +141,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/entropy.h" +``` + +#### stdlib_base_dists_discrete_uniform_entropy( a, b ) + +Returns the [entropy][entropy] of a [discrete uniform][discrete-uniform-distribution] distribution with minimum support `a` and maximum support `b` (in [nats][nats]). + +```c +double out = stdlib_base_dists_discrete_uniform_entropy( 0, 1 ); +// returns ~0.693 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_entropy( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/entropy.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_entropy( a, b ); + printf( "a: %d, b: %d, H(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.js index f281e673e7ad..5fb69265eb29 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var entropy = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = entropy( min, max ); + y = entropy( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..733912e43b12 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( entropy instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = entropy( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/c/benchmark.c new file mode 100644 index 000000000000..765b6f4983cd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/entropy.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-entropy" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_entropy( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/examples/c/example.c new file mode 100644 index 000000000000..a7ce00d7088d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/entropy.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( a, a+10.0 ) ); + y = stdlib_base_dists_discrete_uniform_entropy( a, b ); + printf( "a: %d, b: %d, H(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the entropy of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_entropy( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_ENTROPY_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/lib/native.js new file mode 100644 index 000000000000..3027f64f8ef5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the entropy of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {number} entropy +* +* @example +* var v = entropy( 0, 1 ); +* // returns ~0.693 +* +* @example +* var v = entropy( 4, 12 ); +* // returns ~2.197 +* +* @example +* var v = entropy( -4, 4 ); +* // returns ~2.197 +*/ +function entropy( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = entropy; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/manifest.json new file mode 100644 index 000000000000..ef70a8c35eaf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/manifest.json @@ -0,0 +1,78 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/special/ln" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/ln" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/ln" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/package.json index a688bec71679..e4478bd91b9a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/addon.c new file mode 100644 index 000000000000..5fc40f5afb8e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/entropy.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_entropy ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/main.c new file mode 100644 index 000000000000..40ea48887090 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/src/main.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/entropy.h" +#include "stdlib/math/base/special/ln.h" +#include + +/** +* Returns the entropy of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return entropy +* +* @example +* double y = stdlib_base_dists_discrete_uniform_entropy( 0, 1 ); +* // returns ~0.693 +*/ +double stdlib_base_dists_discrete_uniform_entropy( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + return stdlib_base_ln( b - a + 1 ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/test/test.native.js new file mode 100644 index 000000000000..45080c0cf20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/entropy/test/test.native.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( entropy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof entropy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = entropy( 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the entropy of a discrete uniform distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = entropy( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/README.md index fed3209c1f41..b63092806fa6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/README.md @@ -141,6 +141,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/kurtosis.h" +``` + +#### stdlib_base_dists_discrete_uniform_kurtosis( a, b ) + +Returns the [excess kurtosis][kurtosis] of a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_kurtosis( 0, 1 ); +// returns -2.0 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_kurtosis( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/kurtosis.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_kurtosis( a, b ); + printf( "a: %d, b: %d, Kurt(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.js index 9210007c1c11..8216a02316c7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var kurtosis = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = kurtosis( min, max ); + y = kurtosis( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.native.js new file mode 100644 index 000000000000..a7d1bdbd67c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = kurtosis( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/c/benchmark.c new file mode 100644 index 000000000000..4c57d73c5937 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/kurtosis.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-kurtosis" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_kurtosis( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/examples/c/example.c new file mode 100644 index 000000000000..f65fe01c99d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/kurtosis.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_kurtosis( a, b ); + printf( "a: %d, b: %d, Kurt(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the excess kurtosis of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_kurtosis( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_KURTOSIS_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/lib/native.js new file mode 100644 index 000000000000..0a29d0ae29d6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the excess kurtosis of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {number} excess kurtosis +* +* @example +* var v = kurtosis( 0, 1 ); +* // returns -2.0 +* +* @example +* var v = kurtosis( 4, 12 ); +* // returns ~-1.23 +* +* @example +* var v = kurtosis( -4, 4 ); +* // returns ~-1.23 +*/ +function kurtosis( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = kurtosis; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/manifest.json new file mode 100644 index 000000000000..e9eadda54200 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/manifest.json @@ -0,0 +1,78 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/special/pow" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/pow" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/pow" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/package.json index 5d1c19e6c417..82bc289b1a4a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/addon.c new file mode 100644 index 000000000000..d3b90204f27f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/kurtosis.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_kurtosis ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/main.c new file mode 100644 index 000000000000..d1eb532b1a32 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/src/main.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/kurtosis.h" +#include "stdlib/math/base/special/pow.h" +#include + +/** +* Returns the excess kurtosis of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return excess kurtosis +* +* @example +* double y = stdlib_base_dists_discrete_uniform_kurtosis( 0, 1 ); +* // returns -2.0 +*/ +double stdlib_base_dists_discrete_uniform_kurtosis( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + const double n2 = stdlib_base_pow( b - a + 1.0, 2.0 ); + return -1.2 * ( n2 + 1.0 ) / ( n2 - 1.0 ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/test/test.native.js new file mode 100644 index 000000000000..0b3cefa3f1f9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/kurtosis/test/test.native.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof kurtosis, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = kurtosis( 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the excess kurtosis of a discrete uniform distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = kurtosis( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/README.md index fed1633787de..01b3d5990143 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/README.md @@ -140,6 +140,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/mean.h" +``` + +#### stdlib_base_dists_discrete_uniform_mean( a, b ) + +Returns the [expected value][expected-value] of a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_mean( 0, 1 ); +// returns 0.5 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_mean( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/mean.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_mean( a, b ); + printf( "a: %d, b: %d, E(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.js index 25bd72631f29..6b0589d36de7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var mean = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = mean( min, max ); + y = mean( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.native.js new file mode 100644 index 000000000000..ac276aff4d0d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mean( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/c/benchmark.c new file mode 100644 index 000000000000..0aac9937ee1d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mean.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-mean" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_mean( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/examples/c/example.c new file mode 100644 index 000000000000..3a499228644b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mean.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_mean( a, b ); + printf( "a: %d, b: %d, E(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the expected value of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_mean( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_MEAN_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/lib/native.js new file mode 100644 index 000000000000..5de303bf50ce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the expected value of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {number} expected value +* +* @example +* var v = mean( 0, 1 ); +* // returns 0.5 +* +* @example +* var v = mean( -4, 4 ); +* // returns 0.0 +* +* @example +* var v = mean( 0, 10 ); +* // returns 5.0 +*/ +function mean( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = mean; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/manifest.json new file mode 100644 index 000000000000..bf0302f6cdbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/manifest.json @@ -0,0 +1,75 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/package.json index fbf11ce697ec..0ab80ab09588 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/addon.c new file mode 100644 index 000000000000..161850d98dda --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mean.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_mean ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/main.c new file mode 100644 index 000000000000..5e496e02fbf8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/src/main.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mean.h" +#include + +/** +* Returns the expected value of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return expected value +* +* @example +* double y = stdlib_base_dists_discrete_uniform_mean( 0, 1 ); +* // returns 0.5 +*/ +double stdlib_base_dists_discrete_uniform_mean( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + return ( a + b ) / 2.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/test/test.native.js new file mode 100644 index 000000000000..c7419534abe6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mean/test/test.native.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mean, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = mean( 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the mean of a discrete uniform distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = mean( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/README.md index 60ef0b1888c3..56a3dcda93c5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/README.md @@ -140,6 +140,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/median.h" +``` + +#### stdlib_base_dists_discrete_uniform_median( a, b ) + +Returns the [median][median] of a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_median( 0, 1 ); +// returns 0.5 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_median( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/median.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_median( a, b ); + printf( "a: %d, b: %d, Median(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.js index fd1ba46bfe21..cb0a4108330c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var median = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = median( min, max ); + y = median( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.native.js new file mode 100644 index 000000000000..1e2dfe2fade1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var median = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( median instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = median( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/c/benchmark.c new file mode 100644 index 000000000000..cede89df9e4a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/median.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-median" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_median( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/examples/c/example.c new file mode 100644 index 000000000000..8b45d64ab682 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/median.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_median( a, b ); + printf( "a: %d, b: %d, Median(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the median of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_median( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_MEDIAN_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/lib/native.js new file mode 100644 index 000000000000..90ac30635ec1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the median of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {number} median +* +* @example +* var v = median( 0, 1 ); +* // returns 0.5 +* +* @example +* var v = median( -4, 4 ); +* // returns 0.0 +* +* @example +* var v = median( 0, 10 ); +* // returns 5.0 +*/ +function median( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = median; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/manifest.json new file mode 100644 index 000000000000..bf0302f6cdbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/manifest.json @@ -0,0 +1,75 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/package.json index 9ba391415de3..6b19329ea224 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/addon.c new file mode 100644 index 000000000000..776c87b1dd57 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/median.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_median ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/main.c new file mode 100644 index 000000000000..e381d91169fe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/src/main.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/median.h" +#include + +/** +* Returns the median of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return median +* +* @example +* double y = stdlib_base_dists_discrete_uniform_median( 0, 1 ); +* // returns 0.5 +*/ +double stdlib_base_dists_discrete_uniform_median( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + return ( a + b ) / 2.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/test/test.native.js new file mode 100644 index 000000000000..cef893a5baaa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/median/test/test.native.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var median = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( median instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof median, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = median( 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the median of a discrete uniform distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = median( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/README.md index 3de8821c519d..bcc9fcdb102c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/README.md @@ -158,6 +158,104 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/mgf.h" +``` + +#### stdlib_base_dists_discrete_uniform_mgf( t, a, b ) + +Evaluates the [moment-generating function][mgf] (MGF) for a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_mgf( 2.0, 0, 4 ); +// returns ~689.475 +``` + +The function accepts the following arguments: + +- **t**: `[in] double` input value. +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_mgf( const double t, const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/mgf.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double t; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + t = random_uniform( -10.0, 10.0 ); + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_mgf( t, a, b ); + printf( "t: %lf, a: %d, b: %d, M_X(t;a,b): %lf\n", t, a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.js index 416ab31d7e03..7559830843b7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,16 +34,24 @@ var mgf = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var t; var y; var i; + len = 100; + t = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = ( randu()*4.0 ) - 2.0; + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - t = ( randu() * 20.0 ) - 10.0; - min = round( ( randu() * 20.0 ) - 20.0 ); - max = round( min + ( randu() * 40.0 ) ); - y = mgf( t, min, max ); + y = mgf( t[ i % len ], min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..a84608b86655 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mgf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mgf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var t; + var y; + var i; + + len = 100; + t = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + t[ i ] = ( randu()*4.0 ) - 2.0; + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mgf( t[ i % len ], min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..42e35986303e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/benchmark/c/benchmark.c @@ -0,0 +1,144 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mgf.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-mgf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double t[ 100 ]; + double y; + double tc; + int i; + + for ( i = 0; i < 100; i++ ) { + t[ i ] = random_uniform( -2.0, 2.0 ); + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + tc = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_mgf( t[ i%100 ] ,a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - tc; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/examples/c/example.c new file mode 100644 index 000000000000..de933025f12a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mgf.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double t; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + t = random_uniform( -2.0, 2.0 ); + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_mgf( t, a, b ); + printf( "t: %lf, a: %d, b: %d, M_X(t;a,b): %lf\n", t, a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the moment-generating function (MGF) for a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_mgf( const double t, const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_MGF_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/lib/native.js new file mode 100644 index 000000000000..8ad17280a586 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/lib/native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the moment-generating function (MGF) of a discrete uniform distribution with minimum support `a` and maximum support `b` at a value `t`. +* +* @private +* @param {number} t - input value +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {number} evaluated MGF +* +* @example +* var y = mgf( 2.0, 0, 4 ); +* // returns ~689.475 +* +* @example +* var y = mgf( -0.2, 0, 4 ); +* // returns ~0.697 +* +* @example +* var y = mgf( 2.0, 0, 1 ); +* // returns ~4.195 +* +* @example +* var y = mgf( 0.5, 3, 3 ); +* // returns ~4.482 +* +* @example +* var y = mgf( 0.5, 3, 2 ); +* // returns NaN +* +* @example +* var y = mgf( NaN, 0, 1 ); +* // returns NaN +*/ +function mgf( t, a, b ) { + return addon( t, a, b ); +} + + +// EXPORTS // + +module.exports = mgf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/manifest.json new file mode 100644 index 000000000000..de533e5b6a36 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/manifest.json @@ -0,0 +1,84 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/ternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/expm1" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/expm1" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/expm1" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/package.json index ae9f31290c90..6810d1260499 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/addon.c new file mode 100644 index 000000000000..04a8024e89cb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mgf.h" +#include "stdlib/math/base/napi/ternary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_DII_D( stdlib_base_dists_discrete_uniform_mgf ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/main.c new file mode 100644 index 000000000000..3a12dc1ad554 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/src/main.c @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/mgf.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/expm1.h" +#include "stdlib/math/base/special/exp.h" +#include + +/** +* Evaluates the moment-generating function (MGF) of a discrete uniform distribution with minimum support `a` and maximum support `b` at a value `t`. +* +* @param t input value +* @param a minimum support +* @param b maximum support +* @return evaluated MGF +* +* @example +* double y = stdlib_base_dists_discrete_uniform_mgf( 2.0, 0, 4 ); +* // returns ~689.475 +*/ +double stdlib_base_dists_discrete_uniform_mgf( const double t, const int32_t a, const int32_t b ) { + if ( + stdlib_base_is_nan( t ) || + a > b + ) { + return 0.0/0.0; // NaN + } + if ( t == 0.0 ) { + return 1.0; + } + double ret = stdlib_base_exp( t*a ) * stdlib_base_expm1( t * ( b - a + 1.0 ) ); + ret /= stdlib_base_expm1( t ) * ( b - a + 1.0 ); + return ret; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/test/test.native.js new file mode 100644 index 000000000000..18492a589d9a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/mgf/test/test.native.js @@ -0,0 +1,170 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var smallRange = require( './fixtures/julia/small_range.json' ); +var mediumRange = require( './fixtures/julia/medium_range.json' ); +var largeRange = require( './fixtures/julia/large_range.json' ); + + +// VARIABLES // + +var mgf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mgf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mgf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = mgf( NaN, 0, 1 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = mgf( 2.0, 3.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided valid parameters, the function returns `1` for `t = 0`', opts, function test( t ) { + var y; + + y = mgf( 0.0, 2, 4 ); + t.equal( y, 1.0, 'returns 1' ); + + y = mgf( 0.0, 1, 2 ); + t.equal( y, 1.0, 'returns 1' ); + + y = mgf( 0.0, -4, 4 ); + t.equal( y, 1.0, 'returns 1' ); + + t.end(); +}); + +tape( 'the function evaluates the MGF for `x` given a small range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var y; + var i; + + expected = smallRange.expected; + x = smallRange.x; + a = smallRange.a; + b = smallRange.b; + for ( i = 0; i < x.length; i++ ) { + y = mgf( x[i], a[i], b[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); + +tape( 'the function evaluates the MGF for `x` given a medium range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var y; + var i; + + expected = mediumRange.expected; + x = mediumRange.x; + a = mediumRange.a; + b = mediumRange.b; + for ( i = 0; i < x.length; i++ ) { + y = mgf( x[i], a[i], b[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); + +tape( 'the function evaluates the MGF for `x` given a large range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var y; + var i; + + expected = largeRange.expected; + x = largeRange.x; + a = largeRange.a; + b = largeRange.b; + for ( i = 0; i < x.length; i++ ) { + y = mgf( x[i], a[i], b[i] ); + if ( expected[i] !== null ) { + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/README.md index 1eefe6d4df60..9a272f5205eb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/README.md @@ -139,6 +139,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/skewness.h" +``` + +#### stdlib_base_dists_discrete_uniform_skewness( a, b ) + +Returns the [skewness][skewness] of a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_skewness( 0, 1 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_skewness( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/skewness.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_skewness( a, b ); + printf( "a: %d, b: %d, skew(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.js index 2a9f4356e988..22493996b1d1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var skewness = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = skewness( min, max ); + y = skewness( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..4c65bf7ad7b0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..24af542d86d9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/skewness.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_skewness( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/examples/c/example.c new file mode 100644 index 000000000000..d2c5532882cd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/skewness.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_skewness( a, b ); + printf( "a: %d, b: %d, skew(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the skewness of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_skewness( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_SKEWNESS_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/lib/native.js new file mode 100644 index 000000000000..e24ea007bc8d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the skewness of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {number} skewness +* +* @example +* var v = skewness( 0, 1 ); +* // returns 0.0 +* +* @example +* var v = skewness( -4, 4 ); +* // returns 0.0 +* +* @example +* var v = skewness( 0, 10 ); +* // returns 0.0 +*/ +function skewness( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = skewness; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/manifest.json new file mode 100644 index 000000000000..bf0302f6cdbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/manifest.json @@ -0,0 +1,75 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/package.json index 6a5638a1c92b..90fd5dfd4fa4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/addon.c new file mode 100644 index 000000000000..ee8c02775f19 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/skewness.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_skewness ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/main.c new file mode 100644 index 000000000000..8d34de4f906d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/src/main.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/skewness.h" +#include + +/** +* Returns the skewness of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return skewness +* +* @example +* double y = stdlib_base_dists_discrete_uniform_skewness( 0, 1 ); +* // returns 0.0 +*/ +double stdlib_base_dists_discrete_uniform_skewness( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + return 0.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/test/test.native.js new file mode 100644 index 000000000000..117283830ecc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/skewness/test/test.native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var round = require( '@stdlib/math/base/special/round' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof skewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = skewness( 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns `0.0` as the skewness of a discrete uniform distribution ', opts, function test( t ) { + var a; + var b; + var i; + var v; + + for ( i = 0; i < 10; i++ ) { + a = round( randu()*10.0 ); + b = round( ( randu()*10.0 ) + a ); + v = skewness( a, b ); + t.equal( v, 0.0, 'returns 0.0' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/README.md index 6e0c1c7a11e2..368e895fdb53 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/README.md @@ -141,6 +141,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/stdev.h" +``` + +#### stdlib_base_dists_discrete_uniform_stdev( a, b ) + +Returns the [standard deviation][standard-deviation] of a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_stdev( 0, 1 ); +// returns ~0.5 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_stdev( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/stdev.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_stdev( a, b ); + printf( "a: %d, b: %d, SD(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.js index 104a844208fe..cc4f3a08c793 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var stdev = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = stdev( min, max ); + y = stdev( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d34fd77f5d55 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..eeb577dd2386 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/stdev.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_stdev( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/examples/c/example.c new file mode 100644 index 000000000000..6b483950c363 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/stdev.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_stdev( a, b ); + printf( "a: %d, b: %d, SD(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the standard deviation of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_stdev( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_STDEV_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/lib/native.js new file mode 100644 index 000000000000..7c1d4cffaa32 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the standard deviation of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {PositiveNumber} standard deviation +* +* @example +* var v = stdev( 0, 1 ); +* // returns ~0.5 +* +* @example +* var v = stdev( 4, 12 ); +* // returns ~2.582 +* +* @example +* var v = stdev( -4, 4 ); +* // returns ~2.582 +*/ +function stdev( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = stdev; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/manifest.json new file mode 100644 index 000000000000..f5de3aa14a38 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/manifest.json @@ -0,0 +1,81 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/sqrt" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/sqrt" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/sqrt" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/package.json index f06010702218..9aeaaeb7aee1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/addon.c new file mode 100644 index 000000000000..e2c35e4451c1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/stdev.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_stdev ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/main.c new file mode 100644 index 000000000000..e38d8c2db338 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/src/main.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/stdev.h" +#include "stdlib/math/base/special/pow.h" +#include "stdlib/math/base/special/sqrt.h" +#include + +/** +* Returns the standard deviation of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return standard deviation +* +* @example +* double y = stdlib_base_dists_discrete_uniform_stdev( 0, 1 ); +* // returns ~0.5 +*/ +double stdlib_base_dists_discrete_uniform_stdev( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + return stdlib_base_sqrt( 1.0/12.0 ) * stdlib_base_sqrt( ( stdlib_base_pow( b-a+1, 2.0 ) - 1.0 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/test/test.native.js new file mode 100644 index 000000000000..2eebadc64ad3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/stdev/test/test.native.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof stdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = stdev( 3, 2 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the stdev of a discrete uniform distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = stdev( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/README.md index 2a29cb6ace89..d96e35cf7c41 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/README.md @@ -141,6 +141,101 @@ for ( i = 0; i < 10; i++ ) { + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/discrete-uniform/variance.h" +``` + +#### stdlib_base_dists_discrete_uniform_variance( a, b ) + +Returns the [variance][variance] of a [discrete uniform][discrete-uniform-distribution] distribution with parameters `a` (minimum support) and `b` (maximum support). + +```c +double out = stdlib_base_dists_discrete_uniform_variance( 0, 1 ); +// returns ~0.25 +``` + +The function accepts the following arguments: + +- **a**: `[in] int32_t` minimum support. +- **b**: `[in] int32_t` maximum support. + +```c +double stdlib_base_dists_discrete_uniform_variance( const int32_t a, const int32_t b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/discrete-uniform/variance.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_variance( a, b ); + printf( "a: %d, b: %d, Var(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.js index 9d7aa3275570..dea68637c711 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -33,14 +34,21 @@ var variance = require( './../lib' ); bench( pkg, function benchmark( b ) { var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu() * 10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = round( randu()*10.0 ); - max = round( ( randu()*10.0 ) + min ); - y = variance( min, max ); + y = variance( min[ i % len ], max[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.native.js new file mode 100644 index 000000000000..3c5bcccd88bf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var round = require( '@stdlib/math/base/special/round' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = round( randu()*10.0 ); + max[ i ] = round( randu() * 10.0 ) + min[ i ]; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( min[ i % len ], max[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/c/benchmark.c new file mode 100644 index 000000000000..80a6ade0142f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/variance.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include +#include +#include +#include + +#define NAME "discrete-uniform-variance" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + int32_t a[ 100 ]; + int32_t b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b[ i ] = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a[ i ]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_discrete_uniform_variance( a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/examples/c/example.c new file mode 100644 index 000000000000..482b1af33075 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/variance.h" +#include "stdlib/math/base/special/round.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + int32_t a; + int32_t b; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + a = stdlib_base_round( random_uniform( 0.0, 10.0 ) ); + b = stdlib_base_round( random_uniform( 0.0, 10.0 ) ) + a; + y = stdlib_base_dists_discrete_uniform_variance( a, b ); + printf( "a: %d, b: %d, Var(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Returns the variance of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +*/ +double stdlib_base_dists_discrete_uniform_variance( const int32_t a, const int32_t b ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_BASE_DISTS_DISCRETE_UNIFORM_VARIANCE_H diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/lib/native.js new file mode 100644 index 000000000000..6b67eead5380 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/lib/native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Returns the variance of a discrete uniform distribution. +* +* @private +* @param {integer} a - minimum support +* @param {integer} b - maximum support +* @returns {PositiveNumber} variance +* +* @example +* var v = variance( 0, 1 ); +* // returns ~0.25 +* +* @example +* var v = variance( 4, 12 ); +* // returns ~6.667 +* +* @example +* var v = variance( -4, 4 ); +* // returns ~6.667 +*/ +function variance( a, b ) { + return addon( a, b ); +} + + +// EXPORTS // + +module.exports = variance; diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/manifest.json new file mode 100644 index 000000000000..e9eadda54200 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/manifest.json @@ -0,0 +1,78 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/binary", + "@stdlib/math/base/special/pow" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/pow" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/round", + "@stdlib/math/base/special/pow" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/package.json b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/package.json index 5368bb8269fc..b8ec9a2504b5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/Makefile new file mode 100644 index 000000000000..7733b6180cb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/addon.c new file mode 100644 index 000000000000..544c28ca70d8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/addon.c @@ -0,0 +1,23 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/variance.h" +#include "stdlib/math/base/napi/binary.h" + +// cppcheck-suppress shadowFunction +STDLIB_MATH_BASE_NAPI_MODULE_II_D( stdlib_base_dists_discrete_uniform_variance ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/main.c new file mode 100644 index 000000000000..521367e1c9eb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/src/main.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/discrete-uniform/variance.h" +#include "stdlib/math/base/special/pow.h" +#include + +/** +* Returns the variance of a discrete uniform distribution with parameters `a` (minimum support) and `b` (maximum support). +* +* @param a minimum support +* @param b maximum support +* @return variance +* +* @example +* double y = stdlib_base_dists_discrete_uniform_variance( 0, 1 ); +* // returns ~0.25 +*/ +double stdlib_base_dists_discrete_uniform_variance( const int32_t a, const int32_t b ) { + if ( a > b ) { + return 0.0/0.0; // NaN + } + return ( stdlib_base_pow( b-a+1, 2.0 ) - 1.0 ) / 12.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/test/test.native.js new file mode 100644 index 000000000000..18ca3bff1cf4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/variance/test/test.native.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof variance, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `a > b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = variance( 3.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the variance of a discrete uniform distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var a; + var b; + var i; + var y; + + expected = data.expected; + a = data.a; + b = data.b; + for ( i = 0; i < expected.length; i++ ) { + y = variance( a[i], b[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'a: '+a[i]+', b: '+b[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/exponential/docs/types/index.d.ts index 14d9c9d6c900..93194ba7b0bf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/docs/types/index.d.ts @@ -63,14 +63,14 @@ interface Namespace { Exponential: typeof Exponential; /** - * Returns the entropy of an exponential distribution. + * Returns the differential entropy of an exponential distribution. * * ## Notes * * - If provided a negative value for `λ`, the function returns `NaN`. * * @param lambda - rate parameter - * @returns entropy + * @returns differential entropy * * @example * var v = ns.entropy( 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/docs/types/index.d.ts index d8f3dc311aea..ae5927a1737e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/docs/types/index.d.ts @@ -19,14 +19,14 @@ // TypeScript Version: 4.1 /** -* Returns the entropy of an exponential distribution. +* Returns the differential entropy of an exponential distribution. * * ## Notes * * - If provided a negative value for `λ`, the function returns `NaN`. * * @param lambda - rate parameter -* @returns entropy +* @returns differential entropy * * @example * var v = entropy( 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/lib/main.js index cd582aa391e5..6c5315280919 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/entropy/lib/main.js @@ -27,10 +27,10 @@ var ln = require( '@stdlib/math/base/special/ln' ); // MAIN // /** -* Returns the entropy of an exponential distribution. +* Returns the differential entropy of an exponential distribution. * * @param {NonNegativeNumber} lambda - rate parameter -* @returns {number} entropy +* @returns {number} differential entropy * * @example * var v = entropy( 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/benchmark/c/benchmark.c index 7959e83058bb..cea6f683bad4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/include/stdlib/stats/base/dists/exponential/kurtosis.h b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/include/stdlib/stats/base/dists/exponential/kurtosis.h index c7874c7c36fa..ba4537c25f71 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/include/stdlib/stats/base/dists/exponential/kurtosis.h +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/include/stdlib/stats/base/dists/exponential/kurtosis.h @@ -27,7 +27,7 @@ extern "C" { #endif /** -* Returns the kurtosis of an exponential distribution. +* Returns the excess kurtosis of an exponential distribution. */ double stdlib_base_dists_exponential_kurtosis( const double lambda ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/lib/native.js index 5eb4b4e2f5d8..1dba144158a8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/lib/native.js @@ -26,11 +26,11 @@ var addon = require( './../src/addon.node' ); // MAIN // /** -* Returns the kurtosis of an exponential distribution. +* Returns the excess kurtosis of an exponential distribution. * * @private * @param {NonNegativeNumber} lambda - rate parameter -* @returns {NonNegativeNumber} kurtosis +* @returns {NonNegativeNumber} excess kurtosis * * @example * var v = kurtosis( 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/src/main.c index 83f2a3046338..dd6a8233efbc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/kurtosis/src/main.c @@ -20,10 +20,10 @@ #include "stdlib/math/base/assert/is_nan.h" /** -* Returns the kurtosis of an exponential distribution. +* Returns the excess kurtosis of an exponential distribution. * * @param lambda rate parameter -* @return kurtosis +* @return excess kurtosis * * @example * double y = stdlib_base_exponential_kurtosis( 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/README.md index 2ddf3b182335..971ddf089399 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/README.md @@ -225,7 +225,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { x = random_uniform( 0.0, 100.0 ); - lambda = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); y = stdlib_base_dists_exponential_logcdf( x, lambda ); printf( "x: %lf, λ: %lf, ln(F(x;λ)): %lf\n", x, lambda, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/benchmark/c/benchmark.c index 6cfe01688270..87e86a1fe11d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/benchmark/c/benchmark.c @@ -102,7 +102,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { x[ i ] = random_uniform( 0.0, 100.0 ); - lambda[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/examples/c/example.c index 2a8efde3b952..5158bd42228f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/examples/c/example.c @@ -34,7 +34,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { x = random_uniform( 0.0, 100.0 ); - lambda = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); y = stdlib_base_dists_exponential_logcdf( x, lambda ); printf( "x: %lf, λ: %lf, ln(F(x;λ)): %lf\n", x, lambda, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/mean/benchmark/c/benchmark.c index 2892d330d1da..9032e0ff3c18 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/mean/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/mean/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/median/benchmark/c/benchmark.c index cfb14c0ef306..2cddc02366df 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/median/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/median/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/mode/benchmark/c/benchmark.c index 4a253338503f..a74ac0c2b5cf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/mode/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/mode/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/skewness/benchmark/c/benchmark.c index 8b90a1577ee4..d4b67793dd04 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/skewness/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/skewness/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/exponential/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/exponential/stdev/benchmark/c/benchmark.c index 8dff815e91a8..0d75bb7f4c05 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/exponential/stdev/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/exponential/stdev/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/entropy/README.md index e25541511c28..9da7bd7976c0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/entropy/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_entropy( d1, d2 ); printf( "d1: %lf, d2: %lf, h(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/entropy/benchmark/c/benchmark.c index 791825002c1f..7b48533e0948 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/entropy/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/entropy/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/entropy/examples/c/example.c index ef7cc1632b2d..5a0269d2efe9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/entropy/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/entropy/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_entropy( d1, d2 ); printf( "d1: %lf, d2: %lf, h(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/README.md index 395613b5b1aa..c3529a7bff1b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/README.md @@ -227,8 +227,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_kurtosis( d1, d2 ); printf( "d1: %lf, d2: %lf, Kurt(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/benchmark/c/benchmark.c index b4250000514d..2583ff47ec89 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + 8.0 + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/examples/c/example.c index 79e743afe4f2..a97ab54920ec 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_kurtosis( d1, d2 ); printf( "d1: %lf, d2: %lf, Kurt(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/main.js index 902e0808d05e..871ee2e2b8d4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/main.js @@ -30,7 +30,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); * * @param {PositiveNumber} d1 - numerator degrees of freedom * @param {PositiveNumber} d2 - denominator degrees of freedom -* @returns {PositiveNumber} kurtosis +* @returns {PositiveNumber} excess kurtosis * * @example * var v = kurtosis( 3.0, 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/native.js index e0e6264f040d..8203ef5e6b30 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/f/kurtosis/lib/native.js @@ -31,7 +31,7 @@ var addon = require( './../src/addon.node' ); * @private * @param {PositiveNumber} d1 - numerator degrees of freedom * @param {PositiveNumber} d2 - denominator degrees of freedom -* @returns {PositiveNumber} kurtosis +* @returns {PositiveNumber} excess kurtosis * * @example * var v = kurtosis( 3.0, 9.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/mean/README.md index c4e430f5e919..cc2a0ecf5464 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/mean/README.md @@ -222,8 +222,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_mean( d1, d2 ); printf( "d1: %lf, d2: %lf, E(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/mean/benchmark/c/benchmark.c index 599e35a40911..77edeb8341c9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/mean/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/mean/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + 2.0 + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2[ i ] = random_uniform( 2.0, 12.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/mean/examples/c/example.c index d071c2c01f8f..253c3067190a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/mean/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_mean( d1, d2 ); printf( "d1: %lf, d2: %lf, E(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/mode/README.md index 2247088f6a82..7ea469d4bc69 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/mode/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_mode( d1, d2 ); printf( "d1: %lf, d2: %lf, mode(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/mode/benchmark/c/benchmark.c index 9fbd3bf5ee3f..8ffd0d89edbe 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/mode/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/mode/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + 2.0 + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( 2.0, 12.0 ); + d2[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/mode/examples/c/example.c index 1b8528bd0916..c553ea58ae5f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/mode/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/mode/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_f_mode( d1, d2 ); printf( "d1: %lf, d2: %lf, mode(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/README.md index f0546857105e..d80806d7d5ff 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/README.md @@ -227,8 +227,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_skewness( d1, d2 ); printf( "d1: %lf, d2: %lf, skew(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/benchmark/c/benchmark.c index 2a63d6af6059..1d666cc1d41d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + 6.0 + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2[ i ] = random_uniform( 6.0, 16.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/examples/c/example.c index 002939f24b05..fce48a6e8d5b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/skewness/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/skewness/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_skewness( d1, d2 ); printf( "d1: %lf, d2: %lf, skew(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/stdev/README.md index d9aca435a10f..4821f2ed0ef6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/stdev/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_stdev( d1, d2 ); printf( "d1: %lf, d2: %lf, SD(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/stdev/benchmark/c/benchmark.c index 66bc2d3ed8b5..64071f170d5f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/stdev/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/stdev/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + 4.0 + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2[ i ] = random_uniform( 4.0, 14.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/stdev/examples/c/example.c index 7d778f68e7fd..5619e1b761d2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/stdev/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/stdev/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_stdev( d1, d2 ); printf( "d1: %lf, d2: %lf, SD(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/f/variance/README.md index ed59ef81232c..4ddf17de2356 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/f/variance/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_variance( d1, d2 ); printf( "d1: %lf, d2: %lf, Var(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/f/variance/benchmark/c/benchmark.c index 15abd65d5aaa..d1b44eaf65d9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/variance/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/variance/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - d1[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2[ i ] = random_uniform( 0.0, 10.0 ) + 4.0 + STDLIB_CONSTANT_FLOAT64_EPS; + d1[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2[ i ] = random_uniform( 4.0, 14.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/f/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/f/variance/examples/c/example.c index 4e6e4c13cb53..6bf9aab3d859 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/f/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/f/variance/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - d1 = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - d2 = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + d1 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + d2 = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_f_variance( d1, d2 ); printf( "d1: %lf, d2: %lf, Var(X;d1,d2): %lf\n", d1, d2, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md index 767da2f6217f..aaa43e70f76e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/README.md @@ -139,7 +139,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = entropy( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, h(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/benchmark/benchmark.js index 10d5f07a07b9..5b0223f8d128 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/benchmark/benchmark.js @@ -41,7 +41,7 @@ bench( pkg, function benchmark( b ) { for ( i = 0; i < b.iterations; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = entropy( alpha, s, m ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js index 5043bb11d343..5cffdad400eb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/entropy/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = entropy( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, h(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md index 360f2516210f..d37af810d260 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/README.md @@ -146,7 +146,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = kurtosis( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, Kurt(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/benchmark/benchmark.js index 706b7245ce07..3d601e03192d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/benchmark/benchmark.js @@ -41,7 +41,7 @@ bench( pkg, function benchmark( b ) { for ( i = 0; i < b.iterations; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = kurtosis( alpha, s, m ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js index 4e481442d686..8aaccb671497 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/kurtosis/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = kurtosis( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, Kurt(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md index d2eb64a802c6..462f52b27e79 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/README.md @@ -139,7 +139,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = mean( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, E(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/benchmark/benchmark.js index e7dbbb85b7d5..a5dcce74f8f1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/benchmark/benchmark.js @@ -41,7 +41,7 @@ bench( pkg, function benchmark( b ) { for ( i = 0; i < b.iterations; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = mean( alpha, s, m ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js index 7d534e6859f1..854f3546d4fb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mean/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = mean( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, E(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md index f9e3d61c71eb..0fd6eab1acb2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/README.md @@ -137,7 +137,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = median( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, Median(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/benchmark/benchmark.js index 338bcc934c77..dee7ea92b351 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/benchmark/benchmark.js @@ -41,7 +41,7 @@ bench( pkg, function benchmark( b ) { for ( i = 0; i < b.iterations; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = median( alpha, s, m ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js index 82c790051124..d744e31af374 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/median/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = median( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, Median(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md index 84e55a859785..8f311ff3e8c6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/README.md @@ -137,7 +137,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = mode( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, mode(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/benchmark/benchmark.js index 8be50abfffb0..20e79cc5c031 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/benchmark/benchmark.js @@ -41,7 +41,7 @@ bench( pkg, function benchmark( b ) { for ( i = 0; i < b.iterations; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = mode( alpha, s, m ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js index 9dc5065830b1..bbf6f3612b63 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/mode/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = mode( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, mode(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md index b5bdf1c27a02..0f4d3156f10c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/README.md @@ -146,7 +146,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = skewness( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, skew(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } @@ -156,13 +156,104 @@ for ( i = 0; i < 10; i++ ) { - + -
+* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/frechet/skewness.h" +``` + +#### stdlib_base_dists_frechet_skewness( alpha, s, m ) + +Returns the skewness for a Fréchet distribution with shape `alpha`, scale `s`, and location `m`. + +```c +double y = stdlib_base_frechet_skewness( 5.0, 2.0, 0.0 ); +// returns ~3.535 +``` + +The function accepts the following arguments: + +- **alpha**: `[in] double` shape parameter. +- **s**: `[in] double` scale parameter. +- **m**: `[in] double` location parameter. + +```c +double stdlib_base_dists_frechet_skewness( const double alpha, const double s, const double m ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/frechet/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double s; + double m; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m = random_uniform( -20.0, 20.0 ); + y = stdlib_base_dists_frechet_skewness( alpha, s, m ); + printf( "α: %.4lf, s: %.4lf, m: %.4lf, skew(X;α,s,m): %.4lf\n", alpha, s, m, y ); + } +} +``` + +
+ +
- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.js index 52d2d6442697..e6eb1fa296d0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,17 +33,25 @@ var skewness = require( './../lib' ); bench( pkg, function benchmark( b ) { var alpha; + var len; var m; var s; var y; var i; + len = 100; + alpha = new Float64Array( len ); + s = new Float64Array( len ); + m = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + alpha[ i ] = ( randu()*20.0 ) + EPS; + s[ i ] = ( randu()*20.0 ) + EPS; + m[ i ] = ( randu()*20.0 ) - 40.0; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; - y = skewness( alpha, s, m ); + y = skewness( alpha[ i % len ], s[ i % len ], m[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..1a32fb72d772 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/benchmark.native.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var alpha; + var len; + var s; + var m; + var y; + var i; + + len = 100; + alpha = new Float64Array( len ); + s = new Float64Array( len ); + m = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + alpha[ i ] = ( randu()*20.0 ) + EPS; + s[ i ] = ( randu()*20.0 ) + EPS; + m[ i ] = ( randu()*20.0 ) - 40.0; + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( alpha[ i % len ], s[ i % len ], m[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..13e5b74f97bb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/frechet/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "frechet-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double alpha[ 100 ]; + double s[ 100 ]; + double m[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m[ i ] = random_uniform( -20.0, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_frechet_skewness( alpha[ i%100 ], s[ i%100 ], m[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/c/example.c new file mode 100644 index 000000000000..86b52ad6a703 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/frechet/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double s; + double m; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m = random_uniform( -20.0, 20.0 ); + y = stdlib_base_dists_frechet_skewness( alpha, s, m ); + printf( "α: %.4lf, s: %.4lf, m: %.4lf, skew(X;α,s,m): %.4lf\n", alpha, s, m, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js index 90ce3103eea1..8df4f0a7ca3f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = skewness( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, skew(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' - + -
+* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/frechet/stdev.h" +``` + +#### stdlib_base_dists_frechet_stdev( alpha, s, m ) + +Returns the standard deviation for a Fréchet distribution with shape `alpha`, scale `s`, and location `m`. + +```c +double y = stdlib_base_frechet_stdev( 5.0, 2.0, 0.0 ); +// returns ~0.731 +``` + +The function accepts the following arguments: + +- **alpha**: `[in] double` shape parameter. +- **s**: `[in] double` scale parameter. +- **m**: `[in] double` location parameter. + +```c +double stdlib_base_dists_frechet_stdev( const double alpha, const double s, const double m ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/frechet/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double s; + double m; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m = random_uniform( -20.0, 20.0 ); + y = stdlib_base_dists_frechet_stdev( alpha, s, m ); + printf( "α: %.4lf, s: %.4lf, m: %.4lf, SD(X;α,s,m): %.4lf\n", alpha, s, m, y ); + } +} +``` + +
+ +
- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.js index 5a4c7b54e6ce..7e4953d4e9ed 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,17 +33,25 @@ var stdev = require( './../lib' ); bench( pkg, function benchmark( b ) { var alpha; + var len; var m; var s; var y; var i; + len = 100; + alpha = new Float64Array( len ); + s = new Float64Array( len ); + m = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + alpha[ i ] = ( randu()*20.0 ) + EPS; + s[ i ] = ( randu()*20.0 ) + EPS; + m[ i ] = ( randu()*20.0 ) - 40.0; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; - y = stdev( alpha, s, m ); + y = stdev( alpha[ i % len ], s[ i % len ], m[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..76c7bd50a440 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/benchmark.native.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var alpha; + var len; + var s; + var m; + var y; + var i; + + len = 100; + alpha = new Float64Array( len ); + s = new Float64Array( len ); + m = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + alpha[ i ] = ( randu()*20.0 ) + EPS; + s[ i ] = ( randu()*20.0 ) + EPS; + m[ i ] = ( randu()*20.0 ) - 40.0; + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( alpha[ i % len ], s[ i % len ], m[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..18ce6d7eec02 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/frechet/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "frechet-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double alpha[ 100 ]; + double s[ 100 ]; + double m[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m[ i ] = random_uniform( -20.0, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_frechet_stdev( alpha[ i%100 ], s[ i%100 ], m[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/c/example.c new file mode 100644 index 000000000000..b3607ce56d56 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/frechet/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double s; + double m; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m = random_uniform( -20.0, 20.0 ); + y = stdlib_base_dists_frechet_stdev( alpha, s, m ); + printf( "α: %.4lf, s: %.4lf, m: %.4lf, SD(X;α,s,m): %.4lf\n", alpha, s, m, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js index 7a02ba65d9b0..98590753689f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = stdev( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, SD(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' - + -
+* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/frechet/variance.h" +``` + +#### stdlib_base_dists_frechet_variance( alpha, s, m ) + +Returns the variance for a Fréchet distribution with shape `alpha`, scale `s`, and location `m`. + +```c +double y = stdlib_base_frechet_variance( 5.0, 2.0, 0.0 ); +// returns ~0.535 +``` + +The function accepts the following arguments: + +- **alpha**: `[in] double` shape parameter. +- **s**: `[in] double` scale parameter. +- **m**: `[in] double` location parameter. + +```c +double stdlib_base_dists_frechet_variance( const double alpha, const double s, const double m ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/frechet/variance.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double s; + double m; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m = random_uniform( -20.0, 20.0 ); + y = stdlib_base_dists_frechet_variance( alpha, s, m ); + printf( "α: %.4lf, s: %.4lf, m: %.4lf, Var(X;α,s,m): %.4lf\n", alpha, s, m, y ); + } +} +``` + +
+ +
- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.js index 7f329a2637d7..18f057adafa1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,17 +33,25 @@ var variance = require( './../lib' ); bench( pkg, function benchmark( b ) { var alpha; + var len; var m; var s; var y; var i; + len = 100; + alpha = new Float64Array( len ); + s = new Float64Array( len ); + m = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + alpha[ i ] = ( randu()*20.0 ) + EPS; + s[ i ] = ( randu()*20.0 ) + EPS; + m[ i ] = ( randu()*20.0 ) - 40.0; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - alpha = ( randu()*20.0 ) + EPS; - s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; - y = variance( alpha, s, m ); + y = variance( alpha[ i % len ], s[ i % len ], m[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.native.js new file mode 100644 index 000000000000..c2742f3a5426 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/benchmark.native.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var alpha; + var len; + var s; + var m; + var y; + var i; + + len = 100; + alpha = new Float64Array( len ); + s = new Float64Array( len ); + m = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + alpha[ i ] = ( randu()*20.0 ) + EPS; + s[ i ] = ( randu()*20.0 ) + EPS; + m[ i ] = ( randu()*20.0 ) - 40.0; + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( alpha[ i % len ], s[ i % len ], m[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/c/benchmark.c new file mode 100644 index 000000000000..5dca6f874d9a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/frechet/variance.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "frechet-variance" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double alpha[ 100 ]; + double s[ 100 ]; + double m[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m[ i ] = random_uniform( -20.0, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_frechet_variance( alpha[ i%100 ], s[ i%100 ], m[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/c/example.c new file mode 100644 index 000000000000..38710328f62f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/frechet/variance.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double s; + double m; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + m = random_uniform( -20.0, 20.0 ); + y = stdlib_base_dists_frechet_variance( alpha, s, m ); + printf( "α: %.4lf, s: %.4lf, m: %.4lf, Var(X;α,s,m): %.4lf\n", alpha, s, m, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js index 6e370b98dc2c..fa2d88537322 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/examples/index.js @@ -31,7 +31,7 @@ var i; for ( i = 0; i < 10; i++ ) { alpha = ( randu()*20.0 ) + EPS; s = ( randu()*20.0 ) + EPS; - m = ( randu()*20.0 ) - 40.0; + m = ( randu()*40.0 ) - 20.0; y = variance( alpha, s, m ); console.log( 'α: %d, s: %d, m: %d, Var(X;α,s,m): %d', alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/variance/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/geometric/entropy.h" +``` + +#### stdlib_base_dists_geometric_entropy( p ) + +Returns the entropy of a geometric distribution. + +```c +double out = stdlib_base_dists_geometric_entropy( 0.5 ); +// returns ~1.386 +``` + +The function accepts the following arguments: + +- **p**: `[in] double` success probability. + +```c +double stdlib_base_dists_geometric_entropy( const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/geometric/entropy.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_geometric_entropy( p ); + printf( "p: %lf, H(X;p): %lf\n", p, y ); + } +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js index 72181a16582a..2b3dc56001c4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js @@ -21,9 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var entropy = require( './../lib' ); @@ -31,14 +31,20 @@ var entropy = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = ( randu() * 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = ( randu()*1.0 ) + EPS; - y = entropy( p ); + y = entropy( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..69b57c0dc5a8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( entropy instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var p; + var y; + var i; + + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = ( randu() * 1.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = entropy( p[ i % 100 ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c new file mode 100644 index 000000000000..65fca8fabbbb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/geometric/entropy.h" +#include +#include +#include +#include +#include + +#define NAME "geometric-entropy" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double p[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + p[ i ] = random_uniform( 0.0, 1.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_geometric_entropy( p[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c new file mode 100644 index 000000000000..a80f5327b8b6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/geometric/entropy.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_geometric_entropy( p ); + printf( "p: %lf, H(X;p): %lf\n", p, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= 1.0 + ) { + return 0.0 / 0.0; // NaN + } + q = 1.0 - p; + return ( -( p * stdlib_base_ln( p ) ) - ( q * stdlib_base_ln( q ) ) ) / p; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js new file mode 100644 index 000000000000..04d328c09ce8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( entropy instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof entropy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `p`, the function returns `NaN`', opts, function test( t ) { + var k = entropy( NaN ); + t.equal( isnan( k ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a success probability `p` outside of `[0,1]`, the function returns `NaN`', opts, function test( t ) { + var k; + + k = entropy( -1.0 ); + t.equal( isnan( k ), true, 'returns NaN' ); + + k = entropy( 1.5 ); + t.equal( isnan( k ), true, 'returns NaN' ); + + k = entropy( NINF ); + t.equal( isnan( k ), true, 'returns NaN' ); + + k = entropy( PINF ); + t.equal( isnan( k ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the entropy of a geometric distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var i; + var p; + var y; + + expected = data.expected; + p = data.p; + for ( i = 0; i < expected.length; i++ ) { + y = entropy( p[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'p: '+p[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/kurtosis/lib/main.js index 2954b42d6637..81dec88f3284 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/kurtosis/lib/main.js @@ -29,7 +29,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); * Returns the excess kurtosis of a geometric distribution. * * @param {Probability} p - success probability -* @returns {PositiveNumber} kurtosis +* @returns {PositiveNumber} excess kurtosis * * @example * var v = kurtosis( 0.1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/README.md index fc6fe630c2bd..b36a01e96c7e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/README.md @@ -122,6 +122,94 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/geometric/mean.h" +``` + +#### stdlib_base_dists_geometric_mean( p ) + +Returns the [expected value][expected-value] of a [geometric][geometric-distribution] distribution with success probability `p`. + +```c +double out = stdlib_base_dists_geometric_mean( 0.5 ); +// returns 1.0 +``` + +The function accepts the following arguments: + +- **p**: `[in] double` success probability. + +```c +double stdlib_base_dists_geometric_mean( const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/geometric/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_geometric_mean( p ); + printf( "p: %lf, E(X;p): %lf\n", p, y ); + } +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.js index c821fc2593b7..a380e77c816b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,14 +32,20 @@ var mean = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = ( randu() * 1.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = ( randu()*1.0 ) + EPS; - y = mean( p ); + y = mean( p[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d6dc28067c48 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var p; + var y; + var i; + + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = ( randu() * 1.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mean( p[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/c/benchmark.c new file mode 100644 index 000000000000..2277ae5bc66d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/geometric/mean.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "geometric-mean" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double p[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + p[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 1.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_geometric_mean( p[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/examples/c/example.c new file mode 100644 index 000000000000..7a8ce18fd001 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/geometric/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_geometric_mean( p ); + printf( "p: %lf, E(X;p): %lf\n", p, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' 1.0 + ) { + return 0.0 / 0.0; + } + return ( 1.0 - p ) / p; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/test/test.native.js new file mode 100644 index 000000000000..33be2c3edfe0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/mean/test/test.native.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mean, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `p`, the function returns `NaN`', opts, function test( t ) { + var m = mean( NaN ); + t.equal( isnan( m ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a success probability `p` outside of `[0,1]`, the function returns `NaN`', opts, function test( t ) { + var m; + + m = mean( -1.0 ); + t.equal( isnan( m ), true, 'returns NaN' ); + + m = mean( 1.5 ); + t.equal( isnan( m ), true, 'returns NaN' ); + + m = mean( NINF ); + t.equal( isnan( m ), true, 'returns NaN' ); + + m = mean( PINF ); + t.equal( isnan( m ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the mean of a geometric distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var i; + var p; + var y; + + expected = data.expected; + p = data.p; + for ( i = 0; i < expected.length; i++ ) { + y = mean( p[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'p: '+p[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/factory.js index f8b171f62892..903ba1cfd7f7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/factory.js @@ -72,7 +72,7 @@ function factory( p ) { if ( r === 1.0 ) { return PINF; } - return max( 0.0, ceil( (ln(1.0-r) / log1p(-p)) - (1.0 + 1e-12) ) ); + return max( 0.0, ceil( ( ln(1.0-r)/log1p(-p) ) - ( 1.0+1.0e-12 ) ) ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/main.js index 89f250ea7c1b..3bba3a392db7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/quantile/lib/main.js @@ -83,7 +83,7 @@ function quantile( r, p ) { if ( r === 1.0 ) { return PINF; } - return max( 0.0, ceil( (ln(1.0-r) / log1p(-p))- ( 1 + 1e-12 ) ) ); + return max( 0.0, ceil( ( ln(1.0-r)/log1p(-p) )- ( 1.0+1.0e-12 ) ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/README.md index 3d9d73dc36ef..832271c3ea07 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/README.md @@ -122,6 +122,94 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/geometric/skewness.h" +``` + +#### stdlib_base_dists_geometric_skewness( p ) + +Returns the [skewness][skewness] of a [geometric][geometric-distribution] distribution with success probability `p`. + +```c +double out = stdlib_base_dists_geometric_skewness( 0.5 ); +// returns ~2.121 +``` + +The function accepts the following arguments: + +- **p**: `[in] double` success probability. + +```c +double stdlib_base_dists_geometric_skewness( const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/geometric/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_geometric_skewness( p ); + printf( "p: %lf, skew(X;p): %lf\n", p, y ); + } +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.js index 922d0943bbbd..da18b8227ece 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.js @@ -21,9 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var skewness = require( './../lib' ); @@ -31,14 +31,20 @@ var skewness = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var p; var y; var i; + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = ( randu() * 1.0 ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - p = ( randu()*1.0 ) + EPS; - y = skewness( p ); + y = skewness( p[ i % 100 ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b93d28e03b69 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/benchmark.native.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var p; + var y; + var i; + + len = 100; + p = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + p[ i ] = ( randu() * 1.0 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( p[ i % 100 ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..b8aeb5b28ff4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/benchmark/c/benchmark.c @@ -0,0 +1,138 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/geometric/skewness.h" +#include +#include +#include +#include +#include + +#define NAME "geometric-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double p[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + p[ i ] = random_uniform( 0.0, 1.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_geometric_skewness( p[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/examples/c/example.c new file mode 100644 index 000000000000..89ca038ab2fb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/geometric/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + p = random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_geometric_skewness( p ); + printf( "p: %lf, skew(X;p): %lf\n", p, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= 1.0 + ) { + return 0.0 / 0.0; // NaN + } + return ( 2.0 - p ) / stdlib_base_sqrt( 1.0 - p ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/test/test.native.js new file mode 100644 index 000000000000..52377db074d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/skewness/test/test.native.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof skewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `p`, the function returns `NaN`', opts, function test( t ) { + var s = skewness( NaN ); + t.equal( isnan( s ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a success probability `p` outside of `[0,1]`, the function returns `NaN`', opts, function test( t ) { + var s; + + s = skewness( -1.0 ); + t.equal( isnan( s ), true, 'returns NaN' ); + + s = skewness( 1.5 ); + t.equal( isnan( s ), true, 'returns NaN' ); + + s = skewness( NINF ); + t.equal( isnan( s ), true, 'returns NaN' ); + + s = skewness( PINF ); + t.equal( isnan( s ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the skewness of a geometric distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var i; + var p; + var y; + + expected = data.expected; + p = data.p; + for ( i = 0; i < expected.length; i++ ) { + y = skewness( p[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'p: '+p[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md index 748486fc1e3b..0967438c59ef 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md @@ -131,6 +131,101 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/gumbel/kurtosis.h" +``` + +#### stdlib_base_dists_gumbel_kurtosis( mu, beta ) + +Returns the [excess kurtosis][kurtosis] for a [Gumbel][gumbel-distribution] distribution with location parameter `mu` and scale parameter `beta`. + +```c +double out = stdlib_base_dists_gumbel_kurtosis( 0.0, 1.0 ); +// returns 2.4 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **beta**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_gumbel_kurtosis( const double mu, const double beta ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/gumbel/kurtosis.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double beta; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + beta = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_gumbel_kurtosis( mu, beta ); + printf( "µ: %lf, β: %lf, Kurt(X;µ,β): %lf\n", mu, beta, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.js index eb5a5e6f1dad..25027a028622 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,15 +33,22 @@ var kurtosis = require( './../lib' ); bench( pkg, function benchmark( b ) { var beta; + var len; var mu; var y; var i; + len = 100; + mu = new Float64Array( len ); + beta = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + beta[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - beta = ( randu()*20.0 ) + EPS; - y = kurtosis( mu, beta ); + y = kurtosis( mu[ i % len ], beta[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js new file mode 100644 index 000000000000..f6c51d58521e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var beta; + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + beta = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + beta[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = kurtosis( mu[ i % len ], beta[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/c/benchmark.c new file mode 100644 index 000000000000..04e6d58c2743 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/gumbel/kurtosis.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "gumbel-kurtosis" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double beta[ 100 ]; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_gumbel_kurtosis( mu[ i%100 ], beta[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c new file mode 100644 index 000000000000..c5bd11c93854 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/gumbel/kurtosis.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double beta; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + beta = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_gumbel_kurtosis( mu, beta ); + printf( "µ: %lf, β: %lf, Kurt(X;µ,β): %lf\n", mu, beta, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/gumbel/mode.h" +``` + +#### stdlib_base_dists_gumbel_mode( mu, beta ) + +Returns the [mode][mode] for a [Gumbel][gumbel-distribution] distribution with location parameter `mu` and scale parameter `beta`. + +```c +double out = stdlib_base_dists_gumbel_mode( 0.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **beta**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_gumbel_mode( const double mu, const double beta ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/gumbel/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double beta; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + beta = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_gumbel_mode( mu, beta ); + printf( "µ: %lf, β: %lf, mode(X;µ,β): %lf\n", mu, beta, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.js index 08f9de0a02e1..766f13bd4492 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,15 +33,22 @@ var mode = require( './../lib' ); bench( pkg, function benchmark( b ) { var beta; + var len; var mu; var y; var i; + len = 100; + mu = new Float64Array( len ); + beta = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + beta[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - beta = ( randu()*20.0 ) + EPS; - y = mode( mu, beta ); + y = mode( mu[ i % len ], beta[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..2bb9808bbe46 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var beta; + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + beta = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + beta[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( mu[ i % len ], beta[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..2aae2f615675 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/gumbel/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "gumbel-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double beta[ 100 ]; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_gumbel_mode( mu[ i%100 ], beta[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c new file mode 100644 index 000000000000..37428b42661d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/gumbel/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double beta; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + beta = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_gumbel_mode( mu, beta ); + printf( "µ: %lf, β: %lf, mode(X;µ,β): %lf\n", mu, beta, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/gumbel/stdev.h" +``` + +#### stdlib_base_dists_gumbel_stdev( mu, beta ) + +Returns the [standard deviation][standard-deviation] for a [Gumbel][gumbel-distribution] distribution with location parameter `mu` and scale parameter `beta`. + +```c +double out = stdlib_base_dists_gumbel_stdev( 0.0, 1.0 ); +// returns ~1.283 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **beta**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_gumbel_stdev( const double mu, const double beta ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/gumbel/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double beta; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + beta = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_gumbel_stdev( mu, beta ); + printf( "µ: %lf, β: %lf, SD(X;µ,β): %lf\n", mu, beta, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.js index 12c2f43042d7..1fa1f6b2d773 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -32,15 +33,22 @@ var stdev = require( './../lib' ); bench( pkg, function benchmark( b ) { var beta; + var len; var mu; var y; var i; + len = 100; + mu = new Float64Array( len ); + beta = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + beta[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - beta = ( randu()*20.0 ) + EPS; - y = stdev( mu, beta ); + y = stdev( mu[ i % len ], beta[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..6d2be076d3bd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var beta; + var len; + var mu; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + beta = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + beta[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % len ], beta[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..7b09c59b3c98 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/gumbel/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "gumbel-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double beta[ 100 ]; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_gumbel_stdev( mu[ i%100 ], beta[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c new file mode 100644 index 000000000000..ca485f42d917 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/gumbel/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double beta; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + beta = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_gumbel_stdev( mu, beta ); + printf( "µ: %lf, β: %lf, SD(X;µ,β): %lf\n", mu, beta, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/kumaraswamy/logcdf.h" +``` + +#### stdlib_base_dists_kumaraswamy_logcdf( x, a, b ) + +Evaluates the natural logarithm of the cumulative distribution function (CDF) for a Kumaraswamy's double bounded distribution. + +```c +double out = stdlib_base_dists_kumaraswamy_logcdf( 0.5, 1.0, 1.0 ); +// returns ~-0.693 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **a**: `[in] double` first shape parameter. +- **b**: `[in] double` second shape parameter. + +```c +double stdlib_base_dists_kumaraswamy_logcdf( const double x, const double a, const double b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/kumaraswamy/logcdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double a; + double b; + double y; + int i; + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0, 1.0 ); + a = random_uniform( 0, 5.0 ); + b = random_uniform( 0, 5.0 ); + y = stdlib_base_dists_kumaraswamy_logcdf( x, a, b ); + printf( "x: %lf, a: %lf, b: %lf, ln(F(x;a,b)): %lf\n", x, a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.js index d8065ba018e3..be3b8c9dd96e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.js @@ -21,6 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/array/uniform' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +33,26 @@ var logcdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var a; var s; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + a = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = randu(); + a[ i ] = ( randu()*5.0 ) + EPS; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) + EPS; - a = ( randu()*100.0 ) + EPS; - s = ( randu()*100.0 ) + EPS; - y = logcdf( x, a, s ); + y = logcdf( x[ i % len ], a[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -66,11 +76,11 @@ bench( pkg+':factory', function benchmark( b ) { a = 100.56789; s = 55.54321; mylogcdf = logcdf.factory( a, s ); + x = uniform( 100, -2.0, 2.0 ); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) + EPS; - y = mylogcdf( x ); + y = mylogcdf( x[ i % x.length ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..c51a6c7a9104 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logcdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logcdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var a; + var s; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + a = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = randu(); + a[ i ] = ( randu()*5.0 ) + EPS; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logcdf( x[ i % len ], a[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..99cd6f7f839c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/kumaraswamy/logcdf.h" +#include +#include +#include +#include +#include + +#define NAME "kumaraswamy-logcdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double x[ 100 ]; + double a[ 100 ]; + double b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 1.0 ); + a[ i ] = random_uniform( 0.1, 5.0 ); + b[ i ] = random_uniform( 0.1, 5.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_kumaraswamy_logcdf( x[ i%100 ], a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/examples/c/example.c new file mode 100644 index 000000000000..326e60c64059 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/kumaraswamy/logcdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double a; + double b; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 1.0 ); + a = random_uniform( 0.0, 5.0 ); + b = random_uniform( 0.0, 5.0 ); + y = stdlib_base_dists_kumaraswamy_logcdf( x, a, b ); + printf( "x: %lf, a: %lf, b: %lf, ln(F(x;a,b)): %lf\n", x, a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= 1.0 ) { + return 0.0; + } + return stdlib_base_ln( 1.0 - stdlib_base_pow( 1.0 - stdlib_base_pow( x, a ), b ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/test/test.native.js new file mode 100644 index 000000000000..b7efac9a3a2f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/test/test.native.js @@ -0,0 +1,162 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var randu = require( '@stdlib/random/base/randu' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var logcdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logcdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logcdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = logcdf( NaN, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logcdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logcdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a number greater than or equal to one for `x` and a finite `a` and `b`, the function returns `1`', opts, function test( t ) { + var y = logcdf( PINF, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = logcdf( 100.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = logcdf( 10.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + y = logcdf( 1.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns 0' ); + + t.end(); +}); + +tape( 'if provided a number less than or equal to zero for `x` and a finite `a` and `b`, the function returns `0`', opts, function test( t ) { + var y = logcdf( NINF, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logcdf( -100.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logcdf( -1.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logcdf( 0.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `a`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logcdf( 2.0, 0.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, -1.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 0.0, -1.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NINF, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NINF, PINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NINF, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logcdf( 2.0, 2.0, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 0.0, 2.0, -1/0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logcdf( 2.0, NaN, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function evaluates the logcdf of a Kumaraswamy\'s double bounded distribution', opts, function test( t ) { + var a; + var b; + var x; + var y; + var i; + + // TODO: Add fixtures + for ( i = 0; i < 100; i++ ) { + x = randu(); + a = ( randu()*5.0 ) + EPS; + b = ( randu()*5.0 ) + EPS; + y = logcdf( x, a, b ); + t.equal( isNumber( y ), true, 'returns a number' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/README.md index b1a43d18ec8f..93cf6c5a3b65 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/README.md @@ -174,6 +174,103 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/kumaraswamy/logpdf.h" +``` + +#### stdlib_base_dists_kumaraswamy_logpdf( x, a, b ) + +Evaluates the natural logarithm of the probability distribution function (PDF) for a Kumaraswamy's double bounded distribution. + +```c +double out = stdlib_base_dists_kumaraswamy_logpdf( 0.5, 1.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **a**: `[in] double` first shape parameter. +- **b**: `[in] double` second shape parameter. + +```c +double stdlib_base_dists_kumaraswamy_logpdf( const double x, const double a, const double b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/kumaraswamy/logpdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double a; + double b; + double y; + int i; + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0, 1.0 ); + a = random_uniform( 0, 5.0 ); + b = random_uniform( 0, 5.0 ); + y = stdlib_base_dists_kumaraswamy_logpdf( x, a, b ); + printf( "x: %lf, a: %lf, b: %lf, ln(f(x;a,b)): %lf\n", x, a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.js index 282ea2c431e2..a046b492c5fc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.js @@ -21,6 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/array/uniform' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,18 +33,26 @@ var logpdf = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var a; var s; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + a = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = randu(); + a[ i ] = ( randu()*5.0 ) + EPS; + s[ i ] = ( randu()*5.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) + EPS; - a = ( randu()*100.0 ) + EPS; - s = ( randu()*100.0 ) + EPS; - y = logpdf( x, a, s ); + y = logpdf( x[ i % len ], a[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } @@ -66,11 +76,11 @@ bench( pkg+':factory', function benchmark( b ) { a = 100.56789; s = 55.54321; mylogpdf = logpdf.factory( a, s ); + x = uniform( 100, -2.0, 2.0 ); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = ( randu()*2.0 ) + EPS; - y = mylogpdf( x ); + y = mylogpdf( x[ i % x.length ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..3ef323f526f7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var a; + var s; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + a = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = randu(); + a[ i ] = ( randu()*5.0 ) + EPS; + s[ i ] = ( randu()*5.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logpdf( x[ i % len ], a[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..e0fd65f5e333 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/kumaraswamy/logpdf.h" +#include +#include +#include +#include +#include + +#define NAME "kumaraswamy-logpdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double x[ 100 ]; + double a[ 100 ]; + double b[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 1.0 ); + a[ i ] = random_uniform( 0.1, 5.0 ); + b[ i ] = random_uniform( 0.1, 5.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_kumaraswamy_logpdf( x[ i%100 ], a[ i%100 ], b[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/examples/c/example.c new file mode 100644 index 000000000000..21dc28c0e31f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/kumaraswamy/logpdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double a; + double b; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 1.0 ); + a = random_uniform( 0.0, 5.0 ); + b = random_uniform( 0.0, 5.0 ); + y = stdlib_base_dists_kumaraswamy_logpdf( x, a, b ); + printf( "x: %lf, a: %lf, b: %lf, ln(f(x;a,b)): %lf\n", x, a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= 1.0 + ) { + return STDLIB_CONSTANT_FLOAT64_NINF; + } + out = stdlib_base_ln( a*b ); + out += ( a - 1.0 ) * stdlib_base_ln( x ); + out += ( b - 1.0 ) * stdlib_base_ln( 1.0 - stdlib_base_pow( x, a ) ); + return out; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/test/test.native.js new file mode 100644 index 000000000000..8a96b8d4921c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/test/test.native.js @@ -0,0 +1,177 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var randuFactory = require( '@stdlib/random/base/randu' ).factory; +var pdf = require( '@stdlib/stats/base/dists/kumaraswamy/pdf' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logpdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = logpdf( NaN, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logpdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + y = logpdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a number greater than or equal to one for `x` and a finite `a` and `b`, the function returns `-infinity`', opts, function test( t ) { + var y = logpdf( PINF, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 100.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 10.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 1.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided a number less than or equal to zero for `x` and a finite `a` and `b`, the function returns `-infinity`', opts, function test( t ) { + var y = logpdf( NINF, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( -100.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( -1.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 0.0, 0.5, 1.0 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `a`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logpdf( 2.0, 0.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, -1.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, -1.0, 2.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NINF, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NINF, PINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NINF, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logpdf( 2.0, 2.0, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, 2.0, -1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, 2.0, -1/0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, PINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NINF, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, NaN, NINF ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function evaluates the logpdf of a Kumaraswamy\'s double bounded distribution', opts, function test( t ) { + var expected; + var delta; + var randu; + var tol; + var a; + var b; + var x; + var y; + var i; + + randu = randuFactory({ + 'seed': 240 + }); + for ( i = 0; i < 100; i++ ) { + x = randu(); + a = ( randu()*5.0 ) + EPS; + b = ( randu()*5.0 ) + EPS; + y = logpdf( x, a, b ); + expected = ln( pdf( x, a, b ) ); + if ( y === expected ) { + t.equal( y, expected, 'x: '+x+', a:'+a+', b: '+b+', y: '+y+', expected: '+expected ); + } else { + delta = abs( y - expected ); + tol = 1000.0 * EPS * abs( expected ); + t.ok( delta <= tol, 'within tolerance. x: '+x+'. a: '+a+'. b: '+b+'. y: '+y+'. E: '+expected+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/c/benchmark.c index 72ed8634f06e..0b2e1368f360 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/median/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - a[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - b[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + a[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + b[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/README.md index 05a8d8b21b6a..ef9afc8c2c88 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/README.md @@ -158,6 +158,101 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/kumaraswamy/skewness.h" +``` + +#### stdlib_base_dists_kumaraswamy_skewness( a, b ) + +Returns the [skewness][skewness] of a [Kumaraswamy's double bounded][kumaraswamy-distribution] distribution with first shape parameter `a` and second shape parameter `b`. + +```c +double out = stdlib_base_dists_kumaraswamy_skewness( 1.0, 1.0 ); +// returns ~0.0 +``` + +The function accepts the following arguments: + +- **a**: `[in] double` first shape parameter. +- **b**: `[in] double` second shape parameter. + +```c +double stdlib_base_dists_kumaraswamy_skewness( const +double a, const double b ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/kumaraswamy/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double y; + int i; + for ( i = 0; i < 25; i++ ) { + a = random_uniform( 0.1, 10.0 ); + b = random_uniform( 0.1, 10.0 ); + y = stdlib_base_dists_kumaraswamy_skewness( a, b ); + printf( "a: %lf, b: %lf, skew(X;a,b): %lf\n", a, b, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.js index a6283ee98471..0f320ea65403 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -33,14 +34,21 @@ var skewness = require( './../lib' ); bench( pkg, function benchmark( b ) { var shape1; var shape2; + var len; var y; var i; + len = 100; + shape1 = new Float64Array( len ); + shape2 = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + shape1[ i ] = ( randu()*10.0 ) + EPS; + shape2[ i ] = ( randu()*10.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - shape1 = ( randu()*10.0 ) + EPS; - shape2 = ( randu()*10.0 ) + EPS; - y = skewness( shape1, shape2 ); + y = skewness( shape1[ i % len ], shape2[ i % len] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e6a639b9e03d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var shape1; + var shape2; + var len; + var y; + var i; + + len = 100; + shape1 = new Float64Array( len ); + shape2 = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + shape1[ i ] = ( randu()*10.0 ) + EPS; + shape2[ i ] = ( randu()*10.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( shape1[ i % len ], shape2[ i % len] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..eb09e3a3313f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/benchmark/c/benchmark.c @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/kumaraswamy/skewness.h" +#include +#include +#include +#include +#include + +#define NAME "kumaraswamy-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double shape1[ 100 ]; + double shape2[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + shape1[ i ] = random_uniform( 0.1, 10.0 ); + shape2[ i ] = random_uniform( 0.1, 10.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_kumaraswamy_skewness( shape1[ i%100 ], shape2[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/examples/c/example.c new file mode 100644 index 000000000000..f4cc19d3923e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/kumaraswamy/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( 0.0, 10.0 ); + y = stdlib_base_dists_kumaraswamy_skewness( a, b ); + printf( "a: %lf, b: %lf, skew(X;a,b): %lf\n", a, b, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/levy/mean.h" +``` + +#### stdlib_base_dists_levy_mean( mu, c ) + +Evaluates the [expected value][mean] for a [Lévy][levy-distribution] distribution with location parameter `mu` and scale parameter `c`. + +```c +double out = stdlib_base_dists_levy_mean( 0.0, 1.0 ); +// returns Infinity +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **c**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_levy_mean( const double mu, const double c ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/levy/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( -5.0, 5.0 ); + a = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_levy_mean( mu, c ); + printf( "µ: %lf, c: %lf, E(X;µ,c): %lf\n", mu, c, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.js index d3c4ee049f95..09b800d9e12d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var mean = require( './../lib' ); @@ -31,16 +32,23 @@ var mean = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var c; var y; var i; + len = 100; + mu = new Float64Array( len ); + c = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + c[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - c = ( randu()*20.0 ) + EPS; - y = mean( mu, c ); + y = mean( mu[ i % len ], c[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.native.js new file mode 100644 index 000000000000..7dbd8c4a0798 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mean = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mean instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var c; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + c = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + c[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mean( mu[ i % len ], c[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/c/benchmark.c new file mode 100644 index 000000000000..fbea686025c6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/levy/mean.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "levy-mean" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double c[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + c[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_levy_mean( mu[ i%100 ], c[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/examples/c/example.c new file mode 100644 index 000000000000..ac00b8c79bf8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/levy/mean.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + c = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_levy_mean( mu, c ); + printf( "µ: %lf, c: %lf, E(X;µ,c): %lf\n", mu, c, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mean/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mean/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/levy/mode.h" +``` + +#### stdlib_base_dists_levy_mode( mu, c ) + +Evaluates the [mode][mode] for a [Lévy][levy-distribution] distribution with location parameter `mu` and scale parameter `c`. + +```c +double out = stdlib_base_dists_levy_mode( 0.0, 1.0 ); +// returns ~0.333 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **c**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_levy_mode( const double mu, const double c ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/levy/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + c = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_levy_mode( mu, c ); + printf( "µ: %lf, c: %lf, mode(X;µ,c): %lf\n", mu, c, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.js index 0991bc005d07..d6c2810a4508 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var mode = require( './../lib' ); @@ -31,16 +32,23 @@ var mode = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var c; var y; var i; + len = 100; + mu = new Float64Array( len ); + c = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + c[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - c = ( randu()*20.0 ) + EPS; - y = mode( mu, c ); + y = mode( mu[ i % len ], c[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d15c89664e8b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var c; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + c = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + c[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( mu[ i % len ], c[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..e80f6915a4a5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/levy/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "levy-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double c[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + c[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_levy_mode( mu[ i%100 ], c[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/examples/c/example.c new file mode 100644 index 000000000000..97b191ba81af --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/levy/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + c = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_levy_mode( mu, c ); + printf( "µ: %lf, c: %lf, mode(X;µ,c): %lf\n", mu, c, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/levy/stdev.h" +``` + +#### stdlib_base_dists_levy_stdev( mu, c ) + +Returns the [standard deviation][standard-deviation] for a [Lévy][levy-distribution] distribution with location parameter `mu` and scale parameter `c`. + +```c +double out = stdlib_base_dists_levy_stdev( 0.0, 1.0 ); +// returns Infinity +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **c**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_levy_stdev( const double mu, const double c ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/levy/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + c = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_levy_stdev( mu, c ); + printf( "µ: %lf, c: %lf, SD(X;µ,c): %lf\n", mu, c, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.js index 2fbf0660a61d..1b9d8278fa8f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var stdev = require( './../lib' ); @@ -31,16 +32,23 @@ var stdev = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var c; var y; var i; + len = 100; + mu = new Float64Array( len ); + c = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + c[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - c = ( randu()*20.0 ) + EPS; - y = stdev( mu, c ); + y = stdev( mu[ i % len ], c[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..a1735043bad1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var c; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + c = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + c[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % len ], c[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..bd513b4395a0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/levy/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "levy-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double c[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + c[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_levy_stdev( mu[ i%100 ], c[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/examples/c/example.c new file mode 100644 index 000000000000..820d757cd1a8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/levy/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + c = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_levy_stdev( mu, c ); + printf( "µ: %lf, c: %lf, SD(X;µ,c): %lf\n", mu, c, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/levy/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/logistic/kurtosis.h" +``` + +#### stdlib_base_dists_logistic_kurtosis( mu, s ) + +Returns the excess kurtosis for a logistic distribution with location `mu` and scale `s`. + +```c +double out = stdlib_base_dists_logistic_kurtosis( 0.0, 1.0 ); +// returns 1.2 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_logistic_kurtosis( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/logistic/kurtosis.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + s = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_logistic_kurtosis( mu, s ); + printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y ); + } +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js index 3506be1968fb..7f20c60e7411 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -31,16 +32,23 @@ var kurtosis = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + s[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = kurtosis( mu, s ); + y = kurtosis( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js new file mode 100644 index 000000000000..c3dc60ddecf5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu() * 100.0 ) - 50.0; + s[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = kurtosis( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c new file mode 100644 index 000000000000..54359955e164 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/logistic/kurtosis.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "logistic-kurtosis" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_logistic_kurtosis( mu[ i % 100 ], s[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c new file mode 100644 index 000000000000..c626e5e08911 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/logistic/kurtosis.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + s = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_logistic_kurtosis( mu, s ); + printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/logistic/stdev.h" +``` + +#### stdlib_base_dists_logistic_stdev( mu, s ) + +Returns the [standard deviation][standard-deviation] for a [logistic][logistic-distribution] distribution with location parameter `mu` and scale parameter `s`. + +```c +double out = stdlib_base_dists_logistic_stdev( 0.0, 1.0 ); +// returns ~1.814 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **s**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_logistic_stdev( const double mu, const double s ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/logistic/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + s = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_logistic_stdev( mu, s ); + printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.js index 5544fb29feee..91b59e41fc56 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.js @@ -22,6 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; @@ -31,16 +32,23 @@ var stdev = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { + var len; var mu; var s; var y; var i; + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - mu = ( randu()*100.0 ) - 50.0; - s = ( randu()*20.0 ) + EPS; - y = stdev( mu, s ); + y = stdev( mu[ i % len ], s[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..f929b13622f3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var len; + var mu; + var s; + var y; + var i; + + len = 100; + mu = new Float64Array( len ); + s = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + mu[ i ] = ( randu()*100.0 ) - 50.0; + s[ i ] = ( randu()*20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % len ], s[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..9b6f95e3c250 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/logistic/stdev.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "logistic-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double mu[ 100 ]; + double s[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + s[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_logistic_stdev( mu[ i%100 ], s[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/examples/c/example.c new file mode 100644 index 000000000000..d5dd40af0118 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/logistic/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double mu; + double s; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + s = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_logistic_stdev( mu, s ); + printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +# Entropy + +> Planck (discrete exponential) distribution [differential entropy][entropy]. + + + +
+ +The [differential entropy][entropy] (in [nats][nats]) for a Planck random variable is + + + +```math +H\left( X \right) = \frac{\lambda e^{-\lambda}}{1 - e^{-\lambda}} - \log\left( 1 - e^{-\lambda} \right) +``` + + + +where `λ` is the shape parameter. + +
+ + + + + +
+ +## Usage + +```javascript +var entropy = require( '@stdlib/stats/base/dists/planck/entropy' ); +``` + +#### entropy( lambda ) + +Returns the [differential entropy][entropy] of a Planck distribution with shape parameter `lambda` (in [nats][nats]). + +```javascript +var v = entropy( 0.1 ); +// returns ~3.3030 + +v = entropy( 1.5 ); +// returns ~0.6833 +``` + +If provided a shape parameter `lambda` which is `NaN` or nonpositive, the function returns `NaN`. + +```javascript +var v = entropy( NaN ); +// returns NaN + +v = entropy( -1.5 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var entropy = require( '@stdlib/stats/base/dists/planck/entropy' ); + +var lambda = uniform( 10, 0.1, 5.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = entropy( lambda[ i ] ); + console.log( 'λ: %d, H(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29 + +[nats]: https://en.wikipedia.org/wiki/Nat_%28unit%29 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js new file mode 100644 index 000000000000..ce171ab4f102 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var entropy = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var y; + var i; + + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = entropy( lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt new file mode 100644 index 000000000000..4e26e6fc5a4d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt @@ -0,0 +1,27 @@ + +{{alias}}( λ ) + Returns the differential entropy of a Planck distribution with shape + parameter `λ` (in nats). + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + out: number + Entropy. + + Examples + -------- + > var v = {{alias}}( 0.1 ) + ~3.3030 + > v = {{alias}}( 1.5 ) + ~0.6833 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts new file mode 100644 index 000000000000..0dafc84dc065 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the differential entropy of a Planck distribution. +* +* ## Notes +* +* - If `lambda <= 0`, the function returns `NaN`. +* +* @param lambda - shape parameter +* @returns differential entropy +* +* @example +* var v = entropy( 0.1 ); +* // returns ~3.3030 +* +* @example +* var v = entropy( 1.5 ); +* // returns ~0.6833 +* +* @example +* var v = entropy( 2.9 ); +* // returns ~0.2255 +* +* @example +* var v = entropy( -1.1 ); +* // returns NaN +* +* @example +* var v = entropy( NaN ); +* // returns NaN +*/ +declare function entropy( lambda: number ): number; + + +// EXPORTS // + +export = entropy; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts new file mode 100644 index 000000000000..73b13b540212 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import entropy = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + entropy( 0.3 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + entropy( true ); // $ExpectError + entropy( false ); // $ExpectError + entropy( null ); // $ExpectError + entropy( undefined ); // $ExpectError + entropy( '5' ); // $ExpectError + entropy( [] ); // $ExpectError + entropy( {} ); // $ExpectError + entropy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + entropy(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js new file mode 100644 index 000000000000..acdbbbc7cf6b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var entropy = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 5.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = entropy( lambda[ i ] ); + console.log( 'λ: %d, H(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js new file mode 100644 index 000000000000..44dd7cf7b679 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Planck distribution differential entropy. +* +* @module @stdlib/stats/base/dists/planck/entropy +* +* @example +* var entropy = require( '@stdlib/stats/base/dists/planck/entropy' ); +* +* var v = entropy( 0.1 ); +* // returns ~3.3030 +* +* v = entropy( 1.5 ); +* // returns ~0.6833 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js new file mode 100644 index 000000000000..ac3db097a539 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var exp = require( '@stdlib/math/base/special/exp' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); +var ln = require( '@stdlib/math/base/special/ln' ); + + +// MAIN // + +/** +* Returns the differential entropy of a Planck distribution. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {PositiveNumber} differential entropy +* +* @example +* var v = entropy( 0.1 ); +* // returns ~3.3030 +* +* @example +* var v = entropy( 1.5 ); +* // returns ~0.6833 +* +* @example +* var v = entropy( 2.9 ); +* // returns ~0.2255 +* +* @example +* var v = entropy( -1.1 ); +* // returns NaN +* +* @example +* var v = entropy( NaN ); +* // returns NaN +*/ +function entropy( lambda ) { + var c; + if ( isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + c = -expm1( -lambda ); + return ( lambda * exp( -lambda ) / c ) - ln( c ); +} + + +// EXPORTS // + +module.exports = entropy; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json new file mode 100644 index 000000000000..1c6b072fbcf1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/stats/base/dists/planck/entropy", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution differential entropy.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "parameter", + "memoryless", + "life-time", + "discrete", + "entropy", + "shannon", + "information", + "nats", + "planck", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json new file mode 100644 index 000000000000..14e43954d8c1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json @@ -0,0 +1 @@ +{"lambda": [11.455931688414339, 12.049886662295279, 19.686522775043272, 11.015032049363455, 17.296911359484074, 15.689532162118596, 3.3145508589156147, 5.504482683615719, 6.576128114123461, 13.375086796004984, 10.34069873156734, 9.72980253893475, 11.348605319802008, 6.667030734470609, 11.327226583010956, 18.735451535117857, 1.3853781760477135, 12.9034695366267, 12.229488830745638, 11.965908082806129, 5.264935976789071, 2.6688592326814997, 13.420190489773617, 15.02336736559425, 18.62421960884803, 3.3246336724638903, 16.642827792190545, 7.838647648093957, 19.32238077907249, 8.713855968469682, 13.151286309768249, 12.72787815708906, 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5.3817764966132864e-08, 1.077987085601636, 0.019288798863479485, 1.2476903422225294e-06, 0.00022789098203708, 0.0828018110952809, 1.2103388541413275e-07, 0.00046264419152328986, 7.157004104901858e-05, 2.0907931414794163, 2.6252060014454115e-07, 8.528564421848815e-06, 0.06797976714954818, 4.4204352722693346e-06, 1.5180441692997111e-06, 3.401530834751432e-07, 0.4669980690919109, 7.643900605534708e-06, 0.00010853962561459329, 2.0160359038968086e-06, 2.738744932367392, 4.938381461424489e-06]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py new file mode 100644 index 000000000000..8b3d34e9c760 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py @@ -0,0 +1,77 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> lam = np.random.rand(1000) * 20.0 + python> gen(lam, "data.json") + ``` + """ + # Compute entropy values: + z = np.array(planck.entropy(lam)) + + # Store data to be written to file as a dictionary: + data = { + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + lam = np.random.rand(1000) * 20.0 + gen(lam, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js new file mode 100644 index 000000000000..16326ab2bcb4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var entropy = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof entropy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) { + var v = entropy( NaN ); + t.equal( isnan( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) { + var v; + + v = entropy( 0.0 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + v = entropy( -1.0 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the differential entropy of a Planck distribution', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var i; + var y; + + expected = data.expected; + lambda = data.lambda; + for ( i = 0; i < expected.length; i++ ) { + y = entropy( lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/README.md new file mode 100644 index 000000000000..a4f1d5a8ba0e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/README.md @@ -0,0 +1,139 @@ + + +# Kurtosis + +> Planck (discrete exponential) distribution [excess kurtosis][kurtosis]. + + + +
+ +The [excess kurtosis][kurtosis] for a Planck random variable is + + + +```math +\mathop{\mathrm{Kurt}}\left( X \right) = 4 + 2 \cosh(\lambda) +``` + + + +where `λ` is the shape parameter. + +
+ + + + + +
+ +## Usage + +```javascript +var kurtosis = require( '@stdlib/stats/base/dists/planck/kurtosis' ); +``` + +#### kurtosis( lambda ) + +Returns the [excess kurtosis][kurtosis] of a Planck distribution with shape parameter `lambda`. + +```javascript +var v = kurtosis( 0.1 ); +// returns ~6.0100 + +v = kurtosis( 1.5 ); +// returns ~8.7048 +``` + +If provided a shape parameter `lambda` which is nonpositive or `NaN`, the function returns `NaN`. + +```javascript +var v = kurtosis( NaN ); +// returns NaN + +v = kurtosis( -1.5 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var kurtosis = require( '@stdlib/stats/base/dists/planck/kurtosis' ); + +var lambda = uniform( 10, 0.1, 10.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = kurtosis( lambda[ i ] ); + console.log( 'λ: %d, Kurt(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[kurtosis]: https://en.wikipedia.org/wiki/Kurtosis + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/benchmark/benchmark.js new file mode 100644 index 000000000000..2ed19485a1b2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var kurtosis = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var y; + var i; + + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = kurtosis( lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/repl.txt new file mode 100644 index 000000000000..7f8d80a1e293 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/repl.txt @@ -0,0 +1,27 @@ + +{{alias}}( λ ) + Returns the excess kurtosis of a Planck distribution with shape parameter + `λ`. + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + out: number + Excess kurtosis. + + Examples + -------- + > var v = {{alias}}( 0.1 ) + ~6.0100 + > v = {{alias}}( 1.5 ) + ~8.7048 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/types/index.d.ts new file mode 100644 index 000000000000..1de97e2f3119 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the excess kurtosis of a Planck distribution. +* +* ## Notes +* +* - If `lambda <= 0`, the function returns `NaN`. +* +* @param lambda - shape parameter +* @returns kurtosis +* +* @example +* var v = kurtosis( 0.1 ); +* // returns ~6.0100 +* +* @example +* var v = kurtosis( 1.5 ); +* // returns ~8.7048 +* +* @example +* var v = kurtosis( -1.1 ); +* // returns NaN +* +* @example +* var v = kurtosis( NaN ); +* // returns NaN +*/ +declare function kurtosis( lambda: number ): number; + + +// EXPORTS // + +export = kurtosis; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/types/test.ts new file mode 100644 index 000000000000..32f723300471 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import kurtosis = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + kurtosis( 0.3 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + kurtosis( true ); // $ExpectError + kurtosis( false ); // $ExpectError + kurtosis( null ); // $ExpectError + kurtosis( undefined ); // $ExpectError + kurtosis( '5' ); // $ExpectError + kurtosis( [] ); // $ExpectError + kurtosis( {} ); // $ExpectError + kurtosis( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + kurtosis(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/examples/index.js new file mode 100644 index 000000000000..13f77f695509 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var kurtosis = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 10.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = kurtosis( lambda[ i ] ); + console.log( 'λ: %d, Kurt(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/lib/index.js new file mode 100644 index 000000000000..082da5dc4278 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Planck distribution excess kurtosis. +* +* @module @stdlib/stats/base/dists/planck/kurtosis +* +* @example +* var kurtosis = require( '@stdlib/stats/base/dists/planck/kurtosis' ); +* +* var v = kurtosis( 0.1 ); +* // returns ~6.0100 +* +* v = kurtosis( 1.5 ); +* // returns ~8.7048 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/lib/main.js new file mode 100644 index 000000000000..c9ae313878a8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/lib/main.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var cosh = require( '@stdlib/math/base/special/cosh' ); + + +// MAIN // + +/** +* Returns the excess kurtosis of a Planck distribution. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {PositiveNumber} excess kurtosis +* +* @example +* var v = kurtosis( 0.1 ); +* // returns ~6.0100 +* +* @example +* var v = kurtosis( 1.5 ); +* // returns ~8.7048 +* +* @example +* var v = kurtosis( -1.1 ); +* // returns NaN +* +* @example +* var v = kurtosis( NaN ); +* // returns NaN +*/ +function kurtosis( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + return 4.0 + ( 2.0 * cosh( lambda ) ); +} + + +// EXPORTS // + +module.exports = kurtosis; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/package.json new file mode 100644 index 000000000000..89011730cb52 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/stats/base/dists/planck/kurtosis", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution excess kurtosis.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "parameter", + "memoryless", + "life-time", + "discrete", + "kurtosis", + "excess", + "tails", + "planck", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/fixtures/python/data.json new file mode 100644 index 000000000000..e36ad295a2d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/fixtures/python/data.json @@ -0,0 +1 @@ +{"lambda": [4.975162669672901, 9.489932723747437, 9.147662763199428, 7.485806747136657, 11.453311635593124, 2.7572468600606115, 4.772164918540753, 18.427039841658434, 11.513514163377618, 3.4056518060090846, 10.496093119695294, 16.643555884495335, 10.387625296849157, 19.90659095126921, 14.436653079797866, 16.38618293037597, 0.6486005946342499, 15.17021139359711, 13.510306621439266, 17.931878813902628, 6.958456296603708, 5.636833791613681, 5.129235681164392, 18.851644559724484, 1.5145862189290438, 8.510293534534025, 11.941231890434496, 17.39976633926515, 6.065343452976366, 16.4488911177914, 19.921514031349187, 3.2945985164072744, 15.092177459239144, 9.65680851192754, 5.835184505225451, 17.396776375159604, 18.279650119912418, 4.329048528572876, 2.762393713394231, 9.300356783902963, 9.904484720762117, 14.992197917585523, 16.031817737877766, 6.060163356431412, 15.626650266055167, 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2286677.6720682927, 8.732000495988185, 243.26384680906162, 211511807.33906865, 5829.073188617783, 471890.37915724504, 12478447.514436219, 877.8497858628253, 7420.601575188877, 354.11547686629433, 3970252.284547869, 247716296.2347697, 55354.437520415195, 1570429.1748452946, 12139399.912856596, 70.39178640964268, 6.939881835655007, 86793400.96257105]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/fixtures/python/runner.py new file mode 100644 index 000000000000..161e06609ee9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/fixtures/python/runner.py @@ -0,0 +1,77 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> lam = np.random.rand(1000) * 20 + python> gen(lam, "data.json") + ``` + """ + # Compute excess kurtosis values: + z = np.array(planck.stats(lam, moments='k')) + + # Store data to be written to file as a dictionary: + data = { + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + lam = np.random.rand(1000) * 20.0 + gen(lam, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/test.js new file mode 100644 index 000000000000..e6fa6f90296f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/kurtosis/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var kurtosis = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof kurtosis, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) { + var v = kurtosis( NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) { + var v; + + v = kurtosis( 0.0 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + v = kurtosis( -1.5 ); + t.equal( isnan( v ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns the excess kurtosis of a Planck distribution', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var i; + var y; + + expected = data.expected; + lambda = data.lambda; + for ( i = 0; i < expected.length; i++ ) { + y = kurtosis( lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/README.md new file mode 100644 index 000000000000..d14304e5e82c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/README.md @@ -0,0 +1,149 @@ + + +# Logarithm of Cumulative Distribution Function + +> Evaluate the logarithm of the [cumulative distribution function][cdf] Planck (discrete exponential) distribution. + +
+ +The [cumulative distribution function][cdf] for a Planck random variable is + + + +```math +F(x;\lambda) = 1 - e^{-\lambda (\lfloor x \rfloor + 1)} +``` + + + +where `λ` is the shape parameter and `x` denotes the count of events in a quantized system. + +
+ + + +
+ +## Usage + +```javascript +var logcdf = require( '@stdlib/stats/base/dists/planck/logcdf' ); +``` + +#### logcdf( x, lambda ) + +Evaluates the logarithm of the [cumulative distribution function][cdf] for a Planck (discrete exponential) distribution with shape parameter `lambda`. + +```javascript +var y = logcdf( 2.0, 0.5 ); +// returns ~-0.2525 + +y = logcdf( 2.0, 1.5 ); +// returns ~-0.0112 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = logcdf( NaN, 0.5 ); +// returns NaN + +y = logcdf( 0.0, NaN ); +// returns NaN +``` + +If provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`. + +```javascript +var y = logcdf( 2.0, -1.0 ); +// returns NaN +``` + +#### logcdf.factory( lambda ) + +Returns a function for evaluating the logarithm of the [cumulative distribution function][cdf] of a Planck (discrete exponential) distribution with shape parameter `lambda`. + +```javascript +var mylogcdf = logcdf.factory( 1.5 ); +var y = mylogcdf( 3.0 ); +// returns ~-0.0025 + +y = mylogcdf( 1.0 ); +// returns ~-0.0511 +``` + +
+ + + +
+ +## Notes + +- In virtually all cases, using the `logpmf` or `logcdf` functions is preferable to manually computing the logarithm of the `pmf` or `cdf`, respectively, since the latter is prone to overflow and underflow. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logcdf = require( '@stdlib/stats/base/dists/planck/logcdf' ); + +var x = discreteUniform( 10, 0, 5 ); +var lambda = uniform( 10, 0.1, 5.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = logcdf( x[ i ], lambda[ i ] ); + console.log( 'x: %d, λ: %d, ln(F(x;λ)): %d', x[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/benchmark/benchmark.js new file mode 100644 index 000000000000..fe7102fcfe17 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/benchmark/benchmark.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var logcdf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var x; + var y; + var i; + + x = discreteUniform( 100, 0, 40 ); + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logcdf( x[ i % x.length ], lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+':factory', function benchmark( b ) { + var mylogcdf; + var x; + var y; + var i; + + x = discreteUniform( 100, 0, 40 ); + mylogcdf = logcdf.factory( 0.3 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mylogcdf( x[ i % x.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/repl.txt new file mode 100644 index 000000000000..ba3408ecc8c8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/repl.txt @@ -0,0 +1,65 @@ + +{{alias}}( x, λ ) + Evaluates the logarithm of the cumulative distribution function (CDF) for a + Planck distribution with shape parameter `λ` at a value `x`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + λ: number + Shape parameter. + + Returns + ------- + out: number + Evaluated logCDF. + + Examples + -------- + > var y = {{alias}}( 2.0, 0.5 ) + ~-0.2525 + > y = {{alias}}( 2.0, 1.5 ) + ~-0.0112 + > y = {{alias}}( -1.0, 4.0 ) + -Infinity + > y = {{alias}}( NaN, 0.5 ) + NaN + > y = {{alias}}( 0.0, NaN ) + NaN + // Invalid shape parameter + > y = {{alias}}( 2.0, -1.4 ) + NaN + + +{{alias}}.factory( λ ) + Returns a function for evaluating the logarithm of the cumulative + distribution function (CDF) of a Planck distribution with shape parameter + `λ`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + logcdf: Function + Logarithm of the cumulative distribution function (CDF). + + Examples + -------- + > var mylogcdf = {{alias}}.factory( 1.5 ); + > var y = mylogcdf( 3.0 ) + ~-0.0025 + > y = mylogcdf( 1.0 ) + ~-0.0511 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/types/index.d.ts new file mode 100644 index 000000000000..b149cb4db6d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/types/index.d.ts @@ -0,0 +1,114 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the natural logarithm of the cumulative distribution function (CDF) for a Planck distribution. +* +* @param x - input value +* @returns evaluated logCDF +*/ +type Unary = ( x: number ) => number; + +/** +* Interface for the logarithm of the cumulative distribution function (CDF) of a Planck distribution. +*/ +interface LogCDF { + /** + * Evaluates the logarithm of the cumulative distribution function (CDF) for a Planck distribution with shape parameter `lambda` at a value `x`. + * + * ## Notes + * + * - If `lambda <= 0`, the function returns `NaN`. + * + * @param x - input value + * @param lambda - shape parameter + * @returns evaluated logCDF + * + * @example + * var y = logcdf( 2.0, 0.5 ); + * // returns ~-0.2525 + * + * @example + * var y = logcdf( 2.0, 1.5 ); + * // returns ~-0.0112 + * + * @example + * var y = logcdf( -1.0, 0.5 ); + * // returns -Infinity + * + * @example + * var y = logcdf( NaN, 0.5 ); + * // returns NaN + * + * @example + * var y = logcdf( 0.0, NaN ); + * // returns NaN + * + * @example + * // Invalid shape parameter + * var y = logcdf( 2.0, -1.4 ); + * // returns NaN + */ + ( x: number, lambda: number ): number; + + /** + * Returns a function for evaluating the logarithm of the cumulative distribution function (CDF) for a Planck distribution with shape parameter `lambda`. + * + * @param lambda - shape parameter + * @returns logCDF + * + * @example + * var mylogcdf = logcdf.factory( 1.5 ); + * var y = mylogcdf( 3.0 ); + * // returns ~-0.0025 + * + * y = mylogcdf( 1.0 ); + * // returns ~-0.0511 + */ + factory( lambda: number ): Unary; +} + +/** +* Evaluates the logarithm of the cumulative distribution function (CDF) for a Planck distribution with shape parameter `lambda`. +* +* @param x - input value +* @param lambda - shape parameter +* @returns evaluated logCDF +* +* @example +* var y = logcdf( 2.0, 0.5 ); +* // returns ~-0.2525 +* +* y = logcdf( 2.0, 1.5 ); +* // returns ~-0.0112 +* +* var mylogcdf = logcdf.factory( 1.5 ); +* y = mylogcdf( 3.0 ); +* // returns ~-0.0025 +* +* y = mylogcdf( 1.0 ); +* // returns ~-0.0511 +*/ +declare var logCDF: LogCDF; + + +// EXPORTS // + +export = logCDF; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/types/test.ts new file mode 100644 index 000000000000..6400f0332567 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/docs/types/test.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import logcdf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + logcdf( 2.0, 0.4 ); // $ExpectType number + logcdf( 1.0, 0.2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + logcdf( true, 0.3 ); // $ExpectError + logcdf( false, 0.2 ); // $ExpectError + logcdf( '5', 0.1 ); // $ExpectError + logcdf( [], 0.1 ); // $ExpectError + logcdf( {}, 0.4 ); // $ExpectError + logcdf( ( x: number ): number => x, 0.2 ); // $ExpectError + + logcdf( 9.0, true ); // $ExpectError + logcdf( 9.0, false ); // $ExpectError + logcdf( 5.0, '5' ); // $ExpectError + logcdf( 8.0, [] ); // $ExpectError + logcdf( 9.0, {} ); // $ExpectError + logcdf( 8.0, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + logcdf(); // $ExpectError + logcdf( 2.0 ); // $ExpectError + logcdf( 2.0, 0.8, 4.0 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + logcdf.factory( 0.4 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = logcdf.factory( 0.4 ); + fcn( 2.0 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided an invalid argument... +{ + const fcn = logcdf.factory( 0.4 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = logcdf.factory( 0.4 ); + fcn(); // $ExpectError + fcn( 2.0, 0.0 ); // $ExpectError + fcn( 2.0, 0.0, 1.0 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided a value other than a number... +{ + logcdf.factory( true ); // $ExpectError + logcdf.factory( false ); // $ExpectError + logcdf.factory( '5' ); // $ExpectError + logcdf.factory( [] ); // $ExpectError + logcdf.factory( {} ); // $ExpectError + logcdf.factory( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + logcdf.factory( 0.0, 0.2 ); // $ExpectError + logcdf.factory( 0.0, 0.4, 8 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/examples/index.js new file mode 100644 index 000000000000..713087928bc0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/examples/index.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logcdf = require( './../lib' ); + +var x = discreteUniform( 10, 0, 5 ); +var lambda = uniform( 10, 0.1, 5.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = logcdf( x[ i ], lambda[ i ] ); + console.log( 'x: %d, λ: %d, F(x;λ): %d', x[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/factory.js new file mode 100644 index 000000000000..75ebf64cebd9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/factory.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var constantFunction = require( '@stdlib/utils/constant-function' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); + + +// MAIN // + +/** +* Returns a function for evaluating the logarithm of the cumulative distribution function (CDF) for a Planck distribution with shape parameter `lambda`. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {Function} logCDF +* +* @example +* var logcdf = factory( 1.5 ); +* var y = logcdf( 3.0 ); +* // returns ~-0.0025 +* +* y = logcdf( 1.0 ); +* // returns ~-0.0511 +*/ +function factory( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return constantFunction( NaN ); + } + return logcdf; + + /** + * Evaluates the logarithm of the cumulative distribution function (CDF) for a Planck distribution. + * + * @private + * @param {number} x - input value + * @returns {number} evaluated logCDF + * + * @example + * var y = logcdf( 2.0 ); + * // returns + */ + function logcdf( x ) { + if ( isnan( x ) ) { + return NaN; + } + if ( x < 0.0 ) { + return NINF; + } + if ( x === PINF ) { + return 0.0; + } + return ln( -expm1( -lambda * ( floor(x)+1.0 ) ) ); + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/index.js new file mode 100644 index 000000000000..e4d800b5e370 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Evaluate the logarithm of the cumulative distribution function (CDF) for a Planck distribution with shape parameter `lambda`. +* +* @module @stdlib/stats/base/dists/planck/logcdf +* +* @example +* var logcdf = require( '@stdlib/stats/base/dists/planck/logcdf' ); +* +* var y = logcdf( 2.0, 0.5 ); +* // returns ~-0.2525 +* +* y = logcdf( 2.0, 1.5 ); +* // returns ~-0.0112 +* +* var mylogcdf = logcdf.factory( 1.5 ); +* y = mylogcdf( 3.0 ); +* // returns ~-0.0025 +* +* y = mylogcdf( 1.0 ); +* // returns ~-0.0511 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/main.js new file mode 100644 index 000000000000..4b3c976d2272 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/lib/main.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); + + +// MAIN // + +/** +* Evaluates the logarithm of the cumulative distribution function (CDF) for a Planck distribution with shape parameter `lambda` at a value `x`. +* +* @param {number} x - input value +* @param {PositiveNumber} lambda - shape parameter +* @returns {number} evaluated logCDF +* +* @example +* var y = logcdf( 2.0, 0.5 ); +* // returns ~-0.2525 +* +* @example +* var y = logcdf( 2.0, 1.5 ); +* // returns ~-0.0112 +* +* @example +* var y = logcdf( -1.0, 0.5 ); +* // returns -Infinity +* +* @example +* var y = logcdf( NaN, 0.5 ); +* // returns NaN +* +* @example +* var y = logcdf( 0.0, NaN ); +* // returns NaN +* +* @example +* // Invalid shape parameter +* var y = logcdf( 2.0, -1.4 ); +* // returns NaN +*/ +function logcdf( x, lambda ) { + if ( isnan( x ) || isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + if ( x < 0.0 ) { + return NINF; + } + if ( x === PINF ) { + return 0.0; + } + return ln( -expm1( -lambda * ( floor(x)+1.0 ) ) ); +} + + +// EXPORTS // + +module.exports = logcdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/package.json new file mode 100644 index 000000000000..b15232a21ad8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/stats/base/dists/planck/logcdf", + "version": "0.0.0", + "description": "Evaluate the logarithm of the cumulative distribution function (CDF) for a Planck (discrete exponential) distribution.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "probability", + "cdf", + "cumulative distribution", + "distribution function", + "memoryless", + "life-time", + "discrete", + "logarithm", + "log", + "planck", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/large_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/large_lambda.json new file mode 100644 index 000000000000..e9eee202e27f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/large_lambda.json @@ -0,0 +1 @@ +{"x": [5.0, 9.0, 5.0, 7.0, 3.0, 6.0, 7.0, 1.0, 3.0, 4.0, 8.0, 7.0, 9.0, 10.0, 6.0, 5.0, 2.0, 9.0, 1.0, 5.0, 9.0, 5.0, 6.0, 4.0, 5.0, 9.0, 7.0, 8.0, 4.0, 4.0, 5.0, 2.0, 3.0, 1.0, 4.0, 6.0, 7.0, 7.0, 4.0, 7.0, 0.0, 1.0, 1.0, 3.0, 6.0, 7.0, 7.0, 2.0, 8.0, 1.0, 9.0, 9.0, 6.0, 5.0, 7.0, 4.0, 9.0, 9.0, 3.0, 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b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/runner.py new file mode 100644 index 000000000000..1e511339558c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/runner.py @@ -0,0 +1,87 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(x, lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `x`: input values. + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> x = np.random.rand(1000) * 10 + python> lam = np.random.rand(1000) + python> gen(x, lam, "data.json") + ``` + """ + # Compute CDF values: + z = np.array(planck.logcdf(x, lam)) + + # Store data to be written to file as a dictionary: + data = { + "x": x.tolist(), + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + # Large shape parameter: + x = np.round(np.random.rand(1000) * 10.0) + lam = (np.random.rand(1000) * 10.0) + 10.0 + gen(x, lam, "large_lambda.json") + + # Small shape parameter: + x = np.round(np.random.rand(1000) * 10.0) + lam = np.random.rand(1000) * 0.5 + gen(x, lam, "small_lambda.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/small_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/small_lambda.json new file mode 100644 index 000000000000..7d71196067f8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/fixtures/python/small_lambda.json @@ -0,0 +1 @@ +{"x": [7.0, 3.0, 7.0, 10.0, 7.0, 2.0, 4.0, 7.0, 7.0, 7.0, 7.0, 4.0, 8.0, 3.0, 9.0, 9.0, 6.0, 7.0, 4.0, 9.0, 9.0, 4.0, 10.0, 3.0, 9.0, 4.0, 4.0, 1.0, 0.0, 1.0, 8.0, 9.0, 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of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var logcdf = factory( 0.5 ); + t.equal( typeof logcdf, 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the returned function returns `NaN`', function test( t ) { + var logcdf; + var y; + + logcdf = factory( 0.5 ); + y = logcdf( NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + logcdf = factory( NaN ); + y = logcdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a valid `lambda`, the function returns a function which returns `0` when provided `+infinity` for `x`', function test( t ) { + var logcdf; + var y; + + logcdf = factory( 0.5 ); + y = logcdf( PINF ); + t.equal( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a valid `lambda`, the function returns a function which returns `-Infinity` when provided a negative number for `x`', function test( t ) { + var logcdf; + var y; + + logcdf = factory( 0.5 ); + y = logcdf( NINF ); + t.equal( y, NINF, 'returns expected value' ); + + y = logcdf( -20.0 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logcdf( -2.0 ); + t.equal( y, NINF, 'returns expected value' ); + y = logcdf( -0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the returned function always returns `NaN`', function test( t ) { + var logcdf; + var y; + + logcdf = factory( 0.0 ); + + y = logcdf( 2.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = logcdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + logcdf = factory( -1.5 ); + + y = logcdf( 2.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = logcdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the returned function evaluates the logcdf for `x` given small parameter `lambda`', function test( t ) { + var expected; + var logcdf; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = smallLambda.expected; + x = smallLambda.x; + lambda = smallLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + logcdf = factory( lambda[ i ] ); + y = logcdf( x[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the returned function evaluates the logcdf for `x` given small parameter `lambda`', function test( t ) { + var expected; + var logcdf; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = largeLambda.expected; + x = largeLambda.x; + lambda = largeLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + logcdf = factory( lambda[ i ] ); + y = logcdf( x[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/test.js new file mode 100644 index 000000000000..fe65bdf1a764 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var logcdf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logcdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `logcdf` functions', function test( t ) { + t.equal( typeof logcdf.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/test.logcdf.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/test.logcdf.js new file mode 100644 index 000000000000..4a3770dde3a6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logcdf/test/test.logcdf.js @@ -0,0 +1,133 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var logcdf = require( './../lib' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logcdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = logcdf( NaN, 0.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = logcdf( 4.0, NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `lambda`, the function returns `0`', function test( t ) { + var y = logcdf( PINF, 0.5 ); + t.equal( y, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a negative number for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) { + var y = logcdf( NINF, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logcdf( -4.0, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logcdf( -0.5, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a value shape parameter `lambda` which nonpositive, the function returns `NaN`', function test( t ) { + var y; + + y = logcdf( 3.0, 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = logcdf( 3.0, -1.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the logcdf for `x` given small parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = smallLambda.expected; + x = smallLambda.x; + lambda = smallLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + y = logcdf( x[ i ], lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the logcdf for `x` given large parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = largeLambda.expected; + x = largeLambda.x; + lambda = largeLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + y = logcdf( x[ i ], lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md new file mode 100644 index 000000000000..bd177c1db4d7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md @@ -0,0 +1,152 @@ + + +# Logarithm of Probability Mass Function + +> Evaluate the logarithm of the [probability mass function][pmf] (PMF) for a Planck (discrete exponential) distribution. + +
+ +The [probability mass function][pmf] (PMF) for a Planck random variable is defined as + + + +```math +\Pr(X = x, \lambda) = \begin{cases}(1 - e^{-\lambda})e^{-\lambda x} & \text{for } x = 0, 1, 2, \ldots \\ 0 & \text{otherwise} \end{cases} +``` + + + +where `λ` is the shape parameter and `x` denotes the count of events in a quantized system. + +
+ + + +
+ +## Usage + +```javascript +var logpmf = require( '@stdlib/stats/base/dists/planck/logpmf' ); +``` + +#### logpmf( x, lambda ) + +Evaluates the logarithm of the [probability mass function][pmf] (PMF) of a Planck (discrete exponential) distribution with shape parameter `lambda`. + +```javascript +var y = logpmf( 4.0, 0.3 ); +// returns ~-2.5502 + +y = logpmf( 2.0, 1.7 ); +// returns ~-3.6017 + +y = logpmf( -1.0, 2.5 ); +// returns -Infinity +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = logpmf( NaN, 0.0 ); +// returns NaN + +y = logpmf( 0.0, NaN ); +// returns NaN +``` + +If provided a shape parameter `lambda` which is nonpositive number, the function returns `NaN`. + +```javascript +var y = logpmf( 2.0, -1.0 ); +// returns NaN +``` + +#### logpmf.factory( lambda ) + +Returns a function for evaluating the logarithm of the [probability mass function][pmf] (PMF) of a Planck (discrete exponential) distribution with shape parameter `lambda`. + +```javascript +var mylogpmf = logpmf.factory( 0.5 ); +var y = mylogpmf( 3.0 ); +// returns ~-2.4328 + +y = mylogpmf( 1.0 ); +// returns ~-1.4328 +``` + +
+ + + +
+ +## Notes + +- In virtually all cases, using the `logpmf` or `logcdf` functions is preferable to manually computing the logarithm of the `pmf` or `cdf`, respectively, since the latter is prone to overflow and underflow. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logpmf = require( '@stdlib/stats/base/dists/planck/logpmf' ); + +var x = discreteUniform( 10, 0, 5 ); +var lambda = uniform( 10, 0.1, 5.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = logpmf( x[ i ], lambda[ i ] ); + console.log( 'x: %d, λ: %d, ln( P( X = x; λ ) ): %d', x[ i ], lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js new file mode 100644 index 000000000000..2d48249bfa8f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var logpmf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var x; + var y; + var i; + + x = discreteUniform( 100, 0, 40 ); + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logpmf( x[ i % x.length ], lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+':factory', function benchmark( b ) { + var mylogpmf; + var x; + var y; + var i; + + x = discreteUniform( 100, 0, 40 ); + mylogpmf = logpmf.factory( 0.3 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mylogpmf( x[ i % x.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt new file mode 100644 index 000000000000..1ae67dfc813e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt @@ -0,0 +1,64 @@ + +{{alias}}( x, λ ) + Evaluates the logarithm of the probability mass function (PMF) for a Planck + distribution with shape parameter `λ` at a value `x`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + λ: number + Shape parameter. + + Returns + ------- + out: number + Evaluated logPMF. + + Examples + -------- + > var y = {{alias}}( 4.0, 0.3 ) + ~-2.5502 + > y = {{alias}}( 2.0, 1.7 ) + ~-3.6017 + > y = {{alias}}( -1.0, 2.5 ) + -Infinity + > y = {{alias}}( 0.0, NaN ) + NaN + > y = {{alias}}( NaN, 0.5 ) + NaN + // Invalid shape parameter: + > y = {{alias}}( 2.0, -1.0 ) + NaN + + +{{alias}}.factory( λ ) + Returns a function for evaluating the logarithm of the probability mass + function (PMF) of a Planck distribution with shape parameter `λ`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + logpmf: Function + Logarithm of the probability mass function (PMF). + + Examples + -------- + > var mylogpmf = {{alias}}.factory( 0.5 ); + > var y = mylogpmf( 3.0 ) + ~-2.4328 + > y = mylogpmf( 1.0 ) + ~-1.4328 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts new file mode 100644 index 000000000000..387dba3e316d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts @@ -0,0 +1,114 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the natural logarithm of the probability mass function (PMF) for a Planck distribution. +* +* @param x - input value +* @returns evaluated PMF +*/ +type Unary = ( x: number ) => number; + +/** +* Interface for the natural logarithm of the probability mass function (PMF) of a Planck distribution. +*/ +interface LogPMF { + /** + * Evaluates the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda` at a value `x`. + * + * ## Notes + * + * - If `lambda <= 0`, the function returns `NaN`. + * + * @param x - input value + * @param lambda - shape parameter + * @returns logarithm of PMF + * + * @example + * var y = logpmf( 4.0, 0.3 ); + * // returns ~-2.5502 + * + * @example + * var y = logpmf( 2.0, 1.7 ); + * // returns ~-3.6017 + * + * @example + * var y = logpmf( -1.0, 2.5 ); + * // returns -Infinity + * + * @example + * var y = logpmf( 0.0, NaN ); + * // returns NaN + * + * @example + * var y = logpmf( NaN, 0.5 ); + * // returns NaN + * + * @example + * // Invalid shape parameter: + * var y = logpmf( 2.0, -1.0 ); + * // returns NaN + */ + ( x: number, lambda: number ): number; + + /** + * Returns a function for evaluating the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda`. + * + * @param lambda - shape parameter + * @returns logPMF + * + * @example + * var mylogpmf = logpmf.factory( 0.5 ); + * var y = mylogpmf( 3.0 ); + * // returns ~-2.4327 + * + * y = mylogpmf( 1.0 ); + * // returns ~-1.4327 + */ + factory( lambda: number ): Unary; +} + +/** +* Evaluates the natural logarithm of the probability mass function (PMF) for a Planck distribution. +* +* @param x - input value +* @param lambda - shape parameter +* @returns evaluated logPMF +* +* @example +* var y = logpmf( 4.0, 0.3 ); +* // returns ~-2.5502 +* +* y = logpmf( 2.0, 1.7 ); +* // returns ~-3.6017 +* +* var mylogpmf = logpmf.factory( 0.5 ); +* y = mylogpmf( 3.0 ); +* // returns ~-2.4327 +* +* y = mylogpmf( 1.0 ); +* // returns ~-1.4327 +*/ +declare var logPMF: LogPMF; + + +// EXPORTS // + +export = logPMF; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts new file mode 100644 index 000000000000..344fadf696c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import logpmf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + logpmf( 2.0, 0.4 ); // $ExpectType number + logpmf( 1.0, 0.2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + logpmf( true, 0.3 ); // $ExpectError + logpmf( false, 0.2 ); // $ExpectError + logpmf( '5', 0.1 ); // $ExpectError + logpmf( [], 0.1 ); // $ExpectError + logpmf( {}, 0.4 ); // $ExpectError + logpmf( ( x: number ): number => x, 0.2 ); // $ExpectError + + logpmf( 0.0, true ); // $ExpectError + logpmf( 1.0, false ); // $ExpectError + logpmf( 0.0, '5' ); // $ExpectError + logpmf( 1.0, [] ); // $ExpectError + logpmf( 2.0, {} ); // $ExpectError + logpmf( 3.0, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + logpmf(); // $ExpectError + logpmf( 0.0 ); // $ExpectError + logpmf( 1.0, 0.3, 4.0 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + logpmf.factory( 0.4 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = logpmf.factory( 0.4 ); + fcn( 2.0 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided an invalid argument... +{ + const fcn = logpmf.factory( 0.4 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = logpmf.factory( 0.4 ); + fcn(); // $ExpectError + fcn( 2.0, 0.0 ); // $ExpectError + fcn( 2.0, 0.0, 1.0 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided a value other than a number... +{ + logpmf.factory( true ); // $ExpectError + logpmf.factory( false ); // $ExpectError + logpmf.factory( '5' ); // $ExpectError + logpmf.factory( [] ); // $ExpectError + logpmf.factory( {} ); // $ExpectError + logpmf.factory( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + logpmf.factory( 0.0, 0.2 ); // $ExpectError + logpmf.factory( 0.0, 0.4, 8.0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js new file mode 100644 index 000000000000..5f47a89e33a2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var logpmf = require( './../lib' ); + +var x = discreteUniform( 10, 0, 5 ); +var lambda = uniform( 10, 0.1, 5.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = logpmf( x[ i ], lambda[ i ] ); + console.log( 'x: %d, λ: %d, ln( P( X = x; λ ) ): %d', x[ i ], lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js new file mode 100644 index 000000000000..9a02a76317c8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var constantFunction = require( '@stdlib/utils/constant-function' ); +var isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// MAIN // + +/** +* Returns a function for evaluating the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda`. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {Function} logPMF +* +* @example +* var logpmf = factory( 0.5 ); +* var y = logpmf( 3.0 ); +* // returns ~-2.4328 +* +* y = logpmf( 1.0 ); +* // returns ~-1.4328 +*/ +function factory( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return constantFunction( NaN ); + } + return logpmf; + + /** + * Evaluates the logarithm of the probability mass function (PMF) for a Planck distribution. + * + * @private + * @param {number} x - input value + * @returns {NonPositiveNumber} evaluated logPMF + * + * @example + * var y = logpmf( 2.0 ); + * // returns + */ + function logpmf( x ) { + if ( isnan( x ) ) { + return NaN; + } + if ( isNonNegativeInteger( x ) ) { + return ln( -expm1( -lambda ) ) - ( lambda * x ); + } + return NINF; + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js new file mode 100644 index 000000000000..1084bd9a8c43 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Evaluate the logarithm of the probability mass function (PMF) for a Planck distribution. +* +* @module @stdlib/stats/base/dists/planck/logpmf +* +* @example +* var logpmf = require( '@stdlib/stats/base/dists/planck/logpmf' ); +* +* var y = logpmf( 4.0, 0.3 ); +* // returns ~-2.5502 +* +* y = logpmf( 2.0, 1.7 ); +* // returns ~-3.6017 +* +* y = logpmf( -1.0, 0.5 ); +* // returns 0.0 +* +* var mylogpmf = logpmf.factory( 0.5 ); +* y = mylogpmf( 3.0 ); +* // returns ~-2.4328 +* +* y = mylogpmf( 1.0 ); +* // returns ~-1.4328 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js new file mode 100644 index 000000000000..be92ba4b2b82 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// MAIN // + +/** +* Evaluates the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda` at a value `x`. +* +* @param {number} x - input value +* @param {PositiveNumber} lambda - shape parameter +* @returns {NonPositiveNumber} logarithm of PMF +* +* @example +* var y = logpmf( 4.0, 0.3 ); +* // returns ~-2.5502 +* +* @example +* var y = logpmf( 2.0, 1.7 ); +* // returns ~-3.6017 +* +* @example +* var y = logpmf( -1.0, 2.5 ); +* // returns -Infinity +* +* @example +* var y = logpmf( 0.0, NaN ); +* // returns NaN +* +* @example +* var y = logpmf( NaN, 0.5 ); +* // returns NaN +* +* @example +* // Invalid shape parameter: +* var y = logpmf( 2.0, -1.0 ); +* // returns NaN +*/ +function logpmf( x, lambda ) { + if ( isnan( x ) || isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + if ( isNonNegativeInteger( x ) ) { + return ln( -expm1( -lambda ) ) - ( lambda * x ); + } + return NINF; +} + + +// EXPORTS // + +module.exports = logpmf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json new file mode 100644 index 000000000000..e13245ee25e9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/stats/base/dists/planck/logpmf", + "version": "0.0.0", + "description": "Evaluate the logarithm of the probability mass function (PMF) for a Planck (discrete exponential) distribution.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "probability", + "pmf", + "discrete distribution", + "logarithm", + "log", + "planck", + "univariate", + "discrete" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json new file mode 100644 index 000000000000..d4cd2afb2208 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json @@ -0,0 +1 @@ +{"x": [9.0, 9.0, 2.0, 6.0, 0.0, 7.0, 3.0, 4.0, 5.0, 7.0, 1.0, 5.0, 10.0, 3.0, 1.0, 4.0, 6.0, 10.0, 5.0, 1.0, 5.0, 1.0, 6.0, 9.0, 0.0, 5.0, 3.0, 2.0, 3.0, 5.0, 8.0, 2.0, 3.0, 7.0, 9.0, 2.0, 1.0, 4.0, 7.0, 9.0, 5.0, 7.0, 9.0, 8.0, 6.0, 4.0, 4.0, 1.0, 9.0, 3.0, 0.0, 4.0, 9.0, 9.0, 6.0, 2.0, 2.0, 3.0, 5.0, 0.0, 7.0, 3.0, 2.0, 1.0, 1.0, 6.0, 7.0, 2.0, 8.0, 8.0, 8.0, 10.0, 6.0, 5.0, 0.0, 8.0, 9.0, 7.0, 1.0, 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-18.22954671445832, -65.41596038935964, -48.88975342259694, -18.08800068455605, -42.82273589414573, -19.394064067896135, -57.84342414438852, -8.251711681356683e-09, -48.954686296706754, -128.74017593587388, -51.63429621026194, -126.31313983692363, -104.77656078038574, -35.36925473784508, -2.1559084638994216e-08, -78.72663319366525, -82.35806195031994, -56.37939070246653, -118.27528380924296, -100.74914064628851, -176.4274833073821, -124.22703621365697]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py new file mode 100644 index 000000000000..1ccc2449f54e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py @@ -0,0 +1,87 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(x, lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `x`: input values. + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> x = np.random.rand(1000) * 10.0 + python> lam = np.random.rand(1000) + python> gen(x, lam, "data.json") + ``` + """ + # Compute PDF values: + z = np.array(planck.logpmf(x, lam)) + + # Store data to be written to file as a dictionary: + data = { + "x": x.tolist(), + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + # Large shape parameter: + x = np.round(np.random.rand(1000) * 10.0) + lam = (np.random.rand(1000) * 10.0) + 10.0 + gen(x, lam, "large_lambda.json") + + # Small shape parameter: + x = np.round(np.random.rand(1000) * 10.0) + lam = np.random.rand(1000) * 0.5 + gen(x, lam, "small_lambda.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json new file mode 100644 index 000000000000..e80bd8696bdd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json @@ -0,0 +1 @@ +{"x": [9.0, 2.0, 5.0, 6.0, 7.0, 7.0, 8.0, 2.0, 3.0, 0.0, 5.0, 5.0, 9.0, 3.0, 6.0, 2.0, 6.0, 8.0, 5.0, 4.0, 3.0, 1.0, 6.0, 7.0, 2.0, 1.0, 7.0, 6.0, 1.0, 8.0, 9.0, 2.0, 6.0, 0.0, 3.0, 3.0, 1.0, 1.0, 6.0, 2.0, 3.0, 3.0, 7.0, 3.0, 6.0, 4.0, 5.0, 3.0, 1.0, 9.0, 2.0, 3.0, 5.0, 10.0, 4.0, 2.0, 6.0, 8.0, 4.0, 1.0, 5.0, 7.0, 1.0, 5.0, 5.0, 1.0, 0.0, 0.0, 3.0, 7.0, 1.0, 6.0, 9.0, 1.0, 5.0, 8.0, 1.0, 6.0, 2.0, 4.0, 1.0, 8.0, 8.0, 9.0, 4.0, 9.0, 7.0, 4.0, 5.0, 1.0, 8.0, 8.0, 8.0, 3.0, 1.0, 6.0, 4.0, 4.0, 1.0, 1.0, 5.0, 2.0, 3.0, 7.0, 1.0, 2.0, 7.0, 3.0, 2.0, 9.0, 5.0, 4.0, 4.0, 5.0, 1.0, 4.0, 1.0, 4.0, 0.0, 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-2.5185913125775534, -3.5933472284387658]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js new file mode 100644 index 000000000000..c697773630ab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js @@ -0,0 +1,190 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var logpmf = factory( 0.5 ); + t.equal( typeof logpmf, 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the returned function returns `NaN`', function test( t ) { + var logpmf; + var y; + + logpmf = factory( 0.5 ); + y = logpmf( NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + logpmf = factory( NaN ); + y = logpmf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided `+infinity` for `x`', function test( t ) { + var logpmf; + var y; + + logpmf = factory( 1.0 ); + y = logpmf( PINF ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided a negative integer for `x`', function test( t ) { + var logpmf; + var y; + + logpmf = factory( 0.4 ); + y = logpmf( -4.0 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( -1.0 ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided a non-integer for `x`', function test( t ) { + var logpmf; + var y; + + logpmf = factory( 0.4 ); + y = logpmf( 1.3 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( 1.4 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( 3.2 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( 4.8 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( -1.2 ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `lambda` which is nonpositive, the returned function always returns `NaN`', function test( t ) { + var logpmf; + var y; + + logpmf = factory( 0.0 ); + + y = logpmf( 2.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = logpmf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + logpmf = factory( -1.5 ); + + y = logpmf( 2.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = logpmf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the returned function evaluates the logpmf for `x` given small `lambda`', function test( t ) { + var expected; + var logpmf; + var lambda; + var delta; + var tol; + var i; + var x; + var y; + + expected = smallLambda.expected; + x = smallLambda.x; + lambda = smallLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + logpmf = factory( lambda[ i ] ); + y = logpmf( x[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[i], 'x: '+x[ i ]+'. lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the returned function evaluates the logpmf for `x` given large `lambda`', function test( t ) { + var expected; + var logpmf; + var lambda; + var delta; + var tol; + var i; + var x; + var y; + + expected = largeLambda.expected; + x = largeLambda.x; + lambda = largeLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + logpmf = factory( lambda[ i ] ); + y = logpmf( x[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[i], 'x: '+x[ i ]+'. lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js new file mode 100644 index 000000000000..5d2d6e2f6a68 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var logpmf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logpmf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `logpmf` functions', function test( t ) { + t.equal( typeof logpmf.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js new file mode 100644 index 000000000000..42721405ea14 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var logpmf = require( './../lib' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logpmf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = logpmf( NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = logpmf( 0.0, NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) { + var y = logpmf( PINF, 0.01 ); + t.equal( y, NINF, 'returns -Infinity' ); + t.end(); +}); + +tape( 'if provided a negative integer for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) { + var y = logpmf( -20.0, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( -4.0, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a non-integer for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) { + var y = logpmf( -1.3, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + y = logpmf( 2.4, 0.5 ); + t.equal( y, NINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function always returns `NaN`', function test( t ) { + var y; + + y = logpmf( 2.0, 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = logpmf( 0.0, -1.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the logpmf for `x` given small parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = smallLambda.expected; + x = smallLambda.x; + lambda = smallLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + y = logpmf( x[ i ], lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+'. lambda:'+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the logpmf for `x` given large parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = largeLambda.expected; + x = largeLambda.x; + lambda = largeLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + y = logpmf( x[ i ], lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+'. lambda:'+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/median/README.md new file mode 100644 index 000000000000..f4c5107b5519 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/README.md @@ -0,0 +1,139 @@ + + +# Median + +> Planck (discrete exponential) distribution [median][median]. + + + +
+ +The [median][median] for a Planck random variable is + + + +```math +\mathop{\mathrm{Median}}\left( X \right) = \left\lceil -\frac{\ln(0.5)}{\lambda} \right\rceil \!-1 +``` + + + +where `λ` is the shape parameter. + +
+ + + + + +
+ +## Usage + +```javascript +var median = require( '@stdlib/stats/base/dists/planck/median' ); +``` + +#### median( lambda ) + +Returns the [median][median] of a Planck distribution with shape parameter `lambda`. + +```javascript +var v = median( 0.1 ); +// returns 6 + +v = median( 1.5 ); +// returns 0 +``` + +If provided a shape parameter `lambda` which is nonpositive or `NaN`, the function returns `NaN`. + +```javascript +var v = median( NaN ); +// returns NaN + +v = median( -1.5 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var median = require( '@stdlib/stats/base/dists/planck/median' ); + +var lambda = uniform( 10, 0.1, 10.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = median( lambda[ i ] ); + console.log( 'λ: %d, Median(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[median]: https://en.wikipedia.org/wiki/Median + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/median/benchmark/benchmark.js new file mode 100644 index 000000000000..8ddf131c5afe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var median = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var y; + var i; + + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = median( lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/repl.txt new file mode 100644 index 000000000000..fd6a3c87419e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/repl.txt @@ -0,0 +1,26 @@ + +{{alias}}( λ ) + Returns the median of a Planck distribution with shape parameter `λ`. + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + out: integer + Median. + + Examples + -------- + > var v = {{alias}}( 0.1 ) + 6 + > v = {{alias}}( 1.5 ) + 0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/types/index.d.ts new file mode 100644 index 000000000000..986814388b6c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the median of a Planck distribution. +* +* ## Notes +* +* - If `lambda <= 0`, the function returns `NaN`. +* +* @param lambda - shape parameter +* @returns median +* +* @example +* var v = median( 0.1 ); +* // returns 6 +* +* @example +* var v = median( 1.5 ); +* // returns 0 +* +* @example +* var v = median( -1.1 ); +* // returns NaN +* +* @example +* var v = median( NaN ); +* // returns NaN +*/ +declare function median( lambda: number ): number; + + +// EXPORTS // + +export = median; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/types/test.ts new file mode 100644 index 000000000000..bd0c67d3e16c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import median = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + median( 0.3 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + median( true ); // $ExpectError + median( false ); // $ExpectError + median( null ); // $ExpectError + median( undefined ); // $ExpectError + median( '5' ); // $ExpectError + median( [] ); // $ExpectError + median( {} ); // $ExpectError + median( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + median(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/median/examples/index.js new file mode 100644 index 000000000000..f87f00f66111 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var median = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 10.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = median( lambda[ i ] ); + console.log( 'λ: %d, Median(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/median/lib/index.js new file mode 100644 index 000000000000..024a4937b034 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Planck distribution median. +* +* @module @stdlib/stats/base/dists/planck/median +* +* @example +* var median = require( '@stdlib/stats/base/dists/planck/median' ); +* +* var v = median( 0.1 ); +* // returns 6 +* +* v = median( 1.5 ); +* // returns 0 +*/ + +// MODULES // + +var median = require( './main.js' ); + + +// EXPORTS // + +module.exports = median; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/median/lib/main.js new file mode 100644 index 000000000000..bfb1aaaaf87b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/lib/main.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var ln = require( '@stdlib/math/base/special/ln' ); + + +// MAIN // + +/** +* Returns the median of a Planck distribution. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {NonNegativeInteger} median +* +* @example +* var v = median( 0.1 ); +* // returns 6 +* +* @example +* var v = median( 1.5 ); +* // returns 0 +* +* @example +* var v = median( -1.1 ); +* // returns NaN +* +* @example +* var v = median( NaN ); +* // returns NaN +*/ +function median( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + return ceil( -ln( 0.5 ) / lambda ) - 1.0; +} + + +// EXPORTS // + +module.exports = median; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/median/package.json new file mode 100644 index 000000000000..9b9a3fd74a1c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/stats/base/dists/geometric/median", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution median.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "parameter", + "memoryless", + "life-time", + "discrete", + "median", + "quantile", + "location", + "percentile", + "order", + "planck", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/planck/median/test/fixtures/python/data.json new file mode 100644 index 000000000000..ecf98b16e41d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/test/fixtures/python/data.json @@ -0,0 +1 @@ +{"lambda": [0.6289730391502801, 0.5171096148794918, 14.178194791576393, 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+#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> lam = np.random.rand(1000) * 20 + python> gen(lam, "data.json") + ``` + """ + # Compute median values: + z = np.array(planck.median(lam)) + + # Store data to be written to file as a dictionary: + data = { + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + lam = np.random.rand(1000) * 20.0 + gen(lam, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/median/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/median/test/test.js new file mode 100644 index 000000000000..7f7ad9d77436 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/median/test/test.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var median = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof median, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) { + var v = median( NaN ); + t.equal( isnan( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) { + var v; + + v = median( 0.0 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + v = median( -1.1 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the median of a Planck distribution', function test( t ) { + var expected; + var lambda; + var i; + var y; + + expected = data.expected; + lambda = data.lambda; + for ( i = 0; i < expected.length; i++ ) { + y = median( lambda[ i ] ); + t.equal( y, expected[ i ], 'lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/README.md new file mode 100644 index 000000000000..c0230d074d18 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/README.md @@ -0,0 +1,157 @@ + + +# Moment-Generating Function + +> Planck (discrete exponential) distribution moment-generating function (MGF). + + + +
+ +The [moment-generating function][mgf] for a Planck random variable is + + + +```math +M_X(t) := \mathbb{E}\!\left[e^{tX}\right] = \frac{1 - e^{-\lambda}}{1 - e^{t - \lambda}} +``` + + + +where `λ` is the shape parameter. + +
+ + + + + +
+ +## Usage + +```javascript +var mgf = require( '@stdlib/stats/base/dists/planck/mgf' ); +``` + +#### mgf( t, lambda ) + +Evaluates the moment-generating function ([MGF][mgf]) of a Planck (discrete exponential) distribution with shape parameter `lambda`. + +```javascript +var y = mgf( 0.2, 0.5 ); +// returns ~1.5181 + +y = mgf( 0.4, 1.5 ); +// returns ~1.1645 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = mgf( NaN, 0.0 ); +// returns NaN + +y = mgf( 0.0, NaN ); +// returns NaN +``` + +If provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`. + +```javascript +var y = mgf( 2.0, -1.0 ); +// returns NaN +``` + +#### mgf.factory( lambda ) + +Returns a function for evaluating the [moment-generating function][mgf] of a Planck (discrete exponential) distribution with shape parameter `lambda`. + +```javascript +var mymgf = mgf.factory( 0.8 ); +var y = mymgf( -0.2 ); +// returns ~0.8711 +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var mgf = require( '@stdlib/stats/base/dists/planck/mgf' ); + +var lambda = uniform( 10, 0.1, 5.0 ); +var t = uniform( 10, 0.0, 10.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = mgf( t[ i ], lambda[ i ] ); + console.log( 't: %d, λ: %d, M_X(t;λ): %d', t[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mgf]: https://en.wikipedia.org/wiki/Moment-generating_function + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js new file mode 100644 index 000000000000..f40aad933643 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/benchmark/benchmark.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var mgf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var t; + var y; + var i; + + lambda = uniform( 100, 0.1, 10.0 ); + t = uniform( 100, 0.0, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mgf( t[ i % t.length ], lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+':factory', function benchmark( b ) { + var mymgf; + var t; + var y; + var i; + + t = uniform( 100, 0.0, 10.0 ); + mymgf = mgf.factory( 0.3 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mymgf( t[ i % t.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/repl.txt new file mode 100644 index 000000000000..f628063e0fdf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/repl.txt @@ -0,0 +1,59 @@ + +{{alias}}( t, λ ) + Evaluates the moment-generating function (MGF) for a Planck distribution + with shape parameter `λ` at a value `t`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + t: number + Input value. + + λ: number + Shape parameter. + + Returns + ------- + out: number + Evaluated MGF. + + Examples + -------- + > var y = {{alias}}( 0.2, 0.5 ) + ~1.5181 + > y = {{alias}}( 0.4, 1.5 ) + ~1.1645 + > y = {{alias}}( NaN, 0.0 ) + NaN + > y = {{alias}}( 0.0, NaN ) + NaN + > y = {{alias}}( 2.0, -1.0 ) + NaN + + +{{alias}}.factory( λ ) + Returns a function for evaluating the moment-generating function (MGF) of a + Planck distribution with shape parameter `λ`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + mgf: Function + Moment-generating function (MGF). + + Examples + -------- + > var mymgf = {{alias}}.factory( 0.8 ); + > var y = mymgf( -0.2 ) + ~0.8711 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/types/index.d.ts new file mode 100644 index 000000000000..74eff51f795d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/types/index.d.ts @@ -0,0 +1,103 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the moment-generating function (MGF) of a Planck distribution. +* +* @param t - input value +* @returns evaluated MGF +*/ +type Unary = ( t: number ) => number; + +/** +* Interface for the moment-generating function (MGF) of a Planck distribution. +*/ +interface MGF { + /** + * Evaluates the moment-generating function (MGF) for a Planck distribution with shape parameter `lambda` at a value `t`. + * + * ## Notes + * + * - If `lambda <= 0`, the function returns `NaN`. + * + * @param t - input value + * @param lambda - shape parameter + * @returns evaluated MGF + * + * @example + * var y = mgf( 0.2, 0.5 ); + * // returns ~1.5181 + * + * @example + * var y = mgf( 0.4, 1.5 ); + * // returns ~1.1645 + * + * @example + * var y = mgf( NaN, 0.0 ); + * // returns NaN + * + * @example + * var y = mgf( 0.0, NaN ); + * // returns NaN + * + * @example + * var y = mgf( 2.0, -1.0 ); + * // returns NaN + */ + ( t: number, lambda: number ): number; + + /** + * Returns a function for evaluating the moment-generating function (MGF) of a Planck distribution with shape parameter `lambda`. + * + * @param lambda - shape parameter + * @returns MGF + * + * @example + * var mymgf = mgf.factory( 0.8 ); + * var y = mymgf( -0.2 ); + * // returns ~0.8711 + */ + factory( lambda: number ): Unary; +} + +/** +* Planck distribution moment-generating function (MGF). +* +* @param t - input value +* @param lambda - shape parameter +* @returns evaluated MGF +* +* @example +* var y = mgf( 0.2, 0.5 ); +* // returns ~1.5181 +* +* y = mgf( 0.4, 1.5 ); +* // returns ~1.1645 +* +* var mymgf = mgf.factory( 0.8 ); +* y = mymgf( -0.2 ); +* // returns ~0.8711 +*/ +declare var mgf: MGF; + + +// EXPORTS // + +export = mgf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/types/test.ts new file mode 100644 index 000000000000..e80a2a7bc4fa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/docs/types/test.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import mgf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + mgf( 2.0, 0.4 ); // $ExpectType number + mgf( 1.0, 0.2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + mgf( true, 0.3 ); // $ExpectError + mgf( false, 0.2 ); // $ExpectError + mgf( '5', 0.1 ); // $ExpectError + mgf( [], 0.1 ); // $ExpectError + mgf( {}, 0.4 ); // $ExpectError + mgf( ( x: number ): number => x, 0.2 ); // $ExpectError + + mgf( 9.0, true ); // $ExpectError + mgf( 9.0, false ); // $ExpectError + mgf( 5.0, '5' ); // $ExpectError + mgf( 8.0, [] ); // $ExpectError + mgf( 9.0, {} ); // $ExpectError + mgf( 8.0, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + mgf(); // $ExpectError + mgf( 2.0 ); // $ExpectError + mgf( 2.0, 0.8, 4.0 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + mgf.factory( 0.4 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = mgf.factory( 0.4 ); + fcn( 2.0 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided an invalid argument... +{ + const fcn = mgf.factory( 0.4 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = mgf.factory( 0.4 ); + fcn(); // $ExpectError + fcn( 2.0, 0.8 ); // $ExpectError + fcn( 2.0, 0.9, 1.0 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided a value other than a number... +{ + mgf.factory( true ); // $ExpectError + mgf.factory( false ); // $ExpectError + mgf.factory( '5' ); // $ExpectError + mgf.factory( [] ); // $ExpectError + mgf.factory( {} ); // $ExpectError + mgf.factory( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + mgf.factory( 0.9, 0.2 ); // $ExpectError + mgf.factory( 0.8, 0.4, 8.0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/examples/index.js new file mode 100644 index 000000000000..dc49b4e37075 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/examples/index.js @@ -0,0 +1,32 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var mgf = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 5.0 ); +var t = uniform( 10, 0.0, 10.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = mgf( t[ i ], lambda[ i ] ); + console.log( 't: %d, λ: %d, M_X(t;λ): %d', t[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/factory.js new file mode 100644 index 000000000000..c8d6031767d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/factory.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var constantFunction = require( '@stdlib/utils/constant-function' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); + + +// MAIN // + +/** +* Returns a function for evaluating the moment-generating function (MGF) of a Planck distribution with shape parameter `lambda`. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {Function} MGF +* +* @example +* var mgf = factory( 0.8 ); +* var y = mgf( -0.2 ); +* // returns ~0.8711 +*/ +function factory( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return constantFunction( NaN ); + } + return mgf; + + /** + * Evaluates the moment-generating function (MGF) for a Planck distribution. + * + * @private + * @param {number} t - input value + * @returns {number} evaluated MGF + * + * @example + * var y = mgf( 0.5 ); + * // returns + */ + function mgf( t ) { + if ( isnan( t ) ) { + return NaN; + } + return expm1( -lambda ) / expm1( t - lambda ); + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/index.js new file mode 100644 index 000000000000..363a2cd6081b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Evaluate the moment-generating function (MGF) for a Planck distribution. +* +* @module @stdlib/stats/base/dists/planck/mgf +* +* @example +* var mgf = require( '@stdlib/stats/base/dists/planck/mgf' ); +* +* var y = mgf( 0.2, 0.5 ); +* // returns ~1.5181 +* +* y = mgf( 0.4, 1.5 ); +* // returns ~1.1645 +* +* var mymgf = mgf.factory( 0.8 ); +* y = mymgf( -0.2 ); +* // returns ~0.8711 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/main.js new file mode 100644 index 000000000000..3c9742edf52d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/lib/main.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var expm1 = require( '@stdlib/math/base/special/expm1' ); + + +// MAIN // + +/** +* Evaluates the moment-generating function (MGF) for a Planck distribution with shape parameter `lambda` at a value `t`. +* +* @param {number} t - input value +* @param {PositiveNumber} lambda - shape parameter +* @returns {number} evaluated MGF +* +* @example +* var y = mgf( 0.2, 0.5 ); +* // returns ~1.5181 +* +* @example +* var y = mgf( 0.4, 1.5 ); +* // returns ~1.1645 +* +* @example +* var y = mgf( NaN, 0.0 ); +* // returns NaN +* +* @example +* var y = mgf( 0.0, NaN ); +* // returns NaN +* +* @example +* var y = mgf( 2.0, -1.0 ); +* // returns NaN +*/ +function mgf( t, lambda ) { + if ( isnan( t ) || isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + return expm1( -lambda ) / expm1( t - lambda ); +} + + +// EXPORTS // + +module.exports = mgf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/package.json new file mode 100644 index 000000000000..4776d211666e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/stats/base/dists/planck/mgf", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution moment-generating function (MGF).", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "mgf", + "generating functions", + "moments", + "memoryless", + "life-time", + "discrete", + "planck", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/large_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/large_lambda.json new file mode 100644 index 000000000000..78c4a38595ee --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/large_lambda.json @@ -0,0 +1 @@ +{"x": [5.0, 2.0, 4.0, 7.0, 6.0, 8.0, 2.0, 10.0, 9.0, 7.0, 5.0, 1.0, 2.0, 1.0, 1.0, 4.0, 7.0, 4.0, 5.0, 8.0, 4.0, 6.0, 6.0, 3.0, 3.0, 6.0, 8.0, 4.0, 8.0, 3.0, 7.0, 5.0, 3.0, 7.0, 3.0, 4.0, 1.0, 2.0, 8.0, 2.0, 1.0, 7.0, 2.0, 2.0, 7.0, 1.0, 0.0, 1.0, 6.0, 10.0, 10.0, 2.0, 10.0, 1.0, 1.0, 8.0, 2.0, 2.0, 0.0, 4.0, 3.0, 8.0, 3.0, 3.0, 10.0, 7.0, 9.0, 6.0, 4.0, 5.0, 7.0, 2.0, 6.0, 10.0, 8.0, 7.0, 7.0, 4.0, 1.0, 1.0, 4.0, 8.0, 1.0, 6.0, 10.0, 7.0, 6.0, 5.0, 2.0, 7.0, 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000000000000..019716218341 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/runner.py @@ -0,0 +1,86 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(x, lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `x`: input values. + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> x = np.random.rand(1000) * 10.0 + python> lam = np.random.rand(1000) + python> gen(x, lam, "data.json") + ``` + """ + # Compute MGF values: + z = np.array(np.expm1(-lam) / np.expm1(x - lam)) + + # Store data to be written to file as a dictionary: + data = { + "x": x.tolist(), + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + # Large shape parameter: + x = np.round(np.random.rand(1000) * 10.0) + lam = (np.random.rand(1000) * 10.0) + 10.0 + gen(x, lam, "large_lambda.json") + + # Small shape parameter: + x = np.round(np.random.rand(1000) * 10.0) + lam = np.random.rand(1000) * 0.5 + gen(x, lam, "small_lambda.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/small_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/small_lambda.json new file mode 100644 index 000000000000..546ffd9d31c6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/fixtures/python/small_lambda.json @@ -0,0 +1 @@ +{"x": [6.0, 2.0, 1.0, 7.0, 7.0, 8.0, 9.0, 2.0, 0.0, 6.0, 1.0, 8.0, 5.0, 2.0, 5.0, 1.0, 5.0, 10.0, 2.0, 3.0, 9.0, 2.0, 2.0, 0.0, 9.0, 8.0, 3.0, 9.0, 3.0, 3.0, 2.0, 2.0, 0.0, 4.0, 4.0, 4.0, 8.0, 2.0, 2.0, 6.0, 6.0, 5.0, 1.0, 5.0, 6.0, 6.0, 5.0, 8.0, 8.0, 1.0, 10.0, 1.0, 2.0, 2.0, 4.0, 5.0, 5.0, 4.0, 5.0, 7.0, 6.0, 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Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var mgf = factory( 0.5 ); + t.equal( typeof mgf, 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the returned function returns `NaN`', function test( t ) { + var mgf; + var y; + + mgf = factory( 0.5 ); + y = mgf( NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + mgf = factory( NaN ); + y = mgf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the returned function always returns `NaN`', function test( t ) { + var mgf; + var y; + + mgf = factory( 0.0 ); + y = mgf( 2.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = mgf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + mgf = factory( -1.0 ); + y = mgf( 2.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = mgf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the returned function evaluates the mgf for `x` given small parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var mgf; + var tol; + var x; + var y; + var i; + + expected = smallLambda.expected; + x = smallLambda.x; + lambda = smallLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + mgf = factory( lambda[ i ] ); + y = mgf( x[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the returned function evaluates the mgf for `x` given large parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var mgf; + var tol; + var x; + var y; + var i; + + expected = largeLambda.expected; + x = largeLambda.x; + lambda = largeLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + mgf = factory( lambda[ i ] ); + y = mgf( x[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/test.js new file mode 100644 index 000000000000..9b8d315bdad7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var mgf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mgf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `mgf` functions', function test( t ) { + t.equal( typeof mgf.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/test.mgf.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/test.mgf.js new file mode 100644 index 000000000000..7869c11968a8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mgf/test/test.mgf.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var mgf = require( './../lib' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mgf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = mgf( NaN, 0.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = mgf( 4.0, NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) { + var y; + + y = mgf( 3.0, 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = mgf( 3.0, -0.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the mgf for `x` given small parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = smallLambda.expected; + x = smallLambda.x; + lambda = smallLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + y = mgf( x[ i ], lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the mgf for `x` given large parameter `lambda`', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var x; + var y; + var i; + + expected = largeLambda.expected; + x = largeLambda.x; + lambda = largeLambda.lambda; + for ( i = 0; i < x.length; i++ ) { + y = mgf( x[ i ], lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 2.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md new file mode 100644 index 000000000000..0d62c5c213a4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md @@ -0,0 +1,137 @@ + + +# Mode + +> Planck (discrete exponential) distribution [mode][mode]. + + + +
+ +The [mode][mode] for a Planck random variable with shape parameter `λ` is + + + +```math +\mathop{\mathrm{mode}}\left( X \right) = 0 +``` + + + +
+ + + + + +
+ +## Usage + +```javascript +var mode = require( '@stdlib/stats/base/dists/planck/mode' ); +``` + +#### mode( lambda ) + +Returns the [mode][mode] of a Planck distribution with shape parameter `lambda`. + +```javascript +var v = mode( 0.1 ); +// returns 0 + +v = mode( 1.5 ); +// returns 0 +``` + +If provided a shape parameter `lambda` is nonpositive or `NaN`, the function returns `NaN`. + +```javascript +var v = mode( NaN ); +// returns NaN + +v = mode( -1.5 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var mode = require( '@stdlib/stats/base/dists/planck/mode' ); + +var lambda = uniform( 10, 0.1, 5.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = mode( lambda[ i ] ); + console.log( 'λ: %d, mode(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js new file mode 100644 index 000000000000..8e8500b8b07b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var mode = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var y; + var i; + + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt new file mode 100644 index 000000000000..b4567e8a667f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt @@ -0,0 +1,26 @@ + +{{alias}}( λ ) + Returns the mode of a Planck distribution with shape parameter `λ`. + + If `lambda <= 0`, the function returns `NaN`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + out: integer + Mode. + + Examples + -------- + > var v = {{alias}}( 0.1 ) + 0 + > v = {{alias}}( 1.5 ) + 0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts new file mode 100644 index 000000000000..488fb5289de0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the mode of a Planck distribution. +* +* ## Notes +* +* - If `lambda <= 0`, the function returns `NaN`. +* +* @param lambda - shape parameter +* @returns mode +* +* @example +* var v = mode( 0.1 ); +* // returns 0 +* +* @example +* var v = mode( 1.5 ); +* // returns 0 +* +* @example +* var v = mode( -1.1 ); +* // returns NaN +* +* @example +* var v = mode( NaN ); +* // returns NaN +*/ +declare function mode( lambda: number ): number; + + +// EXPORTS // + +export = mode; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts new file mode 100644 index 000000000000..a1f70068852e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import mode = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + mode( 0.3 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + mode( true ); // $ExpectError + mode( false ); // $ExpectError + mode( null ); // $ExpectError + mode( undefined ); // $ExpectError + mode( '5' ); // $ExpectError + mode( [] ); // $ExpectError + mode( {} ); // $ExpectError + mode( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + mode(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js new file mode 100644 index 000000000000..987223b2b815 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var mode = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 5.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = mode( lambda[ i ] ); + console.log( 'λ: %d, mode(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js new file mode 100644 index 000000000000..06b9e6b178ba --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Planck distribution mode. +* +* @module @stdlib/stats/base/dists/planck/mode +* +* @example +* var mode = require( '@stdlib/stats/base/dists/planck/mode' ); +* +* var v = mode( 0.1 ); +* // returns 0 +* +* v = mode( 1.5 ); +* // returns 0 +*/ + +// MODULES // + +var mode = require( './main.js' ); + + +// EXPORTS // + +module.exports = mode; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js new file mode 100644 index 000000000000..59a3282ae45b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns the mode of a Planck distribution. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {NonNegativeInteger} mode +* +* @example +* var v = mode( 0.1 ); +* // returns 0 +* +* @example +* var v = mode( 1.5 ); +* // returns 0 +* +* @example +* var v = mode( -1.1 ); +* // returns NaN +* +* @example +* var v = mode( NaN ); +* // returns NaN +*/ +function mode( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + return 0; +} + + +// EXPORTS // + +module.exports = mode; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json new file mode 100644 index 000000000000..04c5b8bceac3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/stats/base/dists/planck/mode", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution mode.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "planck", + "parameter", + "memoryless", + "life-time", + "discrete", + "location", + "center", + "mode", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js new file mode 100644 index 000000000000..1a9f3da7a9e6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var mode = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mode, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) { + var v = mode( NaN ); + t.equal( isnan( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) { + var v; + + v = mode( 0.0 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + v = mode( -1.5 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `0.0` as the mode of a Planck distribution', function test( t ) { + var lambda; + var i; + var y; + + lambda = uniform( 10, 0.1, 10.0 ); + + for ( i = 0; i < lambda.length; i++ ) { + y = mode( lambda[ i ] ); + t.equal( y, 0.0, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md new file mode 100644 index 000000000000..68e2a38f95bb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md @@ -0,0 +1,154 @@ + + +# Quantile Function + +> Planck (discrete exponential) distribution [quantile function][quantile-function]. + +
+ +The [quantile function][quantile-function] for a Planck random variable is + + + +```math +Q(p;\lambda) = \left\lceil -\frac{\ln(1-p)}{\lambda} \right\rceil \!-1 +``` + + + +for `0 < p < 1` and where `λ` is the shape parameter. + +
+ + + +
+ +## Usage + +```javascript +var quantile = require( '@stdlib/stats/base/dists/planck/quantile' ); +``` + +#### quantile( p, lambda ) + +Evaluates the [quantile function][quantile-function] for a Planck distribution with shape parameter `lambda` at a probability `p`. + +```javascript +var y = quantile( 0.8, 0.4 ); +// returns 4 + +y = quantile( 0.5, 1.4 ); +// returns 0 + +y = quantile( 0.9, 2.1 ); +// returns 1 +``` + +If provided an input probability `p` outside the interval `[0,1]`, the function returns `NaN`. + +```javascript +var y = quantile( 1.9, 0.5 ); +// returns NaN + +y = quantile( -0.1, 0.5 ); +// returns NaN +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = quantile( NaN, 1.0 ); +// returns NaN + +y = quantile( 0.0, NaN ); +// returns NaN +``` + +If provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`. + +```javascript +var y = quantile( 0.4, -1.0 ); +// returns NaN +``` + +#### quantile.factory( lambda ) + +Returns a function for evaluating the [quantile function][quantile-function] for a Planck distribution with shape parameter `lambda`. + +```javascript +var myquantile = quantile.factory( 0.4 ); +var y = myquantile( 0.4 ); +// returns 1 + +y = myquantile( 0.8 ); +// returns 4 + +y = myquantile( 1.0 ); +// returns Infinity +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var quantile = require( '@stdlib/stats/base/dists/planck/quantile' ); + +var lambda = uniform( 10, 0.1, 10.0 ); +var p = uniform( 10, 0.0, 1.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = quantile( p[ i ], lambda[ i ] ); + console.log( 'p: %d, λ: %d, Q(p;λ): %d', p[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js new file mode 100644 index 000000000000..c4882aa6ecdb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var quantile = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var p; + var y; + var i; + + p = uniform( 100, 0.0, 1.0 ); + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = quantile( p[ i % p.length ], lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+':factory', function benchmark( b ) { + var myquantile; + var p; + var y; + var i; + + myquantile = quantile.factory( 0.3 ); + p = uniform( 100, 0.0, 1.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = myquantile( p[ i % p.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt new file mode 100644 index 000000000000..7ef7c3b90665 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt @@ -0,0 +1,74 @@ + +{{alias}}( p, λ ) + Evaluates the quantile function for a Planck distribution with shape + parameter `λ` at a probability `p`. + + If `p < 0` or `p > 1`, the function returns `NaN`. + + If `λ <= 0`, the function returns `NaN`. + + If provided `NaN` as any argument, the function returns `NaN`. + + Parameters + ---------- + p: number + Input probability. + + λ: number + Shape parameter. + + Returns + ------- + out: number + Evaluated quantile function. + + Examples + -------- + > var y = {{alias}}( 0.8, 0.4 ) + 4 + > y = {{alias}}( 0.5, 1.4 ) + 0 + > y = {{alias}}( 0.9, 2.1 ) + 1 + + > y = {{alias}}( 0.2, -0.1 ) + NaN + + > y = {{alias}}( NaN, 0.8 ) + NaN + > y = {{alias}}( 0.4, NaN ) + NaN + + > y = {{alias}}( -0.5, 1.0 ) + NaN + > y = {{alias}}( 1.5, 1.0 ) + NaN + + +{{alias}}.factory( λ ) + Returns a function for evaluating the quantile function of a Planck + distribution with shape parameter `λ`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + quantile: Function + Quantile function. + + Examples + -------- + > var myquantile = {{alias}}.factory( 0.4 ); + > var y = myquantile( 0.4 ) + 1 + > y = myquantile( 0.8 ) + 4 + > y = myquantile( 1.0 ) + Infinity + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts new file mode 100644 index 000000000000..190f02fb9c86 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts @@ -0,0 +1,132 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the quantile function for a Planck distribution. +* +* ## Notes +* +* - If `p < 0` or `p > 1`, the function returns `NaN`. +* +* @param p - input value +* @returns evaluated quantile function +*/ +type Unary = ( p: number ) => number; + +/** +* Interface for the quantile function of a Planck distribution. +*/ +interface Quantile { + /** + * Evaluates the quantile function for a Planck distribution with shape parameter `lambda` at a probability `p`. + * + * ## Notes + * + * - If `p < 0` or `p > 1`, the function returns `NaN`. + * - If `lambda <= 0`, the function returns `NaN`. + * + * @param p - input value + * @param lambda - shape parameter + * @returns evaluated quantile function + * + * @example + * var y = quantile( 0.8, 0.4 ); + * // returns 4 + * + * @example + * var y = quantile( 0.5, 1.4 ); + * // returns 0 + * + * @example + * var y = quantile( 0.9, 2.1 ); + * // returns 1 + * + * @example + * var y = quantile( 0.2, -0.1 ); + * // returns NaN + * + * @example + * var y = quantile( NaN, 0.8 ); + * // returns NaN + * + * @example + * var y = quantile( 0.4, NaN ); + * // returns NaN + * + * @example + * var y = quantile( -0.5, 1.0 ); + * // returns NaN + * + * @example + * var y = quantile( 1.5, 1.0 ); + * // returns NaN + */ + ( p: number, lambda: number ): number; + + /** + * Returns a function for evaluating the quantile function for a Planck distribution with shape parameter `lambda`. + * + * @param lambda - shape parameter + * @returns quantile function + * + * @example + * var myquantile = quantile.factory( 0.4 ); + * var y = myquantile( 0.4 ); + * // returns 1 + * + * y = myquantile( 0.8 ); + * // returns 4 + * + * y = myquantile( 1.0 ); + * // returns Infinity + */ + factory( lambda: number ): Unary; +} + +/** +* Evaluates the quantile function for a Planck distribution with shape parameter `lambda` at a probability `p`. +* +* @param p - input value +* @param lambda - shape parameter +* @returns evaluated quantile function +* +* @example +* var y = quantile( 0.8, 0.4 ); +* // returns 4 +* +* y = quantile( 0.5, 1.4 ); +* // returns 0 +* +* var myquantile = quantile.factory( 0.4 ); +* y = myquantile( 0.4 ); +* // returns 1 +* +* y = myquantile( 0.8 ); +* // returns 4 +* +* y = myquantile( 1.0 ); +* // returns Infinity +*/ +declare var quantile: Quantile; + + +// EXPORTS // + +export = quantile; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts new file mode 100644 index 000000000000..99fbca207304 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import quantile = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + quantile( 0.2, 0.2 ); // $ExpectType number + quantile( 0.1, 0.2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + quantile( true, 0.3 ); // $ExpectError + quantile( false, 0.2 ); // $ExpectError + quantile( '5', 0.1 ); // $ExpectError + quantile( [], 0.1 ); // $ExpectError + quantile( {}, 0.2 ); // $ExpectError + quantile( ( x: number ): number => x, 0.2 ); // $ExpectError + + quantile( 0.9, true ); // $ExpectError + quantile( 0.9, false ); // $ExpectError + quantile( 0.5, '5' ); // $ExpectError + quantile( 0.8, [] ); // $ExpectError + quantile( 0.9, {} ); // $ExpectError + quantile( 0.8, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + quantile(); // $ExpectError + quantile( 0.2 ); // $ExpectError + quantile( 0.2, 0.8, 4.0 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + quantile.factory( 0.3 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = quantile.factory( 0.3 ); + fcn( 0.2 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided an invalid argument... +{ + const fcn = quantile.factory( 0.3 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = quantile.factory( 0.3 ); + fcn(); // $ExpectError + fcn( 0.2, 0.8 ); // $ExpectError + fcn( 0.2, 0.8, 1.0 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided a value other than a number... +{ + quantile.factory( true ); // $ExpectError + quantile.factory( false ); // $ExpectError + quantile.factory( '5' ); // $ExpectError + quantile.factory( [] ); // $ExpectError + quantile.factory( {} ); // $ExpectError + quantile.factory( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + quantile.factory( 0.2, 0.2 ); // $ExpectError + quantile.factory( 0.3, 0.4, 8.0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js new file mode 100644 index 000000000000..a6d226c46b3f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js @@ -0,0 +1,32 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var quantile = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 10.0 ); +var p = uniform( 10, 0.0, 1.0 ); + +var y; +var i; +for ( i = 0; i < lambda.length; i++ ) { + y = quantile( p[ i ], lambda[ i ] ); + console.log( 'p: %d, λ: %d, Q(p;λ): %d', p[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js new file mode 100644 index 000000000000..07c75e225c4a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var constantFunction = require( '@stdlib/utils/constant-function' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); + + +// MAIN // + +/** +* Returns a function for evaluating the quantile function for a Planck distribution with shape parameter `lambda`. +* +* @param {PositiveNumber} lambda - success probability +* @returns {Function} quantile function +* +* @example +* var quantile = factory( 0.4 ); +* var y = quantile( 0.4 ); +* // returns 1 +* +* y = quantile( 0.8 ); +* // returns 4 +* +* y = quantile( 1.0 ); +* // returns Infinity +*/ +function factory( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return constantFunction( NaN ); + } + return quantile; + + /** + * Evaluates the quantile function for a Planck distribution. + * + * @private + * @param {Probability} p - input value + * @returns {NonNegativeInteger} evaluated quantile function + * + * @example + * var y = quantile( 0.3 ); + * // returns + */ + function quantile( p ) { + if ( isnan( p ) || p < 0.0 || p > 1.0 ) { + return NaN; + } + if ( p === 1.0 ) { + return PINF; + } + return ceil( -ln( 1.0-p ) / lambda ) - 1.0; + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js new file mode 100644 index 000000000000..fed299058b43 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Planck distribution quantile function. +* +* @module @stdlib/stats/base/dists/planck/quantile +* +* @example +* var quantile = require( '@stdlib/stats/base/dists/planck/quantile' ); +* +* var y = quantile( 0.8, 0.4 ); +* // returns 4 +* +* y = quantile( 0.5, 1.4 ); +* // returns 0 +* +* var myquantile = quantile.factory( 0.4 ); +* y = myquantile( 0.4 ); +* // returns 1 +* +* y = myquantile( 0.8 ); +* // returns 4 +* +* y = myquantile( 1.0 ); +* // returns Infinity +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js new file mode 100644 index 000000000000..52f5fef9da70 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var ceil = require( '@stdlib/math/base/special/ceil' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); + + +// MAIN // + +/** +* Evaluates the quantile function for a Planck distribution with shape parameter `lambda` at a probability `p`. +* +* @param {Probability} p - input value +* @param {PositiveNumber} lambda - shape parameter +* @returns {NonNegativeInteger} evaluated quantile function +* +* @example +* var y = quantile( 0.8, 0.4 ); +* // returns 4 +* +* @example +* var y = quantile( 0.5, 1.4 ); +* // returns 0 +* +* @example +* var y = quantile( 0.9, 2.1 ); +* // returns 1 +* +* @example +* var y = quantile( 0.2, -0.1 ); +* // returns NaN +* +* @example +* var y = quantile( NaN, 0.8 ); +* // returns NaN +* +* @example +* var y = quantile( 0.4, NaN ); +* // returns NaN +* +* @example +* var y = quantile( -0.5, 1.0 ); +* // returns NaN +* +* @example +* var y = quantile( 1.5, 1.0 ); +* // returns NaN +*/ +function quantile( p, lambda ) { + if ( isnan( lambda ) || isnan( p ) || lambda <= 0.0 || p < 0.0 || p > 1.0 ) { // eslint-disable-line max-len + return NaN; + } + if ( p === 1.0 ) { + return PINF; + } + return ceil( -ln( 1.0-p ) / lambda ) - 1.0; +} + + +// EXPORTS // + +module.exports = quantile; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json new file mode 100644 index 000000000000..84ddb4a3d480 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/stats/base/dists/planck/quantile", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution quantile function.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "probability", + "cdf", + "inverse", + "failure times", + "memoryless property", + "discrete", + "planck", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json new file mode 100644 index 000000000000..1f8d1bd1ebe6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json @@ -0,0 +1 @@ +{"r": [0.9544555848274979, 0.7403580906863967, 0.2519726241201691, 0.9066083415025643, 0.10472160992685564, 0.17746797020152416, 0.9591828428488697, 0.7304673004774859, 0.635565019532496, 0.39282381518757303, 0.4342203791048863, 0.21925873707696664, 0.7533254901997656, 0.9177567133953949, 0.06207527148340519, 0.317107207060741, 0.8223198170589929, 0.5283732324772701, 0.1614598319686854, 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0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py new file mode 100644 index 000000000000..b1744111ade9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py @@ -0,0 +1,87 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(r, lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `r`: input values. + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> r = np.random.rand(1000) + python> lam = np.random.rand(1000) + python> gen(r, lam, "data.json") + ``` + """ + # Compute quantile values: + z = np.array(planck.ppf(r, lam)) + + # Store data to be written to file as a dictionary: + data = { + "r": r.tolist(), + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + # Large shape parameter: + r = np.random.rand(1000) + lam = (np.random.rand(1000) * 10.0) + 10.0 + gen(r, lam, "large_lambda.json") + + # Small shape parameter: + r = np.random.rand(1000) + lam = np.random.rand(1000) * 0.5 + gen(r, lam, "small_lambda.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json new file mode 100644 index 000000000000..cbf983cd1c69 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json @@ -0,0 +1 @@ +{"r": [0.7462536237075819, 0.19432916923683086, 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0.16499186431854396, 0.24319045913569454, 0.4891479310920348, 0.30583871351935094, 0.20789349840985388, 0.39744095118313977, 0.04854803175466449, 0.33806436380706195, 0.04723106615341849, 0.17873198484177066, 0.44154110676648983, 0.09230673856219923, 0.38317699275312656, 0.22086763814192456, 0.17800014193230435, 0.13909126746505607, 0.061648750703262034, 0.1991565563069308, 0.09268104438782748, 0.06834640441743906, 0.37367962408410066, 0.16187978374664408, 0.1056392711140497, 0.4215798287087052, 0.1860622850149361, 0.48765844562290256, 0.3803440527463615, 0.05122190860983045, 0.2408112306693338, 0.14188537037411147, 0.3114262790274082, 0.30458028154493266, 0.4135087771036594, 0.21806541506001825, 0.17983384616824233, 0.4641139597289056, 0.1682319349093499, 0.17628487498832335, 0.019539465643411913, 0.20412690765591435, 0.48913402775586334, 0.35012109658318635, 0.43143185983479, 0.15276996734980747, 0.28758157482818686, 0.4171174643788504, 0.11765815968789611, 0.2560853322208503, 0.48357837954827565, 0.34714331338781523, 0.21857838127797963, 0.08126451863400713, 0.23152785982718854, 0.0013770746799243727, 0.4629003824149525, 0.03339461615623318, 0.08302273211338956, 0.014655526853111722, 0.3691859112450707, 0.08490373611458107, 0.27774962137845477, 0.4498659350608322, 0.4677924594470558, 0.04875329521878452, 0.09773678783621065, 0.496891547006969, 0.21911464988631996, 0.1243297060264737, 0.33420771146710343, 0.3463391639562473, 0.3490748974151434, 0.14098048035786453, 0.0850319004239013, 0.0952738715732509, 0.3795144032366342, 0.11607394676352528, 0.18761322168482775, 0.4601644632964441, 0.037338429973916065, 0.38879336890933236, 0.233884228404926, 0.17952556347060433, 0.08673669835462833, 0.24331910388992523, 0.04769202736559991, 0.006364373594645978, 0.2283782914970261, 0.43751799270696234, 0.15788662961373207, 0.023420568356262272, 0.14061280042682128, 0.051227239042442974, 0.21596087450415502, 0.0447780192783116, 0.04207963750123189, 0.19620841691344137, 0.4322974560649247, 0.18629037854619312, 0.04257814199198201, 0.3584065545962655, 0.21169204557012655, 0.4412078267375418, 0.3773947513702056, 0.3622855105465947, 0.287745357501777, 0.28235301726464135, 0.07718763863636241, 0.2824312405945318, 0.01149765149581744, 0.17325661474097376, 0.33979390035919244, 0.17175853192528528, 0.3188151067828781, 0.015405519970635662, 0.11244723538708196, 0.32419906686241984, 0.21092554205578556, 0.39306973830684383, 0.052656669164593384, 0.49405587960270136, 0.12492455813471798, 0.4973486606250149, 0.4469915989166607, 0.2725290908550184, 0.1294130105833003, 0.021189191940719998, 0.2345648377380991, 0.08248362775918716, 0.34741599364344955, 0.4600149952794051, 0.2127354291890105, 0.02224448741928986, 0.27384644401718866, 0.40497757995586425, 0.22866275196120667, 0.31167379745387375, 0.22444482239468033, 0.26627658857843917, 0.3701284200164505, 0.17995804020050304, 0.3083140410256097, 0.35382850242722025, 0.4928990291064823, 0.011006821420119717, 0.07216961337769395, 0.3290914774054746, 0.14451087895453812, 0.20680276160472594, 0.10774561258664966, 0.4409283392524962, 0.07560486934029209, 0.13239208082425374, 0.04698671716135566, 0.44949254386276083, 0.37072331308391765, 0.3823184691882801, 0.40237184472619875, 0.21956771597339708, 0.3801936148869511, 0.12040728292818281, 0.24799521438142513, 0.38279516062878655, 0.40171825788199284, 0.25026839514149424, 0.40126870033606754, 0.41973766404165, 0.3083999870763011, 0.4143048382112812, 0.14348027481619013, 0.037000385665188984, 0.4610760888774248, 0.3963678578892963, 0.22249594014859825, 0.022464460009485765, 0.47043362146660406, 0.0008925725442541221, 0.3644348722358255, 0.2692582883547171, 0.3013408677701271, 0.46781754939859443, 0.49071887997882974, 0.36771715459826876, 0.38625474557923306, 0.3705709866754393, 0.1993506115157394, 0.2081425580475324, 0.15078191129155627, 0.402875478529422, 0.3598768230154652, 0.3432418493954254, 0.15888072654854968, 0.4297017037767549, 0.43570895607747695, 0.11194432569424495, 0.024789451634363302, 0.06515441580042775, 0.05634555983527506, 0.043675643780008044, 0.32234356858552116, 0.36792766229383683, 0.10602691236942124, 0.42410530968172067, 0.4848920026227695, 0.05820648366105702], "expected": [11.0, 6.0, 12.0, 7.0, 3.0, 0.0, 3.0, 2.0, 1.0, 1.0, 11.0, 2.0, 31.0, 9.0, 10.0, 3.0, 1.0, 3.0, 3.0, 0.0, 1.0, 204.0, 2.0, 2.0, 1.0, 7.0, 0.0, 6.0, 7.0, 1.0, 0.0, 13.0, 32.0, 2.0, 3.0, 9.0, 21.0, 2.0, 11.0, 2.0, 552.0, 16.0, 34.0, 17.0, 2.0, 2.0, 1.0, 27.0, 5.0, 4.0, 54.0, 3.0, 7.0, 1.0, 57.0, 66.0, 1.0, 1.0, 6.0, 2.0, 0.0, 0.0, 0.0, 5.0, 38.0, 30.0, 3.0, 5.0, 0.0, 0.0, 0.0, 1.0, 63.0, 4.0, 2.0, 32.0, 6.0, 1.0, 8.0, 0.0, 11.0, 4.0, 11.0, 0.0, 0.0, 2.0, 3.0, 3.0, 0.0, 310.0, 0.0, 0.0, 4.0, 3.0, 19.0, 0.0, 0.0, 7.0, 0.0, 0.0, 3.0, 10.0, 5.0, 1.0, 0.0, 25.0, 0.0, 19.0, 1.0, 605.0, 0.0, 6.0, 0.0, 0.0, 0.0, 1.0, 30.0, 5.0, 6.0, 3.0, 0.0, 1.0, 6.0, 4.0, 1.0, 0.0, 0.0, 19.0, 8.0, 7.0, 2.0, 6.0, 4.0, 0.0, 0.0, 1.0, 36.0, 0.0, 13.0, 61.0, 1.0, 0.0, 0.0, 9.0, 4.0, 3.0, 0.0, 4.0, 1.0, 13.0, 10.0, 71.0, 2.0, 14.0, 6.0, 1.0, 9.0, 1.0, 0.0, 5.0, 0.0, 1.0, 1.0, 5.0, 10.0, 18.0, 3.0, 3.0, 6.0, 4.0, 0.0, 2.0, 2.0, 0.0, 7.0, 0.0, 74.0, 1.0, 3.0, 1.0, 21.0, 0.0, 2.0, 0.0, 59.0, 0.0, 0.0, 3.0, 1.0, 5.0, 4.0, 4.0, 5.0, 0.0, 6.0, 0.0, 2.0, 7.0, 14.0, 1.0, 29.0, 5.0, 0.0, 1.0, 0.0, 4.0, 5.0, 18.0, 22.0, 9.0, 474.0, 1.0, 2.0, 1.0, 1.0, 16.0, 4.0, 8.0, 54.0, 2.0, 0.0, 21.0, 3.0, 5.0, 5.0, 2.0, 0.0, 2.0, 101.0, 0.0, 3.0, 2.0, 11.0, 25.0, 2.0, 1.0, 3.0, 21.0, 2.0, 1.0, 1.0, 10.0, 1.0, 1.0, 1.0, 3.0, 2.0, 4.0, 109.0, 0.0, 10.0, 2.0, 6.0, 11.0, 0.0, 7.0, 1.0, 27.0, 5.0, 8.0, 1.0, 5.0, 5.0, 0.0, 5.0, 10.0, 4.0, 4.0, 6.0, 11.0, 1.0, 9.0, 7.0, 1.0, 0.0, 0.0, 1.0, 1.0, 5.0, 1.0, 15.0, 10.0, 3.0, 0.0, 0.0, 28.0, 6.0, 39.0, 0.0, 0.0, 0.0, 28.0, 0.0, 11.0, 2.0, 1.0, 0.0, 517.0, 14.0, 0.0, 0.0, 2.0, 1.0, 0.0, 2.0, 11.0, 14.0, 0.0, 0.0, 1.0, 0.0, 6.0, 1.0, 7.0, 7.0, 6.0, 8.0, 8.0, 8.0, 3.0, 2.0, 0.0, 4.0, 3.0, 5.0, 0.0, 11.0, 9.0, 3.0, 4.0, 0.0, 16.0, 0.0, 8.0, 0.0, 5.0, 1.0, 7.0, 0.0, 3.0, 4.0, 0.0, 0.0, 3.0, 2.0, 0.0, 552.0, 0.0, 0.0, 81.0, 8.0, 0.0, 5.0, 2.0, 69.0, 8.0, 8.0, 34.0, 0.0, 3.0, 0.0, 13.0, 1.0, 18.0, 2.0, 0.0, 0.0, 4.0, 4.0, 3.0, 47.0, 0.0, 4.0, 11.0, 6.0, 7.0, 3.0, 59.0, 3.0, 0.0, 0.0, 5.0, 2.0, 1.0, 0.0, 2.0, 24.0, 8.0, 0.0, 77.0, 15.0, 4.0, 18.0, 1.0, 0.0, 4.0, 0.0, 3.0, 0.0, 0.0, 2.0, 0.0, 1.0, 4.0, 0.0, 3.0, 4.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 8.0, 4.0, 2.0, 0.0, 0.0, 2.0, 13.0, 0.0, 1.0, 29.0, 2.0, 14.0, 6.0, 56.0, 9.0, 4.0, 1.0, 1.0, 2.0, 6.0, 2.0, 11.0, 8.0, 5.0, 5.0, 2.0, 6.0, 0.0, 42.0, 63.0, 19.0, 2.0, 78.0, 112.0, 0.0, 0.0, 0.0, 12.0, 0.0, 2.0, 0.0, 0.0, 1.0, 16.0, 8.0, 6.0, 5.0, 1.0, 8.0, 6.0, 2.0, 1.0, 1.0, 0.0, 16.0, 13313.0, 42.0, 0.0, 4.0, 0.0, 9.0, 4.0, 6.0, 1.0, 5.0, 0.0, 4.0, 5.0, 2.0, 1.0, 0.0, 2.0, 0.0, 2.0, 4.0, 5.0, 7.0, 1.0, 0.0, 9.0, 28.0, 17.0, 2.0, 0.0, 0.0, 2.0, 1.0, 5.0, 6.0, 52.0, 1.0, 39.0, 0.0, 6.0, 0.0, 2.0, 0.0, 0.0, 1.0, 0.0, 5.0, 5.0, 0.0, 5.0, 1.0, 0.0, 0.0, 7.0, 0.0, 6.0, 44.0, 36.0, 3.0, 14.0, 7.0, 7.0, 3.0, 3.0, 7.0, 101.0, 12.0, 0.0, 3.0, 3.0, 0.0, 1.0, 0.0, 3.0, 7.0, 1.0, 4.0, 5.0, 3.0, 37.0, 1.0, 3.0, 2.0, 4.0, 6.0, 2.0, 0.0, 2.0, 1.0, 1.0, 0.0, 16.0, 0.0, 2.0, 10.0, 0.0, 3.0, 6.0, 9.0, 2.0, 0.0, 102.0, 2.0, 3.0, 3.0, 0.0, 4.0, 5.0, 66.0, 0.0, 2.0, 10.0, 0.0, 329.0, 7.0, 0.0, 17.0, 136.0, 1.0, 3.0, 11.0, 3.0, 6.0, 3.0, 4.0, 0.0, 6.0, 4.0, 0.0, 0.0, 7.0, 0.0, 9.0, 8.0, 1.0, 9.0, 5.0, 2.0, 1.0, 0.0, 19.0, 2.0, 8.0, 2.0, 0.0, 0.0, 18.0, 1.0, 3.0, 4.0, 4.0, 10.0, 7.0, 9.0, 13.0, 0.0, 4.0, 4.0, 2.0, 2.0, 0.0, 5.0, 3.0, 0.0, 22.0, 1.0, 17.0, 8.0, 187.0, 4.0, 0.0, 10.0, 108.0, 2.0, 78.0, 13.0, 47.0, 1.0, 3.0, 0.0, 0.0, 5.0, 2.0, 3.0, 3.0, 4.0, 57.0, 74.0, 0.0, 1.0, 0.0, 4.0, 5.0, 3.0, 3.0, 3.0, 2.0, 3.0, 1.0, 2.0, 12.0, 5.0, 0.0, 7.0, 5.0, 2.0, 5.0, 7.0, 0.0, 2.0, 1.0, 2.0, 0.0, 7.0, 1.0, 3.0, 0.0, 3.0, 0.0, 2.0, 1.0, 7.0, 0.0, 36.0, 0.0, 19.0, 12.0, 12.0, 4.0, 0.0, 3.0, 7.0, 2.0, 25.0, 7.0, 4.0, 1.0, 1.0, 1.0, 4.0, 1.0, 23.0, 11.0, 9.0, 15.0, 1.0, 11.0, 0.0, 12.0, 5.0, 21.0, 12.0, 4.0, 2.0, 0.0, 2.0, 3.0, 4.0, 2.0, 12.0, 16.0, 6.0, 2.0, 15.0, 7.0, 1.0, 6.0, 0.0, 1.0, 40.0, 0.0, 3.0, 0.0, 4.0, 15.0, 2.0, 14.0, 5.0, 2.0, 10.0, 4.0, 17.0, 2.0, 0.0, 6.0, 2.0, 7.0, 6.0, 10.0, 0.0, 3.0, 7.0, 1.0, 1.0, 1.0, 0.0, 28.0, 1.0, 3.0, 0.0, 7.0, 0.0, 2.0, 0.0, 24.0, 1.0, 4.0, 7.0, 1.0, 1.0, 25.0, 8.0, 6.0, 4.0, 1.0, 2.0, 1.0, 4.0, 12.0, 286.0, 1.0, 20.0, 0.0, 34.0, 1.0, 0.0, 1.0, 5.0, 4.0, 6.0, 2.0, 5.0, 0.0, 0.0, 0.0, 4.0, 0.0, 18.0, 0.0, 1.0, 1.0, 0.0, 0.0, 5.0, 3.0, 20.0, 10.0, 14.0, 54.0, 6.0, 1.0, 4.0, 0.0, 7.0, 1.0, 3.0, 8.0, 28.0, 0.0, 1.0, 0.0, 0.0, 5.0, 4.0, 2.0, 7.0, 0.0, 11.0, 0.0, 1.0, 5.0, 1.0, 10.0, 3.0, 0.0, 11.0, 2.0, 2.0, 0.0, 6.0, 13.0, 6.0, 1321.0, 1.0, 19.0, 2.0, 19.0, 1.0, 1.0, 0.0, 1.0, 1.0, 8.0, 10.0, 1.0, 1.0, 19.0, 3.0, 1.0, 4.0, 0.0, 7.0, 24.0, 2.0, 55.0, 1.0, 1.0, 77.0, 4.0, 4.0, 0.0, 4.0, 3.0, 1.0, 189.0, 28.0, 2.0, 0.0, 13.0, 6.0, 14.0, 10.0, 9.0, 94.0, 7.0, 3.0, 17.0, 3.0, 1.0, 3.0, 2.0, 1.0, 0.0, 0.0, 0.0, 1.0, 5.0, 149.0, 11.0, 2.0, 0.0, 0.0, 147.0, 10.0, 9.0, 2.0, 1.0, 39.0, 4.0, 5.0, 1.0, 1.0, 5.0, 9.0, 35.0, 0.0, 6.0, 2.0, 2.0, 21.0, 114.0, 1.0, 0.0, 7.0, 0.0, 1.0, 7.0, 2.0, 0.0, 0.0, 0.0, 2.0, 38.0, 9.0, 4.0, 3.0, 2.0, 13.0, 1.0, 0.0, 2.0, 11.0, 2.0, 6.0, 2.0, 3.0, 5.0, 3.0, 3.0, 2.0, 0.0, 6.0, 2.0, 4.0, 0.0, 3.0, 7.0, 1.0, 45.0, 3.0, 1.0, 1.0, 2.0, 0.0, 1230.0, 1.0, 0.0, 0.0, 2.0, 5.0, 1.0, 0.0, 2.0, 2.0, 8.0, 6.0, 0.0, 2.0, 4.0, 16.0, 6.0, 3.0, 3.0, 12.0, 77.0, 8.0, 3.0, 1.0, 6.0, 7.0, 0.0, 0.0, 1.0]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js new file mode 100644 index 000000000000..c2d4f8ddfa2b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var quantile = factory( 1.0 ); + t.equal( typeof quantile, 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the returned function returns `NaN`', function test( t ) { + var quantile; + var y; + + quantile = factory( 1.0 ); + y = quantile( NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + quantile = factory( NaN ); + y = quantile( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a valid shape parameter `lambda`, the function returns a function which returns `NaN` when provided a number outside `[0,1]` for `p`', function test( t ) { + var quantile; + var y; + + quantile = factory( 0.8 ); + y = quantile( -0.1 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = quantile( 1.1 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a valid shape parameter `lambda`, the function returns a function which returns `+Infinity` when provided `1.0` for `p`', function test( t ) { + var quantile; + var y; + + quantile = factory( 0.5 ); + y = quantile( 1.0 ); + t.equal( y, PINF, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the returned function always returns `NaN`', function test( t ) { + var quantile; + var y; + + quantile = factory( -1.0 ); + + y = quantile( 0.4 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = quantile( 0.8 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + quantile = factory( 0.0 ); + + y = quantile( 0.4 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = quantile( 0.8 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the returned function evaluates the quantile for `p` given small parameter `lambda`', function test( t ) { + var quantile; + var expected; + var lambda; + var p; + var y; + var i; + + expected = smallLambda.expected; + p = smallLambda.r; + lambda = smallLambda.lambda; + for ( i = 0; i < p.length; i++ ) { + quantile = factory( lambda[ i ] ); + y = quantile( p[ i ] ); + t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } + t.end(); +}); + +tape( 'the returned function evaluates the quantile for `p` given large parameter `lambda`', function test( t ) { + var quantile; + var expected; + var lambda; + var p; + var y; + var i; + + expected = largeLambda.expected; + p = largeLambda.r; + lambda = largeLambda.lambda; + for ( i = 0; i < p.length; i++ ) { + quantile = factory( lambda[ i ] ); + y = quantile( p[ i ] ); + t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js new file mode 100644 index 000000000000..6ad40b0c38e2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var quantile = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof quantile, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `quantile` functions', function test( t ) { + t.equal( typeof quantile.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js new file mode 100644 index 000000000000..a76f7130beaa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var quantile = require( './../lib' ); + + +// FIXTURES // + +var smallLambda = require( './fixtures/python/small_lambda.json' ); +var largeLambda = require( './fixtures/python/large_lambda.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof quantile, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = quantile( NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = quantile( 0.0, NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a number outside `[0,1]` for `p` and a valid `lambda`, the function returns `NaN`', function test( t ) { + var y = quantile( 2.2, 0.8 ); + t.equal( isnan( y ), true, 'returns expected value' ); + y = quantile( -0.2, 0.8 ); + t.equal( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `1.0` for `p` and a valid `lambda`, the function returns `+Infinity`', function test( t ) { + var y = quantile( 1.0, 0.5 ); + t.equal( y, PINF, 'returns expected value' ); + y = quantile( 1.0, 1.5 ); + t.equal( y, PINF, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function always returns `NaN`', function test( t ) { + var y; + + y = quantile( 0.8, -1.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = quantile( 0.9, 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the quantile for `p` given small parameter `lambda`', function test( t ) { + var expected; + var lambda; + var p; + var y; + var i; + + expected = smallLambda.expected; + p = smallLambda.r; + lambda = smallLambda.lambda; + for ( i = 0; i < p.length; i++ ) { + y = quantile( p[ i ], lambda[ i ] ); + t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } + t.end(); +}); + +tape( 'the function evaluates the quantile for `p` given large parameter `lambda`', function test( t ) { + var expected; + var lambda; + var p; + var y; + var i; + + expected = largeLambda.expected; + p = largeLambda.r; + lambda = largeLambda.lambda; + for ( i = 0; i < p.length; i++ ) { + y = quantile( p[ i ], lambda[ i ] ); + t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/README.md new file mode 100644 index 000000000000..1b9f88959fa9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/README.md @@ -0,0 +1,139 @@ + + +# Skewness + +> Planck (discrete exponential) distribution [skewness][skewness]. + + + +
+ +The [skewness][skewness] for a Planck random variable is + + + +```math +\mathop{\mathrm{skew}}\left( X \right) = 2 \cosh\left( \frac{\lambda}{2} \right) +``` + + + +where `λ` is the shape parameter. + +
+ + + + + +
+ +## Usage + +```javascript +var skewness = require( '@stdlib/stats/base/dists/planck/skewness' ); +``` + +#### skewness( lambda ) + +Returns the [skewness][skewness] of a Planck distribution with shape parameter `lambda`. + +```javascript +var v = skewness( 0.1 ); +// returns ~2.0025 + +v = skewness( 1.5 ); +// returns ~2.5894 +``` + +If provided a shape parameter `lambda` which is nonpositive or `NaN`, the function returns `NaN`. + +```javascript +var v = skewness( NaN ); +// returns NaN + +v = skewness( -1.5 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var skewness = require( '@stdlib/stats/base/dists/planck/skewness' ); + +var lambda = uniform( 10, 0.1, 10.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = skewness( lambda[ i ] ); + console.log( 'λ: %d, skew(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[skewness]: https://en.wikipedia.org/wiki/Skewness + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.js new file mode 100644 index 000000000000..1b30b70b4d42 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var skewness = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var lambda; + var y; + var i; + + lambda = uniform( 100, 0.1, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/repl.txt new file mode 100644 index 000000000000..425b21e196ac --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/repl.txt @@ -0,0 +1,26 @@ + +{{alias}}( λ ) + Returns the skewness of a Planck distribution with shape parameter `λ`. + + If `λ <= 0`, the function returns `NaN`. + + Parameters + ---------- + λ: number + Shape parameter. + + Returns + ------- + out: number + Skewness. + + Examples + -------- + > var v = {{alias}}( 0.1 ) + ~2.0025 + > v = {{alias}}( 1.5 ) + ~2.5894 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/types/index.d.ts new file mode 100644 index 000000000000..c9a1bec062e0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the skewness of a Planck distribution. +* +* ## Notes +* +* - If `lambda <= 0`, the function returns `NaN`. +* +* @param lambda - shape parameter +* @returns skewness +* +* @example +* var v = skewness( 0.1 ); +* // returns ~2.0025 +* +* @example +* var v = skewness( 0.5 ); +* // returns ~2.5894 +* +* @example +* var v = skewness( -1.1 ); +* // returns NaN +* +* @example +* var v = skewness( NaN ); +* // returns NaN +*/ +declare function skewness( lambda: number ): number; + + +// EXPORTS // + +export = skewness; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/types/test.ts new file mode 100644 index 000000000000..26fba10eb1c0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import skewness = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + skewness( 0.3 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a value other than a number... +{ + skewness( true ); // $ExpectError + skewness( false ); // $ExpectError + skewness( null ); // $ExpectError + skewness( undefined ); // $ExpectError + skewness( '5' ); // $ExpectError + skewness( [] ); // $ExpectError + skewness( {} ); // $ExpectError + skewness( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + skewness(); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/examples/index.js new file mode 100644 index 000000000000..1e341166e65b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var skewness = require( './../lib' ); + +var lambda = uniform( 10, 0.1, 10.0 ); + +var v; +var i; +for ( i = 0; i < lambda.length; i++ ) { + v = skewness( lambda[ i ] ); + console.log( 'λ: %d, skew(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/lib/index.js new file mode 100644 index 000000000000..97a1d9ad8b0c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Planck distribution skewness. +* +* @module @stdlib/stats/base/dists/planck/skewness +* +* @example +* var skewness = require( '@stdlib/stats/base/dists/planck/skewness' ); +* +* var v = skewness( 0.1 ); +* // returns ~2.0025 +* +* v = skewness( 1.5 ); +* // returns ~2.5894 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/lib/main.js new file mode 100644 index 000000000000..022a23a3b48c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/lib/main.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var cosh = require( '@stdlib/math/base/special/cosh' ); + + +// MAIN // + +/** +* Returns the skewness of a Planck distribution. +* +* @param {PositiveNumber} lambda - shape parameter +* @returns {PositiveNumber} skewness +* +* @example +* var v = skewness( 0.1 ); +* // returns ~2.0025 +* +* @example +* var v = skewness( 1.5 ); +* // returns ~2.5894 +* +* @example +* var v = skewness( -1.1 ); +* // returns NaN +* +* @example +* var v = skewness( NaN ); +* // returns NaN +*/ +function skewness( lambda ) { + if ( isnan( lambda ) || lambda <= 0.0 ) { + return NaN; + } + return 2.0 * cosh( lambda / 2.0 ); +} + + +// EXPORTS // + +module.exports = skewness; diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/package.json new file mode 100644 index 000000000000..bacbffc9da81 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/stats/base/dists/planck/skewness", + "version": "0.0.0", + "description": "Planck (discrete exponential) distribution skewness.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "planck", + "parameter", + "memoryless", + "life-time", + "discrete", + "skewness", + "shape", + "asymmetry", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/fixtures/python/data.json new file mode 100644 index 000000000000..d82c79615415 --- /dev/null +++ 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34.23514953041343, 7.9629217914313415, 98.17115834342174, 2483.6715404626975, 14.472062031682594, 10.657041345434068, 6331.329517178849, 1492.927450286501, 82.22485155939093, 142.71527558971357, 2.6695289302951433, 968.4532782402533, 445.73932190383545, 54.38172859313243, 16409.69229304873, 59.96714090596663, 309.4163115632597, 11.907014843211856, 916.4444511023312, 435.5653456934577, 10316.813093019737, 23.487285680986055, 3146.9794847077997, 14.00238746751978, 1357.5031505031488, 847.9055157296837, 21.51212030429867, 7519.018173510979, 10.772563572021353, 4891.6107216321525, 8.031944151530581, 2.0427941956541567, 392.9963619947581, 265.03910594027997, 14908.157970400542, 148.11485134347484, 7.945439618232594, 3325.483092216036, 2.615405242533715, 13.502302252914891, 4.192715491841906, 5.681815330387705, 4.378525914644072, 34.41291211652198, 15.625255070838792, 431.50039441611307, 21284.45140569013, 41.5418924986568, 2.0105300602924516, 4.531355581739027, 4.207571359039412, 9.73553422999397, 406.65207106114303, 15.603427897262053, 5444.832315797682, 4.683427892128423, 5826.848494431793, 5.807457381467422, 995.67988860784, 4816.952019395016, 13666.540567938298, 558.9815066358127, 50.53450126183816, 131.54411659088288, 170.01258903479587, 1258.4860650705707, 2944.3741685043647, 11.096400992166359, 2.6803202102642327, 482.1743633906592, 437.0932138531305, 168.74207162781252, 1307.5922377770767, 7.85814553953646, 22.271232955834485, 1127.6466465397723, 1251.4242999098533, 793.7852915868351, 676.8708191335206, 16548.91760657923, 16784.085491659724, 2.0908079605113308, 615.9632240341153, 11.851776893330918, 204.2119259806215, 2364.3571362104894, 9.08666530687298, 13344.380598770778, 2.654602008013745, 3.1094900987387417, 1912.6451622341356, 673.0209712402179, 2663.336998556956, 9929.765400454837, 728.34894366737, 64.96648586894356, 6.364596817234627, 236.50292969744493, 3063.902468471734, 187.50190615702687, 2737.7498687877373, 5016.531576660556, 24.758474641323357, 7411.622682703374, 153.73363736272103, 11195.239862477414, 1385.5678028201037, 8442.918815028519, 1243.2604515772339, 4006.8679301214697, 6794.779206833411, 209.17095332329723, 11.151999709695874, 1600.125096614711, 3.1977835232994822, 2.0005619102268937, 3723.2861244510696, 14.34071392867824, 18.613334548844726, 1510.086928367681, 769.4611202523074, 6.472790618986424, 49.935471080817834, 4587.347820389862, 2035.3900782114067, 2086.774151934695, 2.440121124441877, 3.7256970320566833, 366.6904656083727, 20608.29717332783, 11.025602650346693, 13815.73506982644, 11930.260550054007, 7449.429580283021, 3.1422280118936827, 80.16555399145344, 4.266005629354374, 1108.7209712111912, 12017.104028236376, 107.53536355317944, 267.0016359284868, 2437.659080384837, 26.238409545319996, 1239.123421076834, 39.963029739826744, 11916.149980057786, 3.165286342708584, 8612.796363185518, 2.0058068096472166, 82.5505244041639, 11.314865623090073, 329.7489300797214, 12373.383069420155, 259.3571748928393, 400.6262553103766, 11492.946293907538, 1105.9008604297178, 230.99770987365744, 54.80429075496102, 10453.324235734966, 905.0416605256412, 287.77619465702656, 33.588951357894636, 148.67972816119234, 1015.8450806120609, 2597.4317497229913, 2426.265173551227, 11129.43461711627, 6.614223556607466, 4727.9781718328195, 220.9735863057654, 2.0067038280157456, 9006.715825535248, 6900.071560629846, 5029.210774508388, 21.537888455321433, 92.29085144621293, 170.7846699963083, 169.21833005266402, 179.9769293259341, 739.8778862472844, 2.708037721778811, 3304.392127125198, 2877.3986352806614, 10335.997594540377, 17607.74932672675, 11944.69284304029, 112.4994177550001, 5896.820514852757, 106.28803356491537, 14.074686405408746, 31.02146739741237, 3.2752521851058627, 31.6318082492839, 967.385749260259, 2.295113029925404, 6886.547544771195, 213.1379608912251, 1609.4568494693435, 268.46345471207445, 2.0014202220788104, 21942.504502901447, 4824.31921575694, 67.1543186282478, 515.3266984133878, 83.3280418474593, 307.88029029204296, 67.25149732244334, 524.2897569984356, 7142.324229526201, 53.23971228247373, 16415.707170570284, 253.43689410727856, 2277.999163689945, 2.115282044275916, 694.1256080733643, 58.38632400653941, 7.23018331720033, 2.007217768886417, 20168.459847771956, 41.32059468502806, 535.6755036358221, 97.57415547673806, 11381.044179881123, 278.08494822732126, 102.07693612563692, 2.1816003903521364, 1519.5051044619033, 4713.355602636628, 329.54402291478345, 17.20367379661104, 66.03991140782027, 134.1587481592365, 6.89280904527793, 521.0855563351637, 582.2219690717898, 628.706351353299, 490.03298842223546, 127.2243137678857, 6.328473971336484, 72.07561800623404, 2180.0685410926053, 2530.2241310872287, 2554.848402074959, 633.434163349389, 4.649286261487387, 694.1415439593916, 3683.5832075520807, 3.5257353412534913, 21.961473058306265, 2.390340695033904, 2074.909562213169, 20626.02858699527, 48.0575520746593, 3692.814467801816, 9.44156349832076, 3.5698724833535116, 632.9618963635173, 2749.600581926328, 15.146377142406415, 113.24426302833227, 109.17206751984844, 3797.1587848651398, 2.366893638035487, 3967.848481118579, 8.699115931797412, 103.85613781327305, 3.6758259969896887, 278.7052923874606, 72.44823308389341, 360.0642593645328, 2.502709150657873, 80.78273079675492, 153.37753244215662, 41.351608537302134]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/fixtures/python/runner.py new file mode 100644 index 000000000000..1403beb69158 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/fixtures/python/runner.py @@ -0,0 +1,77 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import planck + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(lam, name): + """ + Generate fixture data and write to file. + + # Arguments + + * `lam`: shape parameter. + * `name::str`: output filename. + + # Examples + + ```python + python> lam = np.random.rand(1000) * 20.0 + python> gen(lam, "data.json") + ``` + """ + # Compute skewness values: + z = np.array(planck.stats(lam, moments='s')) + + # Store data to be written to file as a dictionary: + data = { + "lambda": lam.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding='utf-8') as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding='utf-8') as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + lam = np.random.rand(1000) * 20.0 + gen(lam, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/test.js new file mode 100644 index 000000000000..9d861efdcb00 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/planck/skewness/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var skewness = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof skewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) { + var v = skewness( NaN ); + t.equal( isnan( v ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) { + var v; + + v = skewness( 0.0 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + v = skewness( -1.5 ); + t.equal( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the skewness of a Planck distribution', function test( t ) { + var expected; + var lambda; + var delta; + var tol; + var i; + var y; + + expected = data.expected; + lambda = data.lambda; + for ( i = 0; i < expected.length; i++ ) { + y = skewness( lambda[ i ] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/mean/benchmark/c/benchmark.c index f2db5dd54ccf..671f3a57d0eb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/mean/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/mean/benchmark/c/benchmark.c @@ -100,7 +100,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - sigma[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + sigma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md index 07db6a790b4a..66851a14b5b7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md @@ -59,8 +59,7 @@ var median = require( '@stdlib/stats/base/dists/rayleigh/median' ); #### median( sigma ) -Returns the [median][median] of a [Rayleigh][rayleigh-distribution] distribution with scale -parameter `sigma`. +Returns the [median][median] of a [Rayleigh][rayleigh-distribution] distribution with scale parameter `sigma`. ```javascript var y = median( 9.0 ); @@ -119,6 +118,98 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/rayleigh/median.h" +``` + +#### stdlib_base_dists_rayleigh_median( sigma ) + +Returns the [median][median] of a [Rayleigh][rayleigh-distribution] distribution with scale parameter `sigma`. + +```c +double out = stdlib_base_dists_rayleigh_median( 9.0 ); +// returns ~10.595 +``` + +The function accepts the following arguments: + +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_rayleigh_median( const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/rayleigh/median.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + sigma = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_rayleigh_median( sigma ); + printf( "σ: %lf, Median(X;σ): %lf\n", sigma, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js index d4301399c8a4..49af404e2d80 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js @@ -21,6 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var EPS = require( '@stdlib/constants/float64/eps' ); @@ -32,13 +33,19 @@ var median = require( './../lib' ); bench( pkg, function benchmark( b ) { var sigma; + var len; var y; var i; + len = 100; + sigma = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + sigma[ i ] = ( randu() * 20.0 ) + EPS; + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - sigma = ( randu()*20.0 ) + EPS; - y = median( sigma ); + y = median( sigma[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b65c5add32cd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var median = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( median instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var sigma; + var len; + var y; + var i; + + len = 100; + sigma = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + sigma[ i ] = ( randu() * 20.0 ) + EPS; + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = median( sigma[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c new file mode 100644 index 000000000000..66ce848eca30 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/rayleigh/median.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "rayleigh-median" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double sigma[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + sigma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_rayleigh_median( sigma[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c new file mode 100644 index 000000000000..9829c1e36bf6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/rayleigh/median.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + sigma = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_rayleigh_median( sigma ); + printf( "σ: %lf, Median(X;σ): %lf\n", sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' mlim ) { return 0.0; } diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js index 6bec2b634149..e945064d1d48 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js @@ -21,6 +21,7 @@ // MODULES // var isPositiveInteger = require( '@stdlib/math/base/assert/is-positive-integer' ); +var isInteger = require( '@stdlib/math/base/assert/is-integer' ); var isfinite = require( '@stdlib/math/base/assert/is-finite' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var exp = require( '@stdlib/math/base/special/exp' ); @@ -75,6 +76,9 @@ function pdf( x, n ) { ) { return NaN; } + if ( !isInteger( x ) ) { + return 0.0; + } mlim = ( n * ( n + 1 ) ) / 2; if ( x < 0.0 || x > mlim ) { return 0.0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js index 3d4276aaa769..1515b1d0c946 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js @@ -107,6 +107,20 @@ tape( 'if not provided a positive integer for `n`, the created function always r t.end(); }); +tape( 'the created function returns `0` if provided a non-integer for `x`', function test( t ) { + var pdf = factory( 8 ); + var y = pdf( 1.5 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = pdf( 2.5 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = pdf( 0.1 ); + t.equal( y, 0.0, 'returns expected value' ); + + t.end(); +}); + tape( 'the created function evaluates the PDF for `x` given `n` observations', function test( t ) { var expected; var delta; diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js index 287553c021eb..a851772a5ed2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js @@ -80,6 +80,18 @@ tape( 'if not provided a positive integer for `n`, the function returns `NaN`', t.end(); }); +tape( 'the function returns `0` if provided a non-integer for `x`', function test( t ) { + var y = pdf( 1.5, 8 ); + t.equal( y, 0.0, 'returns expected value' ); + t.end(); + + y = pdf( 2.5, 8 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = pdf( 0.1, 4 ); + t.equal( y, 0.0, 'returns expected value' ); +}); + tape( 'the function evaluates the PDF for `x` given `n` observations', function test( t ) { var expected; var delta; diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/benchmark/c/benchmark.c index 552dd9ba3948..b55452e720e5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/benchmark/c/benchmark.c @@ -17,7 +17,6 @@ */ #include "stdlib/stats/base/dists/t/kurtosis.h" -#include "stdlib/constants/float64/eps.h" #include #include #include @@ -100,7 +99,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - v[ i ] = random_uniform( 0.0, 20.0 ) + 2.0 + STDLIB_CONSTANT_FLOAT64_EPS; + v[ i ] = random_uniform( 2.0, 22.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/manifest.json index e362a39c3324..c7b62131d565 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dists/t/kurtosis/manifest.json @@ -56,8 +56,7 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/pinf" ] }, { diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/t/mode/README.md index 080c218db0c4..0c21e786df57 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/t/mode/README.md @@ -206,7 +206,6 @@ int main( void ) { -
diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/t/skewness/benchmark/c/benchmark.c index 6d2d3ffc9510..fc8f2cb75cd2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/skewness/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/t/skewness/benchmark/c/benchmark.c @@ -99,7 +99,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - v[ i ] = random_uniform( 0.0, 20.0 ) + 3.0; + v[ i ] = random_uniform( 3.0, 23.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/benchmark/c/benchmark.c index 7237d0881d76..d274c7cb53b9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/t/stdev/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/t/stdev/benchmark/c/benchmark.c @@ -99,7 +99,7 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - v[ i ] = random_uniform( 0.0, 20.0 ) + 1.0; + v[ i ] = random_uniform( 1.0, 21.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/include/stdlib/stats/base/dists/triangular/entropy.h b/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/include/stdlib/stats/base/dists/triangular/entropy.h index 128382528a78..13668b0d096e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/include/stdlib/stats/base/dists/triangular/entropy.h +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/include/stdlib/stats/base/dists/triangular/entropy.h @@ -27,7 +27,7 @@ extern "C" { #endif /** -* Returns the entropy of a triangular distribution. +* Returns the differential entropy of a triangular distribution. */ double stdlib_base_dists_triangular_entropy( const double a, const double b, const double c ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/src/main.c index 2f6cafecb5f9..4ea33171bd4e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/src/main.c @@ -21,12 +21,12 @@ #include "stdlib/math/base/special/ln.h" /** -* Returns the entropy of a triangular distribution. +* Returns the differential entropy of a triangular distribution. * * @param a minimum support * @param b maximum support * @param c mode -* @return entropy +* @return differential entropy * * @example * double y = stdlib_base_triangular_entropy( 0.0, 1.0, 0.5 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/test/test.native.js index f18a2e067d26..21e172d7c16d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/entropy/test/test.native.js @@ -80,7 +80,7 @@ tape( 'if provided parameters not satisfying `a <= c <= b`, the function returns t.end(); }); -tape( 'the function returns the entropy of a triangular distribution', opts, function test( t ) { +tape( 'the function returns the differential entropy of a triangular distribution', opts, function test( t ) { var expected; var delta; var tol; diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/kurtosis/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/kurtosis/test/test.native.js index 2b2c6e9f432b..163f256d6d71 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/kurtosis/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/kurtosis/test/test.native.js @@ -80,7 +80,7 @@ tape( 'if provided parameters not satisfying `a <= c <= b`, the function returns t.end(); }); -tape( 'the function returns the kurtosis of a triangular distribution', opts, function test( t ) { +tape( 'the function returns the excess kurtosis of a triangular distribution', opts, function test( t ) { var expected; var delta; var tol; diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/README.md index 24706c185e2f..7d86843ff4f5 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/README.md @@ -102,7 +102,7 @@ y = logpdf( 1.0, 0.0, -1.0, 0.5 ); #### logpdf.factory( a, b, c ) -Returns a function for evaluating the natural logarithm of the [probability density function][pdf] (PDF) of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit) and `c` (mode). +Returns a function for evaluating the natural logarithm of the [probability density function][pdf] (PDF) of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit), and `c` (mode). ```javascript var mylogpdf = logpdf.factory( 0.0, 10.0, 5.0 ); @@ -158,6 +158,109 @@ for ( i = 0; i < 25; i++ ) { + + +
+ + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/triangular/logpdf.h" +``` + +#### stdlib_base_dists_triangular_logpdf( x, a, b, c ) + +Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit), and `c` (mode). + +```c +double y = stdlib_base_dists_triangular_logpdf( 0.5, -1.0, 1.0, 0.0 ); +// returns ~-0.693 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **a**: `[in] double` lower limit. +- **b**: `[in] double` upper limit. +- **c**: `[in] double` mode. + +```c +double stdlib_base_dists_triangular_logpdf( const double x, const double a, const double b, const double c ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/triangular/logpdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double c; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 30.0 ); + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c = random_uniform( a, b ); + y = stdlib_base_dists_triangular_logpdf( x, a, b, c ); + printf( "x: %lf, a: %lf, b: %lf, c: %lf, ln(f(x;a,b,c)): %lf\n", x, a, b, c, y ); + } +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.js index 622b1c297b96..b7584d0ab496 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var logpdf = require( './../lib' ); @@ -34,17 +35,27 @@ bench( pkg, function benchmark( b ) { var mode; var min; var max; + var len; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + mode = new Float64Array( len ); + + for ( i = 0; i < len; i++ ) { + x[ i ] = randu() * 30.0; + min[ i ] = randu() * 10.0; + max[ i ] = min[ i ] + ( randu() * 40.0 ) + EPS; + mode[ i ] = min[ i ] + ( ( max[ i ] - min[ i ] ) * randu() ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = randu() * 30.0; - min = randu() * 10.0; - max = min + ( randu() * 40.0 ) + EPS; - mode = min + ( ( max - min ) * randu() ); - y = logpdf( x, min, max, mode ); + y = logpdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..92de1db930bf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/benchmark.native.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var mode; + var min; + var max; + var len; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + mode = new Float64Array( len ); + + for ( i = 0; i < len; i++ ) { + x[ i ] = randu() * 30.0; + min[ i ] = randu() * 10.0; + max[ i ] = min[ i ] + ( randu() * 40.0 ) + EPS; + mode[ i ] = min[ i ] + ( ( max[ i ] - min[ i ] ) * randu() ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = logpdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..3928690c9976 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/benchmark/c/benchmark.c @@ -0,0 +1,145 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/triangular/logpdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "triangular-logpdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double a[ 100 ]; + double b[ 100 ]; + double c[ 100 ]; + double x[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 30.0 ); + a[ i ] = random_uniform( 0.0, 10.0 ); + b[ i ] = random_uniform( a[ i ] + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c[ i ] = random_uniform( a[ i ], b[ i ] ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_triangular_logpdf( x[ i % 100 ], a[ i % 100 ], b[ i % 100 ], c[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/example.c new file mode 100644 index 000000000000..54d24190f1c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/examples/c/example.c @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/triangular/logpdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double c; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 30.0 ); + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c = random_uniform( a, b ); + y = stdlib_base_dists_triangular_logpdf( x, a, b, c ); + printf( "x: %lf, a: %lf, b: %lf, c: %lf, ln(f(x;a,b,c)): %lf\n", x, a, b, c, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' c || + c > b + ) { + return 0.0/0.0; // NaN + } + if ( x < a ) { + return STDLIB_CONSTANT_FLOAT64_NINF; + } + if ( x < c ) { + return STDLIB_CONSTANT_FLOAT64_LN2 + stdlib_base_ln( x - a ) - stdlib_base_ln( c - a ) - stdlib_base_ln( b - a ); + } + if ( x == c ) { + return STDLIB_CONSTANT_FLOAT64_LN2 - stdlib_base_ln( b - a ); + } + if( x <= b ){ + return STDLIB_CONSTANT_FLOAT64_LN2 + stdlib_base_ln( b - x ) - stdlib_base_ln( b - c ) - stdlib_base_ln( b - a ); + } + return STDLIB_CONSTANT_FLOAT64_NINF; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/test/test.native.js new file mode 100644 index 000000000000..68f5ed5a7039 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/logpdf/test/test.native.js @@ -0,0 +1,216 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var ln = require( '@stdlib/math/base/special/ln' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var smallRange = require( './fixtures/julia/small_range.json' ); +var mediumRange = require( './fixtures/julia/medium_range.json' ); +var largeRange = require( './fixtures/julia/large_range.json' ); + + +// VARIABLES // + +var logpdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( logpdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof logpdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = logpdf( NaN, 0.0, 1.0, 0.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, NaN, 1.0, 0.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, 1.0, NaN, 0.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a number greater than `b` for `x` and valid parameters, the function returns `-infinity`', opts, function test( t ) { + var y = logpdf( PINF, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 20.0, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 2.0, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( 1.1, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided a number smaller than `a` for `x` and valid parameters, the function returns `-infinity`', opts, function test( t ) { + var y = logpdf( NINF, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( -20.0, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( -2.0, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + y = logpdf( -0.5, 0.0, 1.0, 0.5 ); + t.equal( y, NINF, 'returns -infinity' ); + + t.end(); +}); + +tape( 'if provided parameters not satisfying `a <= c <= b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = logpdf( 2.0, 3.0, 2.0, 2.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 0.0, 2.0, 3.0, 4.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, 2.0, 3.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = logpdf( 2.0, PINF, NINF, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns `ln(2/(b-a))` if provided `x = c`', opts, function test( t ) { + var a = 0.0; + var b = 2.0; + var c = 1.5; + t.equal( logpdf( c, a, b, c ), ln( 2.0/(b-a) ), 'returns ln(2/(b-a))' ); + t.end(); +}); + +tape( 'the function evaluates the logpdf for `x` given a small range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var c; + var y; + var i; + + expected = smallRange.expected; + x = smallRange.x; + a = smallRange.a; + b = smallRange.b; + c = smallRange.c; + for ( i = 0; i < x.length; i++ ) { + y = logpdf( x[i], a[i], b[i], c[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 40.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the logpdf for `x` given a medium range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var c; + var y; + var i; + + expected = mediumRange.expected; + x = mediumRange.x; + a = mediumRange.a; + b = mediumRange.b; + c = mediumRange.c; + for ( i = 0; i < x.length; i++ ) { + y = logpdf( x[i], a[i], b[i], c[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 60.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the logpdf for `x` given a large range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var c; + var y; + var i; + + expected = largeRange.expected; + x = largeRange.x; + a = largeRange.a; + b = largeRange.b; + c = largeRange.c; + for ( i = 0; i < x.length; i++ ) { + y = logpdf( x[i], a[i], b[i], c[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 50.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/README.md b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/README.md index 1a71e942c293..b536ae5bf161 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/README.md @@ -253,7 +253,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { t = random_uniform( 0.0, 5.0 ); a = random_uniform( 0.0, 10.0 ); - b = random_uniform( a, 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + b = random_uniform( a+STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); c = random_uniform( a, b ); y = stdlib_base_dists_triangular_mgf( t, a, b, c ); printf( "t: %lf, a: %lf, b: %lf, c: %lf, M_X(t;a,b,c): %lf\n", t, a, b, c, y ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/benchmark/c/benchmark.c index 55f908941b48..56927df272dd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/benchmark/c/benchmark.c @@ -105,8 +105,8 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { t[ i ] = random_uniform( 0.0, 5.0 ); a[ i ] = random_uniform( 0.0, 10.0 ); - b[ i ] = random_uniform( a[ i ], 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - c[ i ] = random_uniform( a[ i ], b[ i ]); + b[ i ] = random_uniform( a[ i ]+STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c[ i ] = random_uniform( a[ i ], b[ i ] ); } tc = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/binding.gyp index 507cb00291e7..ec3992233442 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/binding.gyp +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/binding.gyp @@ -167,4 +167,4 @@ ], # end actions }, # end target copy_addon ], # end targets -} \ No newline at end of file +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/examples/c/example.c index ee321df64d85..9807e3b38933 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/examples/c/example.c @@ -37,7 +37,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { t = random_uniform( 0.0, 5.0 ); a = random_uniform( 0.0, 10.0 ); - b = random_uniform( a, 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + b = random_uniform( a+STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); c = random_uniform( a, b ); y = stdlib_base_dists_triangular_mgf( t, a, b, c ); printf( "t: %lf, a: %lf, b: %lf, c: %lf, M_X(t;a,b,c): %lf\n", t, a, b, c, y ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/include.gypi index c6495fc1da3f..575cb043c0bf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/mgf/include.gypi @@ -50,4 +50,4 @@ ' + + +
+ + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/triangular/pdf.h" +``` + +#### stdlib_base_dists_triangular_pdf( x, a, b, c ) + +Evaluates the [probability density function][pdf] (PDF) of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit), and `c` (mode). + +```c +double y = stdlib_base_dists_triangular_pdf( 0.5, -1.0, 1.0, 0.0 ); +// returns 0.5 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **a**: `[in] double` lower limit. +- **b**: `[in] double` upper limit. +- **c**: `[in] double` mode. + +```c +double stdlib_base_dists_triangular_pdf( const double x, const double a, const double b, const double c ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/triangular/pdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double c; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 30.0 ); + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a+STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c = random_uniform( a, b ); + y = stdlib_base_dists_triangular_pdf( x, a, b, c ); + printf( "x: %lf, a: %lf, b: %lf, c: %lf, f(x;a,b,c): %lf\n", x, a, b, c, y ); + } +} +``` + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js index adee58ea936a..2009ea83885a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js @@ -23,6 +23,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var pdf = require( './../lib' ); @@ -34,17 +35,27 @@ bench( pkg, function benchmark( b ) { var mode; var min; var max; + var len; var x; var y; var i; + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + mode = new Float64Array( len ); + + for ( i = 0; i < len; i++ ) { + x[ i ] = randu() * 30.0; + min[ i ] = randu() * 10.0; + max[ i ] = min[ i ] + ( randu() * 40.0 ) + EPS; + mode[ i ] = min[ i ] + ( ( max[ i ] - min[ i ] ) * randu() ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - x = randu() * 30.0; - min = randu() * 10.0; - max = min + ( randu() * 40.0 ) + EPS; - mode = min + ( ( max - min ) * randu() ); - y = pdf( x, min, max, mode ); + y = pdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..4020e9d53bf7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( pdf instanceof Error ) +}; + + +// MAIN // + +bench( pkg+'::native', opts, function benchmark( b ) { + var mode; + var min; + var max; + var len; + var x; + var y; + var i; + + len = 100; + x = new Float64Array( len ); + min = new Float64Array( len ); + max = new Float64Array( len ); + mode = new Float64Array( len ); + + for ( i = 0; i < len; i++ ) { + x[ i ] = randu() * 30.0; + min[ i ] = randu() * 10.0; + max[ i ] = min[ i ] + ( randu() * 40.0 ) + EPS; + mode[ i ] = min[ i ] + ( ( max[ i ] - min[ i ] ) * randu() ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = pdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..e47af3363e06 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c @@ -0,0 +1,145 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/triangular/pdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "triangular-pdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double a[ 100 ]; + double b[ 100 ]; + double c[ 100 ]; + double x[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 30.0 ); + a[ i ] = random_uniform( 0.0, 10.0 ); + b[ i ] = random_uniform( a[ i ] + STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c[ i ] = random_uniform( a[ i ], b[ i ] ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_triangular_pdf( x[ i % 100 ], a[ i % 100 ], b[ i % 100 ], c[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c new file mode 100644 index 000000000000..b594654852c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/triangular/pdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double c; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0.0, 30.0 ); + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a+STDLIB_CONSTANT_FLOAT64_EPS, 40.0 ); + c = random_uniform( a, b ); + y = stdlib_base_dists_triangular_pdf( x, a, b, c ); + printf( "x: %lf, a: %lf, b: %lf, c: %lf, f(x;a,b,c): %lf\n", x, a, b, c, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' c || + c > b + ) { + return 0.0/0.0; // NaN + } + if ( x < a ) { + return 0.0; + } + if ( x < c ) { + return ( 2.0 * (x - a) ) / ( (b - a) * (c - a) ); + } + if ( x == c ) { + return ( 2.0 / ( b - a ) ); + } + if ( x <= b ) { + return ( 2.0 * (b - x) ) / ( (b - a) * (b - c) ); + } + return 0.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js new file mode 100644 index 000000000000..4dffae744320 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js @@ -0,0 +1,215 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var smallRange = require( './fixtures/julia/small_range.json' ); +var mediumRange = require( './fixtures/julia/medium_range.json' ); +var largeRange = require( './fixtures/julia/large_range.json' ); + + +// VARIABLES // + +var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( pdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof pdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = pdf( NaN, 0.0, 1.0, 0.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 0.0, NaN, 1.0, 0.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 0.0, 1.0, NaN, 0.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 0.0, 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'if provided a number greater than `b` for `x` and valid parameters, the function returns `0`', opts, function test( t ) { + var y = pdf( PINF, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( 20.0, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( 2.0, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( 1.1, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + t.end(); +}); + +tape( 'if provided a number smaller than `a` for `x` and valid parameters, the function returns `0`', opts, function test( t ) { + var y = pdf( NINF, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( -20.0, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( -2.0, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + y = pdf( -0.5, 0.0, 1.0, 0.5 ); + t.equal( y, 0.0, 'returns 0' ); + + t.end(); +}); + +tape( 'if provided parameters not satisfying `a <= c <= b`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = pdf( 2.0, 3.0, 2.0, 2.5 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 0.0, 2.0, 3.0, 4.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 2.0, 2.0, 3.0, 1.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 2.0, PINF, NINF, 0.0 ); + t.equal( isnan( y ), true, 'returns NaN' ); + + t.end(); +}); + +tape( 'the function returns `2/(b-a)` if provided `x = c`', opts, function test( t ) { + var a = 0.0; + var b = 2.0; + var c = 1.5; + t.equal( pdf( c, a, b, c ), 2/(b-a), 'returns 2/(b-a)' ); + t.end(); +}); + +tape( 'the function evaluates the pdf for `x` given a small range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var c; + var y; + var i; + + expected = smallRange.expected; + x = smallRange.x; + a = smallRange.a; + b = smallRange.b; + c = smallRange.c; + for ( i = 0; i < x.length; i++ ) { + y = pdf( x[i], a[i], b[i], c[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the pdf for `x` given a medium range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var c; + var y; + var i; + + expected = mediumRange.expected; + x = mediumRange.x; + a = mediumRange.a; + b = mediumRange.b; + c = mediumRange.c; + for ( i = 0; i < x.length; i++ ) { + y = pdf( x[i], a[i], b[i], c[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the pdf for `x` given a large range `b - a`', opts, function test( t ) { + var expected; + var delta; + var tol; + var x; + var a; + var b; + var c; + var y; + var i; + + expected = largeRange.expected; + x = largeRange.x; + a = largeRange.a; + b = largeRange.b; + c = largeRange.c; + for ( i = 0; i < x.length; i++ ) { + y = pdf( x[i], a[i], b[i], c[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js index 80aaeaff3dcd..9831df998685 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js @@ -45,12 +45,18 @@ tape( 'main export is a function', function test( t ) { }); tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { - var y = pdf( NaN, 0.0, 1.0 ); + var y = pdf( NaN, 0.0, 1.0, 0.5 ); t.equal( isnan( y ), true, 'returns NaN' ); - y = pdf( 0.0, NaN, 1.0 ); + + y = pdf( 0.0, NaN, 1.0, 0.5 ); t.equal( isnan( y ), true, 'returns NaN' ); - y = pdf( 0.0, 1.0, NaN ); + + y = pdf( 0.0, 1.0, NaN, 0.5 ); t.equal( isnan( y ), true, 'returns NaN' ); + + y = pdf( 0.0, 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns NaN' ); + t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/README.md index c802a1d9e5c4..0b6c34ecaac4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/README.md @@ -59,7 +59,7 @@ var variance = require( '@stdlib/stats/base/dists/triangular/variance' ); #### variance( a, b, c ) -Returns the [variance][variance] of a [triangular][triangular-distribution] distribution with minimum support `a`, maximum support`b`, and mode `c`. +Returns the [variance][variance] of a [triangular][triangular-distribution] distribution with minimum support `a`, maximum support `b`, and mode `c`. ```javascript var v = variance( 0.0, 1.0, 0.8 ); @@ -141,6 +141,104 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/triangular/variance.h" +``` + +#### stdlib_base_dists_triangular_variance( a, b, c ) + +Returns the [variance][variance] of a [triangular][triangular-distribution] distribution with minimum support `a`, maximum support `b`, and mode `c`. + +```c +double out = stdlib_base_dists_triangular_variance( 0.0, 1.0, 0.5 ); +// returns ~0.056 +``` + +The function accepts the following arguments: + +- **a**: `[in] double` minimum support. +- **b**: `[in] double` maximum support. +- **c**: `[in] double` mode. + +```c +double stdlib_base_dists_triangular_variance( const double a, const double b, const double c ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/triangular/variance.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a, a+10.0 ); + c = random_uniform( a, b ); + y = stdlib_base_dists_triangular_variance( a, b, c ); + printf( "a: %lf, b: %lf, c: %lf, Var(X;a,b,c): %lf\n", a, b, c, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.js index 806586d035eb..dcebaa3ef732 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.js @@ -21,9 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var pkg = require( './../package.json' ).name; var variance = require( './../lib' ); @@ -34,15 +34,23 @@ bench( pkg, function benchmark( b ) { var mode; var min; var max; + var len; var y; var i; + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + mode = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = ( randu() * 10.0 ); + max[ i ] = ( randu() * 10.0 ) + min[ i ]; + mode[ i ] = min[ i ] + ( randu() * ( max[ i ] - min[ i ] ) ); + } + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - min = ( randu()*10.0 ); - max = ( randu()*10.0 ) + min + EPS; - mode = ( ( max - min ) * randu() ) + min; - y = variance( min, max, mode ); + y = variance( min[ i % len ], max[ i % len ], mode[ i % len ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.native.js new file mode 100644 index 000000000000..88ab58c393fc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/benchmark.native.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var variance = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::native', function benchmark( b ) { + var mode; + var min; + var max; + var len; + var y; + var i; + + len = 100; + min = new Float64Array( len ); + max = new Float64Array( len ); + mode = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + min[ i ] = ( randu() * 10.0 ); + max[ i ] = ( randu() * 10.0 ) + min[ i ]; + mode[ i ] = min[ i ] + ( randu() * ( max[ i ] - min[ i ] ) ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( min[ i % len ], max[ i % len ], mode[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/c/Makefile new file mode 100644 index 000000000000..a4bd7b38fd74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/c/benchmark.c new file mode 100644 index 000000000000..7c438f8f2b7d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/benchmark/c/benchmark.c @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/triangular/variance.h" +#include +#include +#include +#include +#include + +#define NAME "triangular-variance" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,20). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return 20.0*(double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double a[ 100 ]; + double b[ 100 ]; + double c[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + a[ i ] = rand_double() * 20.0; + b[ i ] = ( rand_double() * 20.0 ) + a[ i ]; + c[ i ] = ( rand_double() * ( b[i] - a[i] ) ) + a[i]; + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_triangular_variance( a[ i%100 ], b[ i%100 ], c[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/binding.gyp new file mode 100644 index 000000000000..68a1ca11d160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/examples/c/Makefile new file mode 100644 index 000000000000..25ced822f96a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/examples/c/example.c new file mode 100644 index 000000000000..f227025acf1b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/triangular/variance.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double a; + double b; + double c; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( a, a+10.0 ); + c = a + (b - a) * random_uniform( 0.0, 1.0 ); + y = stdlib_base_dists_triangular_variance( a, b, c ); + printf( "a: %lf, b: %lf, c: %lf, Var(X;a,b,c): %lf\n", a, b, c, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/include.gypi new file mode 100644 index 000000000000..ecfaf82a3279 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/variance/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2025 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= b - ) { + ) { return 0.0 / 0.0; // NaN } return stdlib_base_ln( b - a ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.js index a2e1e7e7731b..1575dae692db 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.js @@ -70,7 +70,7 @@ tape( 'if provided `a >= b`, the function returns `NaN`', function test( t ) { t.end(); }); -tape( 'the function returns the entropy of a uniform distribution', function test( t ) { +tape( 'the function returns differential entropy of a uniform distribution', function test( t ) { var expected; var delta; var tol; diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.native.js index 0cb74fcf5f13..4dedd1678e2f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/entropy/test/test.native.js @@ -79,7 +79,7 @@ tape( 'if provided `a >= b`, the function returns `NaN`', opts, function test( t t.end(); }); -tape( 'the function returns the entropy of a uniform distribution', opts, function test( t ) { +tape( 'the function returns the differential entropy of a uniform distribution', opts, function test( t ) { var expected; var delta; var tol; diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/uniform/mean/examples/c/example.c index edabfe24bf72..3975bc48b436 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/mean/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { a = random_uniform( 0.0, 10.0 ); b = random_uniform( a, 20.0 ); y = stdlib_base_dists_uniform_mean( a, b ); - printf( "a: %lf , b: %lf , E(X;a,b): %lf\n", a, b, y ); + printf( "a: %lf, b: %lf, E(X;a,b): %lf\n", a, b, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/uniform/median/benchmark/c/benchmark.c index 8b02462742c1..cf13231720fb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/median/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/median/benchmark/c/benchmark.c @@ -37,8 +37,8 @@ static void print_version( void ) { /** * Prints the TAP summary. * -* @param total total number of tests -* @param passing total number of passing tests +* @param total total number of tests +* @param passing total number of passing tests */ static void print_summary( int total, int passing ) { printf( "#\n" ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/uniform/median/examples/c/example.c index b33bf71fa67c..84fa42fd05c7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/median/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/median/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { a = random_uniform( 0.0, 10.0 ); b = random_uniform( a, 20.0 ); y = stdlib_base_dists_uniform_median( a, b ); - printf( "a: %lf , b: %lf, Median(X;a,b): %lf\n", a, b, y ); + printf( "a: %lf, b: %lf, Median(X;a,b): %lf\n", a, b, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/README.md index 71c2c37ed93d..8c8123b039cf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/README.md @@ -213,7 +213,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { a = random_uniform( 0.0, 20.0 ); - b = random_uniform( 0.0, 20.0 ) + a; + b = random_uniform( a, a+20.0 ); y = stdlib_base_dists_uniform_variance( a, b ); printf( "a: %lf, b: %lf, Var(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/benchmark/c/benchmark.c index 71afddede9f4..44c5317faada 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/benchmark/c/benchmark.c @@ -101,7 +101,7 @@ static double benchmark( void ) { for ( i = 0; i < 100; i++ ) { min[ i ] = random_uniform( 0.0, 20.0 ); - max[ i ] = random_uniform( 0.0, 20.0 ) + min[ i ]; + max[ i ] = random_uniform( min[ i ], min[ i ] + 20.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/examples/c/example.c index 5e55ea631e08..ecd60aab6fe9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/variance/examples/c/example.c @@ -33,7 +33,7 @@ int main( void ) { for ( i = 0; i < 25; i++ ) { a = random_uniform( 0.0, 20.0 ); - b = random_uniform( 0.0, 20.0 ) + a; + b = random_uniform( a, a+20.0 ); y = stdlib_base_dists_uniform_variance( a, b ); printf( "a: %lf, b: %lf, Var(X;a,b): %lf\n", a, b, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/README.md index 5961c59dd8c3..4bacee01c13a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/README.md @@ -142,7 +142,7 @@ for ( i = 0; i < 10; i++ ) { x = randu() * 10.0; lambda = randu() * 10.0; k = randu() * 10.0; - y = cdf( x, lambda, k ); + y = cdf( x, k, lambda ); console.log( 'x: %d, k: %d, λ: %d, F(x;k,λ): %d', x, k, lambda, y ); } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/benchmark/c/benchmark.c index d819d401d954..6106a6b697a3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/benchmark/c/benchmark.c @@ -102,9 +102,9 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - x[ i ] = random_uniform( 0.0 , 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - lambda[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - k[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/test/test.native.js index 35ec3d09effc..80fd4941bcaf 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/cdf/test/test.native.js @@ -47,7 +47,7 @@ var opts = { // TESTS // -tape( 'main export is a function', opts, opts, function test( t ) { +tape( 'main export is a function', opts, function test( t ) { t.ok( true, __filename ); t.strictEqual( typeof cdf, 'function', 'main export is a function' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/weibull/kurtosis/lib/main.js index 402d5741347f..0a0f2b73bfbe 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/kurtosis/lib/main.js @@ -32,7 +32,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); * * @param {PositiveNumber} k - shape parameter * @param {PositiveNumber} lambda - scale parameter -* @returns {number} kurtosis +* @returns {number} excess kurtosis * * @example * var v = kurtosis( 1.0, 1.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/benchmark/c/benchmark.c index 565c641c23ec..d22643d1ceb3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/benchmark/c/benchmark.c @@ -102,9 +102,9 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - x[ i ] = random_uniform( 0.0 , 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - lambda[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - k[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/test/test.native.js index bb26d94924c2..8d8493a9abba 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/logcdf/test/test.native.js @@ -47,9 +47,9 @@ var opts = { // TESTS // -tape( 'main export is a function', opts, opts, opts, function test( t ) { +tape( 'main export is a function', opts, function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.strictEqual( typeof logcdf, 'function', 'main export is a function' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/benchmark/c/benchmark.c index ccb9587f8a78..b4547328c689 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/benchmark/c/benchmark.c @@ -102,9 +102,9 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - x[ i ] = random_uniform( 0.0 , 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - lambda[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - k[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/test/test.native.js index bc6b5af7702f..7406e8a554c8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/test/test.native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/test/test.native.js @@ -48,9 +48,9 @@ var opts = { // TESTS // -tape( 'main export is a function', opts, opts, opts, function test( t ) { +tape( 'main export is a function', opts, function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.strictEqual( typeof logpdf, 'function', 'main export is a function' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/README.md index 90e97373c8d2..79868a9f1151 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/README.md @@ -224,8 +224,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - k = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - lambda = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + k = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_weibull_mean( k, lambda ); printf( "k: %lf, λ: %lf, E(X;k,λ): %lf\n", k, lambda, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/benchmark/c/benchmark.c index 0a0290e4f576..37558a1ee580 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 1.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - k[ i ] = random_uniform( 0.0, 1.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 1.0 ); + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 1.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/examples/c/example.c index 3c1b480e7411..9b72bb941035 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/examples/c/example.c @@ -33,8 +33,8 @@ int main( void ) { int i; for ( i = 0; i < 25; i++ ) { - k = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - lambda = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + k = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_weibull_mean( k, lambda ); printf( "k: %lf, λ: %lf, E(X;k,λ): %lf\n", k, lambda, y ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/src/main.c index 7a85e4b350a7..aa7b5d27a2ce 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/mean/src/main.c @@ -37,7 +37,7 @@ double stdlib_base_dists_weibull_mean( const double k, const double lambda ) { stdlib_base_is_nan( lambda ) || k <= 0.0 || lambda <= 0.0 - ) { + ) { return 0.0 / 0.0; // NaN } return lambda * stdlib_base_gamma( 1.0 + (1.0/k) ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/median/benchmark/c/benchmark.c index 25018ab2079a..ea1a5c658e04 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/median/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/median/benchmark/c/benchmark.c @@ -101,8 +101,8 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - lambda[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - k[ i ] = random_uniform( 0.0, 10.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/pdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/weibull/pdf/benchmark/c/benchmark.c index 5d405e2ca68f..ee14654e8432 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/weibull/pdf/benchmark/c/benchmark.c +++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/pdf/benchmark/c/benchmark.c @@ -102,9 +102,9 @@ static double benchmark( void ) { int i; for ( i = 0; i < 100; i++ ) { - x[ i ] = random_uniform( 0.0 , 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - lambda[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; - k[ i ] = random_uniform( 0.0, 100.0 ) + STDLIB_CONSTANT_FLOAT64_EPS; + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + k[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); } t = tic(); diff --git a/lib/node_modules/@stdlib/stats/base/dmax/README.md b/lib/node_modules/@stdlib/stats/base/dmax/README.md deleted file mode 100644 index 736649960950..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/README.md +++ /dev/null @@ -1,305 +0,0 @@ - - -# dmax - -> Calculate the maximum value of a double-precision floating-point strided array. - -
- -
- - - -
- -## Usage - -```javascript -var dmax = require( '@stdlib/stats/base/dmax' ); -``` - -#### dmax( N, x, strideX ) - -Computes the maximum value of a double-precision floating-point strided array `x`. - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - -var v = dmax( x.length, x, 1 ); -// returns 2.0 -``` - -The function has the following parameters: - -- **N**: number of indexed elements. -- **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: stride length for `x`. - -The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum value of every other element in `x`, - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); - -var v = dmax( 4, x, 2 ); -// returns 4.0 -``` - -Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - - - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - -var v = dmax( 4, x1, 2 ); -// returns 4.0 -``` - -#### dmax.ndarray( N, x, strideX, offsetX ) - -Computes the maximum value of a double-precision floating-point strided array using alternative indexing semantics. - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; - -var v = dmax.ndarray( N, x, 1, 0 ); -// returns 2.0 -``` - -The function has the following additional parameters: - -- **offsetX**: starting index for `x`. - -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value - -```javascript -var Float64Array = require( '@stdlib/array/float64' ); - -var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); - -var v = dmax.ndarray( 4, x, 2, 1 ); -// returns 4.0 -``` - -
- - - -
- -## Notes - -- If `N <= 0`, both functions return `NaN`. - -
- - - -
- -## Examples - - - -```javascript -var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); -var dmax = require( '@stdlib/stats/base/dmax' ); - -var x = discreteUniform( 10, -50, 50, { - 'dtype': 'float64' -}); -console.log( x ); - -var v = dmax( x.length, x, 1 ); -console.log( v ); -``` - -
- - - - - -* * * - -
- -## C APIs - - - -
- -
- - - - - -
- -### Usage - -```c -#include "stdlib/stats/base/dmax.h" -``` - -#### stdlib_strided_dmax( N, \*X, strideX ) - -Computes the maximum value of a double-precision floating-point strided array. - -```c -const double x[] = { 1.0, -2.0, 3.0, -4.0 }; - -double v = stdlib_strided_dmax( 4, x, 1 ); -// returns 3.0 -``` - -The function accepts the following arguments: - -- **N**: `[in] CBLAS_INT` number of indexed elements. -- **X**: `[in] double*` input array. -- **strideX**: `[in] CBLAS_INT` stride length for `X`. - -```c -double stdlib_strided_dmax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); -``` - -#### stdlib_strided_dmax_ndarray( N, \*X, strideX, offsetX ) - -Computes the maximum value of a double-precision floating-point strided array using alternative indexing semantics. - -```c -const double x[] = { 1.0, -2.0, 3.0, -4.0 }; - -double v = stdlib_strided_dmax_ndarray( 4, x, 1, 0 ); -// returns 3.0 -``` - -The function accepts the following arguments: - -- **N**: `[in] CBLAS_INT` number of indexed elements. -- **X**: `[in] double*` input array. -- **strideX**: `[in] CBLAS_INT` stride length for `X`. -- **offsetX**: `[in] CBLAS_INT` starting index for `X`. - -```c -double stdlib_strided_dmax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); -``` - -
- - - - - -
- -
- - - - - -
- -### Examples - -```c -#include "stdlib/stats/base/dmax.h" -#include - -int main( void ) { - // Create a strided array: - const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; - - // Specify the number of indexed elements: - const int N = 8; - - // Specify a stride: - const int strideX = 1; - - // Compute the maximum value: - double v = stdlib_strided_dmax( N, x, strideX ); - - // Print the result: - printf( "max: %lf\n", v ); -} -``` - -
- - - -
- - - - - -
- -* * * - -## See Also - -- [`@stdlib/stats/base/dmin`][@stdlib/stats/base/dmin]: calculate the minimum value of a double-precision floating-point strided array. -- [`@stdlib/stats/base/dnanmax`][@stdlib/stats/base/dnanmax]: calculate the maximum value of a double-precision floating-point strided array, ignoring NaN values. -- [`@stdlib/stats/base/max`][@stdlib/stats/base/max]: calculate the maximum value of a strided array. -- [`@stdlib/stats/base/smax`][@stdlib/stats/base/smax]: calculate the maximum value of a single-precision floating-point strided array. - -
- - - - - -
- -[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 - -[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray - - - -[@stdlib/stats/base/dmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmin - -[@stdlib/stats/base/dnanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanmax - -[@stdlib/stats/base/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/max - -[@stdlib/stats/base/smax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/smax - - - -
- - diff --git a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmax/benchmark/c/benchmark.length.c deleted file mode 100644 index 37d1c777e986..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/c/benchmark.length.c +++ /dev/null @@ -1,197 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmax.h" -#include -#include -#include -#include -#include - -#define NAME "dmax" -#define ITERATIONS 1000000 -#define REPEATS 3 -#define MIN 1 -#define MAX 6 - -/** -* Prints the TAP version. -*/ -static void print_version( void ) { - printf( "TAP version 13\n" ); -} - -/** -* Prints the TAP summary. -* -* @param total total number of tests -* @param passing total number of passing tests -*/ -static void print_summary( int total, int passing ) { - printf( "#\n" ); - printf( "1..%d\n", total ); // TAP plan - printf( "# total %d\n", total ); - printf( "# pass %d\n", passing ); - printf( "#\n" ); - printf( "# ok\n" ); -} - -/** -* Prints benchmarks results. -* -* @param iterations number of iterations -* @param elapsed elapsed time in seconds -*/ -static void print_results( int iterations, double elapsed ) { - double rate = (double)iterations / elapsed; - printf( " ---\n" ); - printf( " iterations: %d\n", iterations ); - printf( " elapsed: %0.9f\n", elapsed ); - printf( " rate: %0.9f\n", rate ); - printf( " ...\n" ); -} - -/** -* Returns a clock time. -* -* @return clock time -*/ -static double tic( void ) { - struct timeval now; - gettimeofday( &now, NULL ); - return (double)now.tv_sec + (double)now.tv_usec/1.0e6; -} - -/** -* Generates a random number on the interval [0,1). -* -* @return random number -*/ -static double rand_double( void ) { - int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); -} - -/** -* Runs a benchmark. -* -* @param iterations number of iterations -* @param len array length -* @return elapsed time in seconds -*/ -static double benchmark1( int iterations, int len ) { - double elapsed; - double x[ len ]; - double v; - double t; - int i; - - for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; - } - v = 0.0; - t = tic(); - for ( i = 0; i < iterations; i++ ) { - // cppcheck-suppress uninitvar - v = stdlib_strided_dmax( len, x, 1 ); - if ( v != v ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( v != v ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Runs a benchmark. -* -* @param iterations number of iterations -* @param len array length -* @return elapsed time in seconds -*/ -static double benchmark2( int iterations, int len ) { - double elapsed; - double x[ len ]; - double v; - double t; - int i; - - for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; - } - v = 0.0; - t = tic(); - for ( i = 0; i < iterations; i++ ) { - // cppcheck-suppress uninitvar - v = stdlib_strided_dmax_ndarray( len, x, 1, 0 ); - if ( v != v ) { - printf( "should not return NaN\n" ); - break; - } - } - elapsed = tic() - t; - if ( v != v ) { - printf( "should not return NaN\n" ); - } - return elapsed; -} - -/** -* Main execution sequence. -*/ -int main( void ) { - double elapsed; - int count; - int iter; - int len; - int i; - int j; - - // Use the current time to seed the random number generator: - srand( time( NULL ) ); - - print_version(); - count = 0; - for ( i = MIN; i <= MAX; i++ ) { - len = pow( 10, i ); - iter = ITERATIONS / pow( 10, i-1 ); - for ( j = 0; j < REPEATS; j++ ) { - count += 1; - printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark1( iter, len ); - print_results( iter, elapsed ); - printf( "ok %d benchmark finished\n", count ); - } - } - for ( i = MIN; i <= MAX; i++ ) { - len = pow( 10, i ); - iter = ITERATIONS / pow( 10, i-1 ); - for ( j = 0; j < REPEATS; j++ ) { - count += 1; - printf( "# c::%s:ndarray:len=%d\n", NAME, len ); - elapsed = benchmark2( iter, len ); - print_results( iter, elapsed ); - printf( "ok %d benchmark finished\n", count ); - } - } - print_summary( count, count ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmax/examples/c/example.c deleted file mode 100644 index 5e235e7df779..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/examples/c/example.c +++ /dev/null @@ -1,37 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmax.h" -#include - -int main( void ) { - // Create a strided array: - const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; - - // Specify the number of indexed elements: - const int N = 4; - - // Specify the stride length: - const int strideX = 2; - - // Compute the maximum value: - double v = stdlib_strided_dmax( N, x, strideX ); - - // Print the result: - printf( "max: %lf\n", v ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmax/lib/index.js deleted file mode 100644 index c8a0b0275d01..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/lib/index.js +++ /dev/null @@ -1,68 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -/** -* Compute the maximum value of a double-precision floating-point strided array. -* -* @module @stdlib/stats/base/dmax -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var dmax = require( '@stdlib/stats/base/dmax' ); -* -* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* -* var v = dmax( x.length, x, 1 ); -* // returns 2.0 -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var dmax = require( '@stdlib/stats/base/dmax' ); -* -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* -* var v = dmax.ndarray( 4, x, 2, 1 ); -* // returns 4.0 -*/ - -// MODULES // - -var join = require( 'path' ).join; -var tryRequire = require( '@stdlib/utils/try-require' ); -var isError = require( '@stdlib/assert/is-error' ); -var main = require( './main.js' ); - - -// MAIN // - -var dmax; -var tmp = tryRequire( join( __dirname, './native.js' ) ); -if ( isError( tmp ) ) { - dmax = main; -} else { - dmax = tmp; -} - - -// EXPORTS // - -module.exports = dmax; - -// exports: { "ndarray": "dmax.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/base/dmax/package.json b/lib/node_modules/@stdlib/stats/base/dmax/package.json deleted file mode 100644 index 9606d9cfe998..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/package.json +++ /dev/null @@ -1,77 +0,0 @@ -{ - "name": "@stdlib/stats/base/dmax", - "version": "0.0.0", - "description": "Calculate the maximum value of a double-precision floating-point strided array.", - "license": "Apache-2.0", - "author": { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - }, - "contributors": [ - { - "name": "The Stdlib Authors", - "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" - } - ], - "main": "./lib", - "browser": "./lib/main.js", - "gypfile": true, - "directories": { - "benchmark": "./benchmark", - "doc": "./docs", - "example": "./examples", - "include": "./include", - "lib": "./lib", - "src": "./src", - "test": "./test" - }, - "types": "./docs/types", - "scripts": {}, - "homepage": "https://github.com/stdlib-js/stdlib", - "repository": { - "type": "git", - "url": "git://github.com/stdlib-js/stdlib.git" - }, - "bugs": { - "url": "https://github.com/stdlib-js/stdlib/issues" - }, - "dependencies": {}, - "devDependencies": {}, - "engines": { - "node": ">=0.10.0", - "npm": ">2.7.0" - }, - "os": [ - "aix", - "darwin", - "freebsd", - "linux", - "macos", - "openbsd", - "sunos", - "win32", - "windows" - ], - "keywords": [ - "stdlib", - "stdmath", - "statistics", - "stats", - "mathematics", - "math", - "maximum", - "max", - "range", - "extremes", - "domain", - "extent", - "strided", - "strided array", - "typed", - "array", - "float64", - "double", - "float64array" - ], - "__stdlib__": {} -} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmax/src/addon.c deleted file mode 100644 index 03816c073bc2..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/src/addon.c +++ /dev/null @@ -1,60 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2024 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmax.h" -#include "stdlib/napi/export.h" -#include "stdlib/napi/argv.h" -#include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_strided_float64array.h" -#include "stdlib/napi/create_double.h" -#include - -/** -* Receives JavaScript callback invocation data. -* -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmax( N, X, strideX ), v ); - return v; -} - -/** -* Receives JavaScript callback invocation data. -* -* @param env environment under which the function is invoked -* @param info callback data -* @return Node-API value -*/ -static napi_value addon_method( napi_env env, napi_callback_info info ) { - STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); - STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); - STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmax_ndarray( N, X, strideX, offsetX ), v ); - return v; -} - -STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmax/src/main.c b/lib/node_modules/@stdlib/stats/base/dmax/src/main.c deleted file mode 100644 index e52926ff6923..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmax/src/main.c +++ /dev/null @@ -1,72 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmax.h" -#include "stdlib/blas/base/shared.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_positive_zero.h" -#include "stdlib/strided/base/stride2offset.h" - -/** -* Computes the maximum value of a double-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X input array -* @param strideX stride length -* @return output value -*/ -double API_SUFFIX(stdlib_strided_dmax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { - const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); - return API_SUFFIX(stdlib_strided_dmax_ndarray)( N, X, strideX, ox ); -} - -/** -* Computes the maximum value of a double-precision floating-point strided array using alternative indexing semantics. -* -* @param N number of indexed elements -* @param X input array -* @param strideX stride length -* @param offsetX starting index -* @return output value -*/ -double API_SUFFIX(stdlib_strided_dmax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { - CBLAS_INT ix; - CBLAS_INT i; - double max; - double v; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || strideX == 0 ) { - return X[ 0 ]; - } - ix = offsetX; - max = X[ ix ]; - for ( i = 1; i < N; i++ ) { - ix += strideX; - v = X[ ix ]; - if ( stdlib_base_is_nan( v ) ) { - return v; - } - if ( v > max || ( v == max && stdlib_base_is_positive_zero( v ) ) ) { - max = v; - } - } - return max; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabs/README.md b/lib/node_modules/@stdlib/stats/base/dmaxabs/README.md index 1f05fd773bd0..464e8426ffdc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabs/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmaxabs/README.md @@ -274,7 +274,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dminabs`][@stdlib/stats/base/dminabs]: calculate the minimum absolute value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dnanmaxabs`][@stdlib/stats/base/dnanmaxabs]: calculate the maximum absolute value of a double-precision floating-point strided array, ignoring NaN values. - [`@stdlib/stats/base/maxabs`][@stdlib/stats/base/maxabs]: calculate the maximum absolute value of a strided array. @@ -294,7 +294,7 @@ int main( void ) { -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/dminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dminabs diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmaxabs/docs/repl.txt index 824db79503ae..c2b47bd59fb0 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmaxabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmaxabs/src/addon.c index 638aec564904..cd99f0200301 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmaxabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmaxabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmaxabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md index e636b54a135d..bae86b03493e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' ); ``` -#### dmaxabssorted( N, x, stride ) +#### dmaxabssorted( N, x, strideX ) Computes the maximum absolute value of a sorted double-precision floating-point strided array `x`. @@ -56,18 +56,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmaxabssorted( N, x, 2 ); +var v = dmaxabssorted( 4, x, 2 ); // returns 4.0 ``` @@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmaxabssorted( N, x1, 2 ); +var v = dmaxabssorted( 4, x1, 2 ); // returns 4.0 ``` -#### dmaxabssorted.ndarray( N, x, stride, offset ) +#### dmaxabssorted.ndarray( N, x, strideX, offsetX ) Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -102,18 +97,16 @@ var v = dmaxabssorted.ndarray( x.length, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmaxabssorted.ndarray( N, x, 2, 1 ); +var v = dmaxabssorted.ndarray( 4, x, 2, 1 ); // returns 4.0 ``` @@ -139,16 +132,13 @@ var v = dmaxabssorted.ndarray( N, x, 2, 1 ); ```javascript -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dmaxabssorted( x.length, x, 1 ); @@ -159,6 +149,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmaxabssorted.h" +``` + +#### stdlib_strided_dmaxabssorted( N, \*X, strideX ) + +Computes the maximum absolute value of a sorted double-precision floating-point strided array. + +```c +const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 }; + +double v = stdlib_strided_dmaxabssorted( 4, x, 2 ); +// returns 7.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmaxabssorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmaxabssorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics. + +```c +const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 }; + +double v = stdlib_strided_dmaxabssorted_ndarray( 4, x, 2, 0 ); +// returns 7.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmaxabssorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmaxabssorted.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the maximum absolute value: + double v = stdlib_strided_dmaxabssorted( N, x, strideX ); + + // Print the result: + printf( "maxabs: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js index 4e8df530c306..1eb995830a5b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmaxabssorted = require( './../lib/dmaxabssorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dmaxabssorted = require( './../lib/dmaxabssorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js index 9ef830eda3a4..07fd755c16be 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dmaxabssorted = tryRequire( resolve( __dirname, './../lib/dmaxabssorted.nati var opts = { 'skip': ( dmaxabssorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js index a620612645ee..230a464a14fe 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmaxabssorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dmaxabssorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js index a497940daed0..f45700dff534 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dmaxabssorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' var opts = { 'skip': ( dmaxabssorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c index 81b461c7d421..0623aab79d4d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmaxabssorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i - (len/2); + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmaxabssorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt index 9a05d38c550b..679ec6b5fa91 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the maximum absolute value of a sorted double-precision floating- point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,8 +22,8 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,22 +37,19 @@ > {{alias}}( x.length, x, 1 ) 3.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 2.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) 3.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the maximum absolute value of a sorted double-precision floating- point strided array using alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 3.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts index 72bcb1bd6bcd..9970a5e2144e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum absolute value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmaxabssorted( x.length, x, 1 ); * // returns 3.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns maximum absolute value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmaxabssorted.ndarray( x.length, x, 1, 0 ); * // returns 3.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns maximum absolute value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c index 0417e40b9812..8ce3bc40c15b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmaxabssorted.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 }; + const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the maximum absolute value: - double v = stdlib_strided_dmaxabssorted( N, x, stride ); + double v = stdlib_strided_dmaxabssorted( N, x, strideX ); // Print the result: printf( "maxabs: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js index 5ab49c15d1ec..7646a057a54f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dmaxabssorted = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - x.length; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dmaxabssorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h index 8bb1138d13c5..f8fafdabed17 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMAXABSSORTED_H #define STDLIB_STATS_BASE_DMAXABSSORTED_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the maximum absolute value of a sorted double-precision floating-point strided array. */ -double stdlib_strided_dmaxabssorted( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmaxabssorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js index 9a91fbbc1605..533e9da91cf2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,44 +31,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum absolute value * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ -1.0, -2.0, -3.0 ] ); -* var N = x.length; * -* var v = dmaxabssorted( N, x, 1 ); +* var v = dmaxabssorted( x.length, x, 1 ); * // returns 3.0 */ -function dmaxabssorted( N, x, stride ) { - var v1; - var v2; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - v1 = x[ (1-N) * stride ]; - v2 = x[ 0 ]; - } else { - v1 = x[ 0 ]; - v2 = x[ (N-1) * stride ]; - } - if ( isnan( v1 ) || isnan( v2 ) ) { - return NaN; - } - v1 = abs( v1 ); - v2 = abs( v2 ); - if ( v1 > v2 ) { - return v1; - } - return v2; +function dmaxabssorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js index 5ed23b5c8fad..9e3ead8a17b5 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum absolute value * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ -1.0, -2.0, -3.0 ] ); -* var N = x.length; * -* var v = dmaxabssorted( N, x, 1 ); +* var v = dmaxabssorted( x.length, x, 1 ); * // returns 3.0 */ -function dmaxabssorted( N, x, stride ) { - return addon( N, x, stride ); +function dmaxabssorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js index 48313ac1b150..b0116bda24b4 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js @@ -28,20 +28,17 @@ * var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' ); * * var x = new Float64Array( [ -1.0, -2.0, -3.0 ] ); -* var N = x.length; * -* var v = dmaxabssorted( N, x, 1 ); +* var v = dmaxabssorted( x.length, x, 1 ); * // returns 3.0 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmaxabssorted.ndarray( N, x, 2, 1 ); +* var v = dmaxabssorted.ndarray( 4, x, 2, 1 ); * // returns 4.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js index a916d1a6b1ed..5d21803e898e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js @@ -31,32 +31,30 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum absolute value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmaxabssorted( N, x, 2, 1 ); +* var v = dmaxabssorted( 4, x, 2, 1 ); * // returns 4.0 */ -function dmaxabssorted( N, x, stride, offset ) { +function dmaxabssorted( N, x, strideX, offsetX ) { var v1; var v2; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return x[ 0 ]; } - v1 = x[ offset ]; - v2 = x[ offset + ((N-1)*stride) ]; + v1 = x[ offsetX ]; + v2 = x[ offsetX + ( ( N - 1 ) * strideX ) ]; if ( isnan( v1 ) || isnan( v2 ) ) { return NaN; } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js index b2867599a5af..de4c3cf23616 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmaxabssorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmaxabssorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum absolute value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmaxabssorted( N, x, 2, 1 ); +* var v = dmaxabssorted( 4, x, 2, 1 ); * // returns 4.0 */ -function dmaxabssorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmaxabssorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json index 5bea2ec4b6a7..f20b3f18864a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,18 +28,20 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmaxabssorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,34 +51,56 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmaxabssorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmaxabssorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c index 2d997a02fcf4..b6c000583b23 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmaxabssorted.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxabssorted( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmaxabssorted)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c deleted file mode 100644 index d26827cb8e88..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c +++ /dev/null @@ -1,58 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmaxabssorted.h" -#include "stdlib/math/base/assert/is_nan.h" -#include -#include - -/** -* Computes the maximum absolute value of a sorted double-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmaxabssorted( const int64_t N, const double *X, const int64_t stride ) { - double v1; - double v2; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - v1 = X[ (1-N) * stride ]; - v2 = X[ 0 ]; - } else { - v1 = X[ 0 ]; - v2 = X[ (N-1) * stride ]; - } - if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) { - return 0.0 / 0.0; // NaN - } - v1 = fabs( v1 ); - v2 = fabs( v2 ); - if ( v1 > v2 ) { - return v1; - } - return v2; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c new file mode 100644 index 000000000000..396f6a63a34d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmaxabssorted.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/abs.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the maximum absolute value of a sorted double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmaxabssorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + double v1; + double v2; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + v1 = X[ offsetX ]; + v2 = X[ ( ( N - 1 ) * strideX ) + offsetX ]; + if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) { + return 0.0 / 0.0; // NaN + } + v1 = stdlib_base_abs( v1 ); + v2 = stdlib_base_abs( v2 ); + if ( v1 > v2 ) { + return v1; + } + return v2; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js index 85710b088c45..994dec1ec029 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, 2 ); + v = dmaxabssorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, -2 ); + v = dmaxabssorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmaxabssorted( N, x1, 2 ); + v = dmaxabssorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js index cc2276961163..61261f63439e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, 2 ); + v = dmaxabssorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, -2 ); + v = dmaxabssorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmaxabssorted( N, x1, 2 ); + v = dmaxabssorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js index 070a3e9810db..b00f94f068c3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, 2, 0 ); + v = dmaxabssorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, -2, 6 ); + v = dmaxabssorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, 2, 1 ); + v = dmaxabssorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js index 348454887153..347b35dec2fc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, 2, 0 ); + v = dmaxabssorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, -2, 6 ); + v = dmaxabssorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmaxabssorted( N, x, 2, 1 ); + v = dmaxabssorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md b/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md index 749f8a8b95cf..39f2f6cfd0cd 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' ); ``` -#### dmaxsorted( N, x, stride ) +#### dmaxsorted( N, x, strideX ) Computes the maximum value of a sorted double-precision floating-point strided array `x`. @@ -44,15 +44,13 @@ Computes the maximum value of a sorted double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = dmaxsorted( N, x, 1 ); +var v = dmaxsorted( x.length, x, 1 ); // returns 3.0 x = new Float64Array( [ 3.0, 2.0, 1.0 ] ); -N = x.length; -v = dmaxsorted( N, x, 1 ); +v = dmaxsorted( x.length, x, 1 ); // returns 3.0 ``` @@ -60,18 +58,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmaxsorted( N, x, 2 ); +var v = dmaxsorted( 4, x, 2 ); // returns 4.0 ``` @@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmaxsorted( N, x1, 2 ); +var v = dmaxsorted( 4, x1, 2 ); // returns 4.0 ``` -#### dmaxsorted.ndarray( N, x, stride, offset ) +#### dmaxsorted.ndarray( N, x, strideX, offsetX ) Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -100,26 +93,23 @@ Computes the maximum value of a sorted double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = dmaxsorted.ndarray( N, x, 1, 0 ); +var v = dmaxsorted.ndarray( x.length, x, 1, 0 ); // returns 3.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmaxsorted.ndarray( N, x, 2, 1 ); +var v = dmaxsorted.ndarray( 4, x, 2, 1 ); // returns 4.0 ``` @@ -145,16 +135,13 @@ var v = dmaxsorted.ndarray( N, x, 2, 1 ); ```javascript -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dmaxsorted( x.length, x, 1 ); @@ -165,6 +152,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmaxsorted.h" +``` + +#### stdlib_strided_dmaxsorted( N, \*X, strideX ) + +Computes the maximum value of a sorted double-precision floating-point strided array. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; + +double v = stdlib_strided_dmaxsorted( 3, x, 1 ); +// returns 3.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmaxsorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmaxsorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; + +double v = stdlib_strided_dmaxsorted_ndarray( 3, x, 1, 0 ); +// returns 3.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmaxsorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmaxsorted.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the maximum value: + double v = stdlib_strided_dmaxsorted( N, x, strideX ); + + // Print the result: + printf( "max: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js index 0726a05b9bc3..7cd40722fd2b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmaxsorted = require( './../lib/dmaxsorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dmaxsorted = require( './../lib/dmaxsorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js index 5e49fb7244cc..10835ad82014 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dmaxsorted = tryRequire( resolve( __dirname, './../lib/dmaxsorted.native.js' var opts = { 'skip': ( dmaxsorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js index 17609b252d90..6d3290ead750 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmaxsorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dmaxsorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js index f02448bd23a0..96436d79fe29 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dmaxsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dmaxsorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c index f2c96f345e6a..285e7691b37a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmaxsorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmaxsorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt index d1483c778af7..3d5acf84d04e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the maximum value of a sorted double-precision floating-point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,8 +22,8 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,22 +37,19 @@ > {{alias}}( x.length, x, 1 ) 3.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 2.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) 3.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 3.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts index 8da4da37c2e8..9ccb5a79afc3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmaxsorted( x.length, x, 1 ); * // returns 3.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns maximum value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmaxsorted.ndarray( x.length, x, 1, 0 ); * // returns 3.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns maximum value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c index b0e839fdacb0..f4b35e787d0a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmaxsorted.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the maximum value: - double v = stdlib_strided_dmaxsorted( N, x, stride ); + double v = stdlib_strided_dmaxsorted( N, x, strideX ); // Print the result: printf( "max: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js index a1517627f936..b76928ded2a6 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dmaxsorted = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dmaxsorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h b/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h index 3f6b84867480..ced00e5df072 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMAXSORTED_H #define STDLIB_STATS_BASE_DMAXSORTED_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the maximum value of a sorted double-precision floating-point strided array. */ -double stdlib_strided_dmaxsorted( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmaxsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js index b971b79e02e2..d4f61fc852cd 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,48 +31,19 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = dmaxsorted( N, x, 1 ); +* var v = dmaxsorted( x.length, x, 1 ); * // returns 3.0 */ -function dmaxsorted( N, x, stride ) { - var v1; - var v2; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - v1 = x[ (1-N) * stride ]; - v2 = x[ 0 ]; - } else { - v1 = x[ 0 ]; - v2 = x[ (N-1) * stride ]; - } - if ( isnan( v1 ) || isnan( v2 ) ) { - return NaN; - } - if ( v1 === v2 ) { - if ( isPositiveZero( v1 ) || isPositiveZero( v2 ) ) { - return 0.0; - } - return v1; - } - if ( v1 > v2 ) { - return v1; - } - return v2; +function dmaxsorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js index e28f2c171be5..bbfbda92dd2a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = dmaxsorted( N, x, 1 ); +* var v = dmaxsorted( x.length, x, 1 ); * // returns 3.0 */ -function dmaxsorted( N, x, stride ) { - return addon( N, x, stride ); +function dmaxsorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js index b083a5b78157..76a8823d27ae 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js @@ -28,20 +28,17 @@ * var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = dmaxsorted( N, x, 1 ); +* var v = dmaxsorted( x.length, x, 1 ); * // returns 3.0 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmaxsorted.ndarray( N, x, 2, 1 ); +* var v = dmaxsorted.ndarray( 4, x, 2, 1 ); * // returns 4.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js index ea52a26e0776..e5f5369fbbac 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js @@ -31,32 +31,30 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmaxsorted( N, x, 2, 1 ); +* var v = dmaxsorted( 4, x, 2, 1 ); * // returns 4.0 */ -function dmaxsorted( N, x, stride, offset ) { +function dmaxsorted( N, x, strideX, offsetX ) { var v1; var v2; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return x[ 0 ]; } - v1 = x[ offset ]; - v2 = x[ offset + ((N-1)*stride) ]; + v1 = x[ offsetX ]; + v2 = x[ offsetX + ((N-1)*strideX) ]; if ( isnan( v1 ) || isnan( v2 ) ) { return NaN; } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js index 8938dd264060..2810650cfbec 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmaxsorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmaxsorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmaxsorted( N, x, 2, 1 ); +* var v = dmaxsorted( 4, x, 2, 1 ); * // returns 4.0 */ -function dmaxsorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmaxsorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json index eac9da6f48c9..61565b33b0a3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,19 +28,20 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmaxsorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-positive-zero", "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-positive-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -49,36 +51,56 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmaxsorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-positive-zero", - "@stdlib/math/base/assert/is-nan" + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmaxsorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-positive-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-positive-zero" + "@stdlib/math/base/assert/is-positive-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c index 29545a3b5e21..8d9cd96d16ac 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmaxsorted.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxsorted( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmaxsorted)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/dmaxsorted.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/dmaxsorted.c deleted file mode 100644 index e9ad7acb5908..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/dmaxsorted.c +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmaxsorted.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_positive_zero.h" -#include - -/** -* Computes the maximum value of a sorted double-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmaxsorted( const int64_t N, const double *X, const int64_t stride ) { - double v1; - double v2; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - v1 = X[ (1-N) * stride ]; - v2 = X[ 0 ]; - } else { - v1 = X[ 0 ]; - v2 = X[ (N-1) * stride ]; - } - if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) { - return 0.0 / 0.0; // NaN - } - if ( v1 == v2 ) { - if ( stdlib_base_is_positive_zero( v1 ) || stdlib_base_is_positive_zero( v2 ) ) { - return 0.0; - } - return v1; - } - if ( v1 > v2 ) { - return v1; - } - return v2; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c new file mode 100644 index 000000000000..bc731204b781 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmaxsorted.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_positive_zero.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the maximum value of a sorted double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmaxsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the maximum value of a sorted double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + double v1; + double v2; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + v1 = X[ offsetX ]; + v2 = X[ ( (N-1)*strideX ) + offsetX ]; + if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) { + return 0.0 / 0.0; // NaN + } + if ( v1 == v2 ) { + if ( stdlib_base_is_positive_zero( v1 ) || stdlib_base_is_positive_zero( v2 ) ) { + return 0.0; + } + return v1; + } + if ( v1 > v2 ) { + return v1; + } + return v2; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js index 9decf6e9e4b3..eb4b224b3c83 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, 2 ); + v = dmaxsorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, -2 ); + v = dmaxsorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmaxsorted( N, x1, 2 ); + v = dmaxsorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js index 7946ef28b215..e26985fbf933 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, 2 ); + v = dmaxsorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, -2 ); + v = dmaxsorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmaxsorted( N, x1, 2 ); + v = dmaxsorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js index 546d36c8f705..52eef5af97b8 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, 2, 0 ); + v = dmaxsorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -148,14 +144,13 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0, 2.0, // 2 -7.0, - 3.0, // 1 + 3.0, // 1 3.0, 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, -2, 6 ); + v = dmaxsorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, 2, 1 ); + v = dmaxsorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js index b18bc5d2b7aa..77cb453e7b0c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, 2, 0 ); + v = dmaxsorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -157,14 +153,13 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0, 2.0, // 2 -7.0, - 3.0, // 1 + 3.0, // 1 3.0, 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, -2, 6 ); + v = dmaxsorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmaxsorted( N, x, 2, 1 ); + v = dmaxsorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/README.md b/lib/node_modules/@stdlib/stats/base/dmeankbn/README.md index bfd03ff5c837..464c63f65e1a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dmeankbn = require( '@stdlib/stats/base/dmeankbn' ); ``` -#### dmeankbn( N, x, stride ) +#### dmeankbn( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x` using an improved Kahan–Babuška algorithm. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeankbn( N, x, 1 ); +var v = dmeankbn( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeankbn( N, x, 2 ); +var v = dmeankbn( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmeankbn( N, x1, 2 ); +var v = dmeankbn( 4, x1, 2 ); // returns 1.25 ``` -#### dmeankbn.ndarray( N, x, stride, offset ) +#### dmeankbn.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeankbn.ndarray( N, x, 1, 0 ); +var v = dmeankbn.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeankbn.ndarray( N, x, 2, 1 ); +var v = dmeankbn.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -153,18 +144,12 @@ var v = dmeankbn.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeankbn = require( '@stdlib/stats/base/dmeankbn' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeankbn( x.length, x, 1 ); @@ -175,6 +160,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmeankbn.h" +``` + +#### stdlib_strided_dmeankbn( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeankbn( 3, x, 1 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmeankbn( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmeankbn_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeankbn_ndarray( 3, x, 1, 0 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmeankbn_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmeankbn.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dmeankbn( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.js index 80197bed4f1a..5c607146788f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeankbn = require( './../lib/dmeankbn.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeankbn = require( './../lib/dmeankbn.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.native.js index 41e89cbc5c42..621dd06fbe66 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeankbn = tryRequire( resolve( __dirname, './../lib/dmeankbn.native.js' ) ) var opts = { 'skip': ( dmeankbn instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.js index 42d6b41b45d7..f9b82e39e385 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeankbn = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeankbn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.native.js index 606d17b03960..9ef63df0f3a9 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeankbn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmeankbn instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/c/benchmark.length.c index 32e34d40ac98..68f80302ce3e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmeankbn( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmeankbn_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/repl.txt index 8ccf7d6fd7b9..4c5ce5bf868f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm and alternative indexing semantics. @@ -66,10 +63,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/types/index.d.ts index eddbcf62105d..3f7b096fc8b5 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmeankbn( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmeankbn.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/c/example.c index 513ed2bf3816..f801ef87610e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmeankbn.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dmeankbn( N, x, stride ); + double v = stdlib_strided_dmeankbn( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/index.js index b925551ecf89..dcfd9b4768cc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeankbn = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeankbn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/include/stdlib/stats/base/dmeankbn.h b/lib/node_modules/@stdlib/stats/base/dmeankbn/include/stdlib/stats/base/dmeankbn.h index 80395526b40a..ac4a030442f6 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/include/stdlib/stats/base/dmeankbn.h +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/include/stdlib/stats/base/dmeankbn.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMEANKBN_H #define STDLIB_STATS_BASE_DMEANKBN_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. */ -double stdlib_strided_dmeankbn( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmeankbn)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmeankbn_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.js index 732bdbd15c67..8f575c041c3c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.js @@ -20,7 +20,8 @@ // MODULES // -var dsumkbn = require( '@stdlib/blas/ext/base/dsumkbn' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,26 +39,19 @@ var dsumkbn = require( '@stdlib/blas/ext/base/dsumkbn' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeankbn( N, x, 1 ); +* var v = dmeankbn( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeankbn( N, x, stride ) { - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - return dsumkbn( N, x, stride ) / N; +function dmeankbn( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.native.js index d14f319ca98f..dec69ed2ad9f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/dmeankbn.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeankbn( N, x, 1 ); +* var v = dmeankbn( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeankbn( N, x, stride ) { - return addon( N, x, stride ); +function dmeankbn( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/index.js index 1ff126321e86..cd7148deb0c5 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/index.js @@ -28,20 +28,17 @@ * var dmeankbn = require( '@stdlib/stats/base/dmeankbn' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeankbn( N, x, 1 ); +* var v = dmeankbn( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmeankbn = require( '@stdlib/stats/base/dmeankbn' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeankbn.ndarray( N, x, 2, 1 ); +* var v = dmeankbn.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.js index 3c6a5a0bfbb4..9dd04923145e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.js @@ -39,27 +39,25 @@ var dsumkbn = require( '@stdlib/blas/ext/base/dsumkbn' ).ndarray; * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array * @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeankbn( N, x, 2, 1 ); +* var v = dmeankbn( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeankbn( N, x, stride, offset ) { +function dmeankbn( N, x, stride, offsetX ) { if ( N <= 0 ) { return NaN; } if ( N === 1 || stride === 0 ) { - return x[ offset ]; + return x[ offsetX ]; } - return dsumkbn( N, x, stride, offset ) / N; + return dsumkbn( N, x, stride, offsetX ) / N; } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.native.js index cc7cb53ff9df..b9f78806909d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmeankbn.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmeankbn.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeankbn( N, x, 2, 1 ); +* var v = dmeankbn( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeankbn( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmeankbn( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeankbn/manifest.json index 2f068cdd4b99..3134efdea577 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,18 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmeankbn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/dsum", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumkbn", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,34 +50,53 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmeankbn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/dsum" + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumkbn" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmeankbn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumkbn" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/dsum" + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumkbn" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeankbn/src/addon.c index 13c61ff0afee..16ab841bf671 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmeankbn.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmeankbn( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeankbn)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeankbn_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/src/dmeankbn.c b/lib/node_modules/@stdlib/stats/base/dmeankbn/src/dmeankbn.c deleted file mode 100644 index 21f543d6a9d6..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/src/dmeankbn.c +++ /dev/null @@ -1,47 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeankbn.h" -#include "stdlib/blas/ext/base/dsum.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. -* -* ## Method -* -* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). -* -* ## References -* -* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmeankbn( const int64_t N, const double *X, const int64_t stride ) { - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - return stdlib_strided_dsum( N, X, stride ) / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeankbn/src/main.c new file mode 100644 index 000000000000..18d7fbce2cc1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeankbn.h" +#include "stdlib/blas/ext/base/dsumkbn.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm. +* +* ## Method +* +* - This implementation uses an "improved Kahan–Babuška algorithm", as described by Neumaier (1974). +* +* ## References +* +* - Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." _Zeitschrift Für Angewandte Mathematik Und Mechanik_ 54 (1): 39–51. doi:[10.1002/zamm.19740540106](https://doi.org/10.1002/zamm.19740540106). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeankbn)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmeankbn_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeankbn_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return API_SUFFIX(stdlib_strided_dsumkbn_ndarray)( N, X, strideX, offsetX ) / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.js index 5a81b0edb8eb..caf895123d94 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeankbn = require( './../lib/dmeankbn.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, 2 ); + v = dmeankbn( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, -2 ); + v = dmeankbn( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeankbn( N, x1, 2 ); + v = dmeankbn( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.native.js index cd204870c370..d9b8feab7b49 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.dmeankbn.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, 2 ); + v = dmeankbn( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, -2 ); + v = dmeankbn( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeankbn( N, x1, 2 ); + v = dmeankbn( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.js index 9ad93874a243..75c58ceaec10 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeankbn = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, 2, 0 ); + v = dmeankbn( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, -2, 6 ); + v = dmeankbn( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, 2, 1 ); + v = dmeankbn( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.native.js index 9ad61a946cd9..d7481c6ffd08 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, 2, 0 ); + v = dmeankbn( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, -2, 6 ); + v = dmeankbn( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeankbn( N, x, 2, 1 ); + v = dmeankbn( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/README.md b/lib/node_modules/@stdlib/stats/base/dmeankbn2/README.md index 79ba581a937c..9cd39328b22a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dmeankbn2 = require( '@stdlib/stats/base/dmeankbn2' ); ``` -#### dmeankbn2( N, x, stride ) +#### dmeankbn2( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x` using a second-order iterative Kahan–Babuška algorithm. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeankbn2( N, x, 1 ); +var v = dmeankbn2( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeankbn2( N, x, 2 ); +var v = dmeankbn2( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmeankbn2( N, x1, 2 ); +var v = dmeankbn2( 4, x1, 2 ); // returns 1.25 ``` -#### dmeankbn2.ndarray( N, x, stride, offset ) +#### dmeankbn2.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeankbn2.ndarray( N, x, 1, 0 ); +var v = dmeankbn2.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeankbn2.ndarray( N, x, 2, 1 ); +var v = dmeankbn2.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -153,18 +144,12 @@ var v = dmeankbn2.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeankbn2 = require( '@stdlib/stats/base/dmeankbn2' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeankbn2( x.length, x, 1 ); @@ -175,6 +160,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmeankbn2.h" +``` + +#### stdlib_strided_dmeankbn2( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeankbn2( 3, x, 1 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmeankbn2( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmeankbn2_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeankbn2_ndarray( 3, x, 1, 0 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmeankbn2_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmeankbn2.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dmeankbn2( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.js index aa3686426e6f..94ef669117c1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeankbn2 = require( './../lib/dmeankbn2.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeankbn2 = require( './../lib/dmeankbn2.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.native.js index b2eecd4c4da9..40cefc5afb5e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeankbn2 = tryRequire( resolve( __dirname, './../lib/dmeankbn2.native.js' ) var opts = { 'skip': ( dmeankbn2 instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.js index 09b56f2896e3..4440e6398d18 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeankbn2 = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeankbn2 = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.native.js index 9bca0d443e1f..8a6d233e08d2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeankbn2 = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( dmeankbn2 instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/c/benchmark.length.c index 9bdd94d80e1e..5c4406ae1521 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmeankbn2( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmeankbn2_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/repl.txt index 308ce9919a89..54574cfadb7d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. @@ -66,10 +63,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/types/index.d.ts index f8732f1de76f..1fd0d5685388 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmeankbn2( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmeankbn2.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/c/example.c index 08615b214eb1..15ded0b20f29 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmeankbn2.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dmeankbn2( N, x, stride ); + double v = stdlib_strided_dmeankbn2( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/index.js index 9bfda33bc537..528c93604fdc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeankbn2 = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeankbn2( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/include/stdlib/stats/base/dmeankbn2.h b/lib/node_modules/@stdlib/stats/base/dmeankbn2/include/stdlib/stats/base/dmeankbn2.h index 4261bd047eae..af966ae860fb 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/include/stdlib/stats/base/dmeankbn2.h +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/include/stdlib/stats/base/dmeankbn2.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMEANKBN2_H #define STDLIB_STATS_BASE_DMEANKBN2_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. */ -double stdlib_strided_dmeankbn2( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmeankbn2)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmeankbn2_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.js index 5f360ab52eb6..6d0f99f131be 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.js @@ -20,7 +20,8 @@ // MODULES // -var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -38,26 +39,19 @@ var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeankbn2( N, x, 1 ); +* var v = dmeankbn2( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeankbn2( N, x, stride ) { - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - return dsumkbn2( N, x, stride ) / N; +function dmeankbn2( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.native.js index 3c33c6516fcd..b53872d305d7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/dmeankbn2.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeankbn2( N, x, 1 ); +* var v = dmeankbn2( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeankbn2( N, x, stride ) { - return addon( N, x, stride ); +function dmeankbn2( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/index.js index 8119e5e605d8..a8330f52309a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/index.js @@ -28,20 +28,17 @@ * var dmeankbn2 = require( '@stdlib/stats/base/dmeankbn2' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeankbn2( N, x, 1 ); +* var v = dmeankbn2( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmeankbn2 = require( '@stdlib/stats/base/dmeankbn2' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeankbn2.ndarray( N, x, 2, 1 ); +* var v = dmeankbn2.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.js index aaf215d410c9..3afca374064c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.js @@ -38,28 +38,26 @@ var dsumkbn2 = require( '@stdlib/blas/ext/base/dsumkbn2' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeankbn2( N, x, 2, 1 ); +* var v = dmeankbn2( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeankbn2( N, x, stride, offset ) { +function dmeankbn2( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return dsumkbn2( N, x, stride, offset ) / N; + return dsumkbn2( N, x, strideX, offsetX ) / N; } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.native.js index d053dd4bcb48..1bd38b1c2510 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmeankbn2.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmeankbn2.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeankbn2( N, x, 2, 1 ); +* var v = dmeankbn2( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeankbn2( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmeankbn2( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeankbn2/manifest.json index d660d766efdb..ce69744dc239 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmeankbn2.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumkbn2", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -48,33 +50,52 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmeankbn2.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumkbn2" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmeankbn2.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumkbn2" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumkbn2" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/addon.c index 31051791b550..5ecf1de083b3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmeankbn2.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmeankbn2( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeankbn2)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeankbn2_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/dmeankbn2.c b/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/dmeankbn2.c deleted file mode 100644 index 492970fc8679..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/dmeankbn2.c +++ /dev/null @@ -1,47 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeankbn2.h" -#include "stdlib/blas/ext/base/dsumkbn2.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. -* -* ## Method -* -* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). -* -* ## References -* -* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmeankbn2( const int64_t N, const double *X, const int64_t stride ) { - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - return stdlib_strided_dsumkbn2( N, X, stride ) / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/main.c new file mode 100644 index 000000000000..fffffbb830ad --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeankbn2.h" +#include "stdlib/blas/ext/base/dsumkbn2.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. +* +* ## Method +* +* - This implementation uses a second-order iterative Kahan–Babuška algorithm, as described by Klein (2005). +* +* ## References +* +* - Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." _Computing_ 76 (3): 279–93. doi:[10.1007/s00607-005-0139-x](https://doi.org/10.1007/s00607-005-0139-x). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeankbn2)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmeankbn2_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeankbn2_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return API_SUFFIX(stdlib_strided_dsumkbn2_ndarray)( N, X, strideX, offsetX ) / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.js index fd3968d189d4..2435a6920440 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeankbn2 = require( './../lib/dmeankbn2.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, 2 ); + v = dmeankbn2( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, -2 ); + v = dmeankbn2( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeankbn2( N, x1, 2 ); + v = dmeankbn2( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.native.js index 124266c8f904..729664806835 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.dmeankbn2.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, 2 ); + v = dmeankbn2( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, -2 ); + v = dmeankbn2( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeankbn2( N, x1, 2 ); + v = dmeankbn2( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.js index a16fc4fc9daf..acdeba736b1a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeankbn2 = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, 2, 0 ); + v = dmeankbn2( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, -2, 6 ); + v = dmeankbn2( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, 2, 1 ); + v = dmeankbn2( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.native.js index 5da2ea8d1a34..1abd0823a065 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeankbn2/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, 2, 0 ); + v = dmeankbn2( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, -2, 6 ); + v = dmeankbn2( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeankbn2( N, x, 2, 1 ); + v = dmeankbn2( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/README.md b/lib/node_modules/@stdlib/stats/base/dmeanli/README.md index e27e0cf2fec3..86cac69872d9 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dmeanli = require( '@stdlib/stats/base/dmeanli' ); ``` -#### dmeanli( N, x, stride ) +#### dmeanli( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanli( N, x, 1 ); +var v = dmeanli( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanli( N, x, 2 ); +var v = dmeanli( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmeanli( N, x1, 2 ); +var v = dmeanli( 4, x1, 2 ); // returns 1.25 ``` -#### dmeanli.ndarray( N, x, stride, offset ) +#### dmeanli.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanli.ndarray( N, x, 1, 0 ); +var v = dmeanli.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanli.ndarray( N, x, 2, 1 ); +var v = dmeanli.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -154,18 +145,12 @@ var v = dmeanli.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanli = require( '@stdlib/stats/base/dmeanli' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanli( x.length, x, 1 ); @@ -176,6 +161,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmeanli.h" +``` + +#### stdlib_strided_dmeanli( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanli( 3, x, 1 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmeanli( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmeanli_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanli_ndarray( 3, x, 1, 0 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmeanli_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmeanli.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dmeanli( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.js index ea11e280c6ac..731724a2fe75 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanli = require( './../lib/dmeanli.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanli = require( './../lib/dmeanli.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.native.js index e5fa10c7ab42..2d7d31044d4e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanli = tryRequire( resolve( __dirname, './../lib/dmeanli.native.js' ) ); var opts = { 'skip': ( dmeanli instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.js index 19d166634b01..39beddb9c1bb 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanli = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanli = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.native.js index c9ff08310537..798be4f8250a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanli = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmeanli instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/c/benchmark.length.c index 2f64700c5c17..fb3d686731e1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmeanli( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmeanli_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeanli/docs/repl.txt index 4c68e6e5eaad..50ac9f69bc99 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -66,10 +63,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmeanli/docs/types/index.d.ts index c0a6a3e8d86f..5ceffa65e34d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmeanli( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmeanli.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeanli/examples/c/example.c index 80f0343be0b7..eab94ee573a4 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmeanli.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dmeanli( N, x, stride ); + double v = stdlib_strided_dmeanli( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeanli/examples/index.js index 09a89bf01f97..221f365295e6 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanli = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanli( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/include/stdlib/stats/base/dmeanli.h b/lib/node_modules/@stdlib/stats/base/dmeanli/include/stdlib/stats/base/dmeanli.h index e59af74ae18d..f043ae69c6bd 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/include/stdlib/stats/base/dmeanli.h +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/include/stdlib/stats/base/dmeanli.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMEANLI_H #define STDLIB_STATS_BASE_DMEANLI_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. */ -double stdlib_strided_dmeanli( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmeanli)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmeanli_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.js b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.js index 8641f5970d76..3c120ffc39b3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.js @@ -20,7 +20,8 @@ // MODULES // -var dapxsum = require( '@stdlib/blas/ext/base/dapxsum' ).ndarray; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -34,33 +35,19 @@ var dapxsum = require( '@stdlib/blas/ext/base/dapxsum' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanli( N, x, 1 ); +* var v = dmeanli( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanli( N, x, stride ) { - var ix; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - return x[ ix ] + ( dapxsum( N-1, -x[ ix ], x, stride, ix+stride ) / N ); +function dmeanli( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.native.js b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.native.js index 110beb5ecb41..1039ea046c0a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/dmeanli.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanli( N, x, 1 ); +* var v = dmeanli( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanli( N, x, stride ) { - return addon( N, x, stride ); +function dmeanli( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/index.js index f774bc02880f..2a94dfd2086a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/index.js @@ -28,20 +28,17 @@ * var dmeanli = require( '@stdlib/stats/base/dmeanli' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanli( N, x, 1 ); +* var v = dmeanli( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmeanli = require( '@stdlib/stats/base/dmeanli' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanli.ndarray( N, x, 2, 1 ); +* var v = dmeanli.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.js index 965ab01b7d84..d4a30355ae9d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.js @@ -34,28 +34,26 @@ var dapxsum = require( '@stdlib/blas/ext/base/dapxsum' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanli( N, x, 2, 1 ); +* var v = dmeanli( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanli( N, x, stride, offset ) { +function dmeanli( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return x[ offset ] + ( dapxsum( N-1, -x[ offset ], x, stride, offset+stride ) / N ); // eslint-disable-line max-len + return x[ offsetX ] + ( dapxsum( N-1, -x[ offsetX ], x, strideX, offsetX+strideX ) / N ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.native.js index 0649a08ff355..35918c8ea04d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmeanli.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmeanli.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanli( N, x, 2, 1 ); +* var v = dmeanli( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanli( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmeanli( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeanli/manifest.json index 9229bc3c6fd3..e669c336813b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmeanli.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dapxsum", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -48,33 +50,52 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmeanli.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dapxsum" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmeanli.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dapxsum" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dapxsum" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeanli/src/addon.c index 97b55ecf2bf4..502ea8b2306a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmeanli.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmeanli( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanli)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanli_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/src/dmeanli.c b/lib/node_modules/@stdlib/stats/base/dmeanli/src/dmeanli.c deleted file mode 100644 index dc86cba878d1..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/src/dmeanli.c +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanli.h" -#include "stdlib/blas/ext/base/dapxsum.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. -* -* ## References -* -* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmeanli( const int64_t N, const double *X, const int64_t stride ) { - int64_t ix; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - return X[ ix ] + ( stdlib_strided_dapxsum( N-1, -X[ ix ], X+( (stride > 0) ? stride : 0 ), stride ) / (double)N ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeanli/src/main.c new file mode 100644 index 000000000000..1cf12298d5d3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/src/main.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeanli.h" +#include "stdlib/blas/ext/base/dapxsum.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm. +* +* ## References +* +* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanli)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmeanli_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanli_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return X[ offsetX ] + ( API_SUFFIX(stdlib_strided_dapxsum_ndarray)( N-1, -X[ offsetX ], X, strideX, offsetX + strideX ) / (double)N ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.js b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.js index 101a26235b4b..61ecdc57288f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanli = require( './../lib/dmeanli.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, 2 ); + v = dmeanli( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, -2 ); + v = dmeanli( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanli( N, x1, 2 ); + v = dmeanli( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.native.js b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.native.js index e7011fcb3ab0..85c88edb0360 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.dmeanli.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, 2 ); + v = dmeanli( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, -2 ); + v = dmeanli( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanli( N, x1, 2 ); + v = dmeanli( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.js index 1689d7eecb7e..ccd17618f83c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanli = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, 2, 0 ); + v = dmeanli( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, -2, 6 ); + v = dmeanli( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, 2, 1 ); + v = dmeanli( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.native.js index 6afb463ca90b..3a2a9cdf46f7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanli/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, 2, 0 ); + v = dmeanli( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, -2, 6 ); + v = dmeanli( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanli( N, x, 2, 1 ); + v = dmeanli( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/README.md b/lib/node_modules/@stdlib/stats/base/dmeanors/README.md index ef5b9edb6552..93e949222b49 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dmeanors = require( '@stdlib/stats/base/dmeanors' ); ``` -#### dmeanors( N, x, stride ) +#### dmeanors( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x` using ordinary recursive summation. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanors( N, x, 1 ); +var v = dmeanors( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanors( N, x, 2 ); +var v = dmeanors( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmeanors( N, x1, 2 ); +var v = dmeanors( 4, x1, 2 ); // returns 1.25 ``` -#### dmeanors.ndarray( N, x, stride, offset ) +#### dmeanors.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanors.ndarray( N, x, 1, 0 ); +var v = dmeanors.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanors.ndarray( N, x, 2, 1 ); +var v = dmeanors.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -154,18 +145,12 @@ var v = dmeanors.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanors = require( '@stdlib/stats/base/dmeanors' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanors( x.length, x, 1 ); @@ -176,6 +161,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmeanors.h" +``` + +#### stdlib_strided_dmeanors( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using ordinary recursive summation. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanors( 3, x, 1 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmeanors( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmeanors_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanors_ndarray( 3, x, 1, 0 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmeanors_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmeanors.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dmeanors( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.js index 0ab8d27af04f..9525c2c2756f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib/dmeanors.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanors = require( './../lib/dmeanors.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.native.js index 566a8bd28b1b..f52bbe94f6a7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanors = tryRequire( resolve( __dirname, './../lib/dmeanors.native.js' ) ) var opts = { 'skip': ( dmeanors instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.js index 606a2f42df50..fffc1ef8c0fc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.native.js index 5ded0fabdb69..091900e77a8f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmeanors instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/c/benchmark.length.c index e42713363397..c148f4c9549d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmeanors( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmeanors_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeanors/docs/repl.txt index 28ea6ddcee0d..f3ba55c5735b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. @@ -65,10 +62,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmeanors/docs/types/index.d.ts index 85c1b0761529..75a6459338c9 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmeanors( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmeanors.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeanors/examples/c/example.c index 76cb7e915e40..38c5b576f0f8 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmeanors.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dmeanors( N, x, stride ); + double v = stdlib_strided_dmeanors( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeanors/examples/index.js index 087fa521591f..f0a140c36168 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanors = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/include/stdlib/stats/base/dmeanors.h b/lib/node_modules/@stdlib/stats/base/dmeanors/include/stdlib/stats/base/dmeanors.h index 909d7215c7d5..c508c4e9495f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/include/stdlib/stats/base/dmeanors.h +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/include/stdlib/stats/base/dmeanors.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMEANORS_H #define STDLIB_STATS_BASE_DMEANORS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. */ -double stdlib_strided_dmeanors( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmeanors)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmeanors_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.js b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.js index 9b96ecff81e7..c02463849521 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.js @@ -20,7 +20,8 @@ // MODULES // -var dsumors = require( '@stdlib/blas/ext/base/dsumors' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,26 +31,19 @@ var dsumors = require( '@stdlib/blas/ext/base/dsumors' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanors( N, x, 1 ); +* var v = dmeanors( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanors( N, x, stride ) { - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - return dsumors( N, x, stride ) / N; +function dmeanors( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.native.js b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.native.js index 37421aea14a2..63a193e1f77b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/dmeanors.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanors( N, x, 1 ); +* var v = dmeanors( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanors( N, x, stride ) { - return addon( N, x, stride ); +function dmeanors( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/index.js index 3172955e48cc..420515201cf6 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/index.js @@ -28,20 +28,17 @@ * var dmeanors = require( '@stdlib/stats/base/dmeanors' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanors( N, x, 1 ); +* var v = dmeanors( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmeanors = require( '@stdlib/stats/base/dmeanors' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanors.ndarray( N, x, 2, 1 ); +* var v = dmeanors.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.js index cca34655640f..47763f2a7941 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.js @@ -30,28 +30,26 @@ var dsumors = require( '@stdlib/blas/ext/base/dsumors' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanors( N, x, 2, 1 ); +* var v = dmeanors( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanors( N, x, stride, offset ) { +function dmeanors( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return dsumors( N, x, stride, offset ) / N; + return dsumors( N, x, strideX, offsetX ) / N; } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.native.js index 84e10b7f9e00..c78167f66496 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmeanors.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmeanors.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanors( N, x, 2, 1 ); +* var v = dmeanors( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanors( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmeanors( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeanors/manifest.json index c4d125525906..58b25e8b64fc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumors", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -48,33 +50,52 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumors" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumors" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumors" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeanors/src/addon.c index 4d4bffc1a971..1985367b0455 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmeanors.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmeanors( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanors)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanors_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/src/dmeanors.c b/lib/node_modules/@stdlib/stats/base/dmeanors/src/dmeanors.c deleted file mode 100644 index d2b73a48343b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/src/dmeanors.c +++ /dev/null @@ -1,39 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanors.h" -#include "stdlib/blas/ext/base/dsumors.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmeanors( const int64_t N, const double *X, const int64_t stride ) { - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - return stdlib_strided_dsumors( N, X, stride ) / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeanors/src/main.c new file mode 100644 index 000000000000..297fb62286a1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/src/main.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeanors.h" +#include "stdlib/blas/ext/base/dsumors.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanors)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmeanors_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanors_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return API_SUFFIX(stdlib_strided_dsumors_ndarray)( N, X, strideX, offsetX ) / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.js b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.js index bf78c7147c8c..29dd9f902197 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanors = require( './../lib/dmeanors.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, 2 ); + v = dmeanors( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, -2 ); + v = dmeanors( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanors( N, x1, 2 ); + v = dmeanors( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.native.js b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.native.js index f8e713fabad4..7b19a256aae7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.dmeanors.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, 2 ); + v = dmeanors( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, -2 ); + v = dmeanors( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanors( N, x1, 2 ); + v = dmeanors( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.js index 5b99a88e4ab6..7beb2804b9db 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanors = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, 2, 0 ); + v = dmeanors( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, -2, 6 ); + v = dmeanors( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, 2, 1 ); + v = dmeanors( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.native.js index 367683dea94a..05c9310918bf 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanors/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, 2, 0 ); + v = dmeanors( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, -2, 6 ); + v = dmeanors( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanors( N, x, 2, 1 ); + v = dmeanors( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/README.md b/lib/node_modules/@stdlib/stats/base/dmeanpw/README.md index 42648a1c1c87..7c25a769e5fe 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dmeanpw = require( '@stdlib/stats/base/dmeanpw' ); ``` -#### dmeanpw( N, x, stride ) +#### dmeanpw( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x` using pairwise summation. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanpw( N, x, 1 ); +var v = dmeanpw( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanpw( N, x, 2 ); +var v = dmeanpw( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmeanpw( N, x1, 2 ); +var v = dmeanpw( 4, x1, 2 ); // returns 1.25 ``` -#### dmeanpw.ndarray( N, x, stride, offset ) +#### dmeanpw.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanpw.ndarray( N, x, 1, 0 ); +var v = dmeanpw.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanpw.ndarray( N, x, 2, 1 ); +var v = dmeanpw.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -154,18 +145,12 @@ var v = dmeanpw.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanpw = require( '@stdlib/stats/base/dmeanpw' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanpw( x.length, x, 1 ); @@ -176,6 +161,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmeanpw.h" +``` + +#### stdlib_strided_dmeanpw( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanpw( 3, x, 1 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmeanpw( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmeanpw_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanpw_ndarray( 3, x, 1, 0 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmeanpw_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmeanpw.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dmeanpw( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.js index 55dd91550bba..1c583d684f99 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib/dmeanpw.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanpw = require( './../lib/dmeanpw.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.native.js index 50c7619d07fb..c0c74ee51370 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanpw = tryRequire( resolve( __dirname, './../lib/dmeanpw.native.js' ) ); var opts = { 'skip': ( dmeanpw instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.js index 514f739ae328..69c392290801 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.native.js index 0d75fbd7e352..e1b227ce1362 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmeanpw instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/c/benchmark.length.c index 9f477ae0bde1..6cf638225211 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmeanpw( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmeanpw_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/repl.txt index 59a6766de847..546642f87989 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. @@ -65,10 +62,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/types/index.d.ts index 24f79e3454e6..cf736c23329a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmeanpw.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/c/example.c index e536a847024e..98d8da2d5dd8 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmeanpw.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dmeanpw( N, x, stride ); + double v = stdlib_strided_dmeanpw( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/index.js index 88785ea57b34..a0e41d6280b2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanpw = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/include/stdlib/stats/base/dmeanpw.h b/lib/node_modules/@stdlib/stats/base/dmeanpw/include/stdlib/stats/base/dmeanpw.h index bb2bd3b692ed..f9e5f46b8fc5 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/include/stdlib/stats/base/dmeanpw.h +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/include/stdlib/stats/base/dmeanpw.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DMEANPW_H #define STDLIB_STATS_BASE_DMEANPW_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation. */ -double stdlib_strided_dmeanpw( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmeanpw)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmeanpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.js index 23c3d495bc54..74174953d87d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.js @@ -20,7 +20,8 @@ // MODULES // -var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,26 +31,19 @@ var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanpw( N, x, 1 ); +* var v = dmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanpw( N, x, stride ) { - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - return dsumpw( N, x, stride ) / N; +function dmeanpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.native.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.native.js index 07aeb0ca1142..6d5aeea37e05 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/dmeanpw.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanpw( N, x, 1 ); +* var v = dmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanpw( N, x, stride ) { - return addon( N, x, stride ); +function dmeanpw( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/index.js index aedcd8241ba8..4bd5fb715ad4 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/index.js @@ -28,20 +28,17 @@ * var dmeanpw = require( '@stdlib/stats/base/dmeanpw' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanpw( N, x, 1 ); +* var v = dmeanpw( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmeanpw = require( '@stdlib/stats/base/dmeanpw' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanpw.ndarray( N, x, 2, 1 ); +* var v = dmeanpw.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.js index 1d82572ac62a..f0913441942f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.js @@ -30,28 +30,26 @@ var dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanpw( N, x, 2, 1 ); +* var v = dmeanpw( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanpw( N, x, stride, offset ) { +function dmeanpw( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return dsumpw( N, x, stride, offset ) / N; + return dsumpw( N, x, strideX, offsetX ) / N; } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.native.js index 88f56d74c642..3e810de1e8cf 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmeanpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmeanpw.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanpw( N, x, 2, 1 ); +* var v = dmeanpw( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanpw( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmeanpw( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeanpw/manifest.json index 8935fd87c0d8..455803ffaf83 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dmeanpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumpw", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -48,33 +50,52 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dmeanpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumpw" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dmeanpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dsumpw" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dsumpw" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeanpw/src/addon.c index 3000af106511..2b27fbf751cc 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmeanpw.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmeanpw( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanpw)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanpw_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/src/dmeanpw.c b/lib/node_modules/@stdlib/stats/base/dmeanpw/src/dmeanpw.c deleted file mode 100644 index 15667f776eb5..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/src/dmeanpw.c +++ /dev/null @@ -1,39 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanpw.h" -#include "stdlib/blas/ext/base/dsumpw.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmeanpw( const int64_t N, const double *X, const int64_t stride ) { - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - return stdlib_strided_dsumpw( N, X, stride ) / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeanpw/src/main.c new file mode 100644 index 000000000000..967a09848012 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/src/main.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeanpw.h" +#include "stdlib/blas/ext/base/dsumpw.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanpw)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmeanpw_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return API_SUFFIX(stdlib_strided_dsumpw_ndarray)( N, X, strideX, offsetX ) / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.js index ff9dea80fdb7..4741f3793513 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanpw = require( './../lib/dmeanpw.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, 2 ); + v = dmeanpw( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, -2 ); + v = dmeanpw( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanpw( N, x1, 2 ); + v = dmeanpw( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.native.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.native.js index 00d048762bb7..8a54690fb397 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.dmeanpw.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, 2 ); + v = dmeanpw( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, -2 ); + v = dmeanpw( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanpw( N, x1, 2 ); + v = dmeanpw( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.js index 5f074e7645fa..3edd89b74984 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanpw = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, 2, 0 ); + v = dmeanpw( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, -2, 6 ); + v = dmeanpw( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, 2, 1 ); + v = dmeanpw( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.native.js index cb8de9f2a420..4e2ff8fb13be 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanpw/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, 2, 0 ); + v = dmeanpw( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, -2, 6 ); + v = dmeanpw( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanpw( N, x, 2, 1 ); + v = dmeanpw( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanstdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dmeanstdev/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanstdev/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmeanstdev/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, 2, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_dmeanstdev)( N, correction, X, strideX, Out, strideOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanstdev/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmeanstdev/src/addon.cpp deleted file mode 100644 index 512607cd81fe..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanstdev/src/addon.cpp +++ /dev/null @@ -1,164 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanstdev.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmeanstdev { - - /** - * Computes the mean and standard deviation of a double-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects six arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `strideX`: `X` stride length - * - `Out`: output array - * - `strideOut`: `Out` stride length - */ - napi_value node_dmeanstdev( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 6; - napi_value argv[ 6 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 6 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res2; - status = napi_is_typedarray( env, argv[ 2 ], &res2 ); - assert( status == napi_ok ); - if ( res2 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - bool res4; - status = napi_is_typedarray( env, argv[ 4 ], &res4 ); - assert( status == napi_ok ); - if ( res4 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype5; - status = napi_typeof( env, argv[ 5 ], &vtype5 ); - assert( status == napi_ok ); - if ( vtype5 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 3 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideOut; - status = napi_get_value_int64( env, argv[ 5 ], &strideOut ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype4; - size_t olen; - void *Out; - status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &olen, &Out, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype4 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - if ( llabs(strideOut) > (int64_t)olen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the required number of output elements." ); - return nullptr; - } - - stdlib_strided_dmeanstdev( N, correction, (double *)X, strideX, (double *)Out, strideOut ); - - return nullptr; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmeanstdev, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmeanstdev diff --git a/lib/node_modules/@stdlib/stats/base/dmeanstdev/src/dmeanstdev.c b/lib/node_modules/@stdlib/stats/base/dmeanstdev/src/main.c similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmeanstdev/src/dmeanstdev.c rename to lib/node_modules/@stdlib/stats/base/dmeanstdev/src/main.c diff --git a/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/include.gypi b/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, 2, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_dmeanstdevpn)( N, correction, X, strideX, Out, strideOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/addon.cpp deleted file mode 100644 index eaabf59861ca..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/addon.cpp +++ /dev/null @@ -1,164 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanstdevpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmeanstdevpn { - - /** - * Computes the mean and standard deviation of a double-precision floating-point strided array using a two-pass algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects six arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `strideX`: `X` stride length - * - `Out`: output array - * - `strideOut`: `Out` stride length - */ - napi_value node_dmeanstdevpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 6; - napi_value argv[ 6 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 6 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res2; - status = napi_is_typedarray( env, argv[ 2 ], &res2 ); - assert( status == napi_ok ); - if ( res2 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - bool res4; - status = napi_is_typedarray( env, argv[ 4 ], &res4 ); - assert( status == napi_ok ); - if ( res4 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype5; - status = napi_typeof( env, argv[ 5 ], &vtype5 ); - assert( status == napi_ok ); - if ( vtype5 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 3 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideOut; - status = napi_get_value_int64( env, argv[ 5 ], &strideOut ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype4; - size_t olen; - void *Out; - status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &olen, &Out, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype4 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - if ( llabs(strideOut) > (int64_t)olen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the required number of output elements." ); - return nullptr; - } - - stdlib_strided_dmeanstdevpn( N, correction, (double *)X, strideX, (double *)Out, strideOut ); - - return nullptr; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmeanstdevpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmeanstdevpn diff --git a/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/dmeanstdevpn.c b/lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/main.c similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/dmeanstdevpn.c rename to lib/node_modules/@stdlib/stats/base/dmeanstdevpn/src/main.c diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvar/include.gypi b/lib/node_modules/@stdlib/stats/base/dmeanvar/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanvar/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmeanvar/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, 2, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_dmeanvar)( N, correction, X, strideX, Out, strideOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvar/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmeanvar/src/addon.cpp deleted file mode 100644 index 06be1a695193..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanvar/src/addon.cpp +++ /dev/null @@ -1,164 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanvar.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmeanvar { - - /** - * Computes the mean and variance of a double-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects six arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `strideX`: `X` stride length - * - `Out`: output array - * - `strideOut`: `Out` stride length - */ - napi_value node_dmeanvar( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 6; - napi_value argv[ 6 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 6 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res2; - status = napi_is_typedarray( env, argv[ 2 ], &res2 ); - assert( status == napi_ok ); - if ( res2 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - bool res4; - status = napi_is_typedarray( env, argv[ 4 ], &res4 ); - assert( status == napi_ok ); - if ( res4 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype5; - status = napi_typeof( env, argv[ 5 ], &vtype5 ); - assert( status == napi_ok ); - if ( vtype5 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 3 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideOut; - status = napi_get_value_int64( env, argv[ 5 ], &strideOut ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype4; - size_t olen; - void *Out; - status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &olen, &Out, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype4 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - if ( llabs(strideOut) > (int64_t)olen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the required number of output elements." ); - return nullptr; - } - - stdlib_strided_dmeanvar( N, correction, (double *)X, strideX, (double *)Out, strideOut ); - - return nullptr; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmeanvar, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmeanvar diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvar/src/dmeanvar.c b/lib/node_modules/@stdlib/stats/base/dmeanvar/src/main.c similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmeanvar/src/dmeanvar.c rename to lib/node_modules/@stdlib/stats/base/dmeanvar/src/main.c diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include.gypi b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, 2, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_dmeanvarpn)( N, correction, X, strideX, Out, strideOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.cpp deleted file mode 100644 index 00f34fa95666..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/addon.cpp +++ /dev/null @@ -1,164 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanvarpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmeanvarpn { - - /** - * Computes the mean and variance of a double-precision floating-point strided array using a two-pass algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects six arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `strideX`: `X` stride length - * - `Out`: output array - * - `strideOut`: `Out` stride length - */ - napi_value node_dmeanvarpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 6; - napi_value argv[ 6 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 6 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 6 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res2; - status = napi_is_typedarray( env, argv[ 2 ], &res2 ); - assert( status == napi_ok ); - if ( res2 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - bool res4; - status = napi_is_typedarray( env, argv[ 4 ], &res4 ); - assert( status == napi_ok ); - if ( res4 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype5; - status = napi_typeof( env, argv[ 5 ], &vtype5 ); - assert( status == napi_ok ); - if ( vtype5 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Sixth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 3 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideOut; - status = napi_get_value_int64( env, argv[ 5 ], &strideOut ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype4; - size_t olen; - void *Out; - status = napi_get_typedarray_info( env, argv[ 4 ], &vtype4, &olen, &Out, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype4 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a Float64Array." ); - return nullptr; - } - if ( llabs(strideOut) > (int64_t)olen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fifth argument has insufficient elements based on the associated stride and the required number of output elements." ); - return nullptr; - } - - stdlib_strided_dmeanvarpn( N, correction, (double *)X, strideX, (double *)Out, strideOut ); - - return nullptr; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmeanvarpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmeanvarpn diff --git a/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/dmeanvarpn.c b/lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/main.c similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/dmeanvarpn.c rename to lib/node_modules/@stdlib/stats/base/dmeanvarpn/src/main.c diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dmeanwd/README.md index 323b3a45fcdb..69bb79be6859 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dmeanwd = require( '@stdlib/stats/base/dmeanwd' ); ``` -#### dmeanwd( N, x, stride ) +#### dmeanwd( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x` using Welford's algorithm. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanwd( N, x, 1 ); +var v = dmeanwd( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanwd( N, x, 2 ); +var v = dmeanwd( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmeanwd( N, x1, 2 ); +var v = dmeanwd( 4, x1, 2 ); // returns 1.25 ``` -#### dmeanwd.ndarray( N, x, stride, offset ) +#### dmeanwd.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dmeanwd.ndarray( N, x, 1, 0 ); +var v = dmeanwd.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmeanwd.ndarray( N, x, 2, 1 ); +var v = dmeanwd.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -153,18 +144,12 @@ var v = dmeanwd.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanwd = require( '@stdlib/stats/base/dmeanwd' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanwd( x.length, x, 1 ); @@ -175,6 +160,124 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmeanwd.h" +``` + +#### stdlib_strided_dmeanwd( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using Welford's algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanwd( 3, x, 1 ); +// returns ~0.333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmeanwd( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmeanwd_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dmeanwd_ndarray( 3, x, 1, 0 ); +// returns ~0.333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmeanwd_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmeanwd.h" +#include +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the minimum value: + double v = stdlib_strided_dmeanwd( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.js index 9c24bb919d7d..3713d2d922f9 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib/dmeanwd.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanwd = require( './../lib/dmeanwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.native.js index 12e63e1da6cf..6727e8128cbd 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanwd = tryRequire( resolve( __dirname, './../lib/dmeanwd.native.js' ) ); var opts = { 'skip': ( dmeanwd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.js index a5476f221cf8..aa3398ee0787 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmeanwd = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dmeanwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.native.js index 75c64850dfbb..a2219c2eec9e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dmeanwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmeanwd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/c/benchmark.length.c index f3848799a2a0..9821c99240f2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmeanwd( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmeanwd_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/repl.txt index 79d66ef89ee5..64a9280f4586 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -65,10 +62,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/types/index.d.ts index f773dc88e93a..933a231f7b05 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmeanwd.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/c/example.c index c6942fc1f5dc..9a2bb614408e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmeanwd.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dmeanwd( N, x, stride ); + double v = stdlib_strided_dmeanwd( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/index.js index b36874113f2c..78bc5eddc4c9 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dmeanwd = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dmeanwd( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/include.gypi b/lib/node_modules/@stdlib/stats/base/dmeanwd/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. */ -double stdlib_strided_dmeanwd( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmeanwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmeanwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.js index a953ec520358..49696786b228 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -43,43 +49,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanwd( N, x, 1 ); +* var v = dmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanwd( N, x, stride ) { - var mu; - var ix; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - n += 1; - mu += ( x[ix]-mu ) / n; - ix += stride; - } - return mu; +function dmeanwd( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.native.js index eeeac023e640..92829c3d8048 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/dmeanwd.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanwd( N, x, 1 ); +* var v = dmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dmeanwd( N, x, stride ) { - return addon( N, x, stride ); +function dmeanwd( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/index.js index ade1ec81720f..89cb4de7bf50 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/index.js @@ -28,20 +28,17 @@ * var dmeanwd = require( '@stdlib/stats/base/dmeanwd' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dmeanwd( N, x, 1 ); +* var v = dmeanwd( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmeanwd = require( '@stdlib/stats/base/dmeanwd' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanwd.ndarray( N, x, 2, 1 ); +* var v = dmeanwd.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.js index db4a67b67ec0..13f25ea9c2b5 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.js @@ -43,21 +43,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanwd( N, x, 2, 1 ); +* var v = dmeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanwd( N, x, stride, offset ) { +function dmeanwd( N, x, strideX, offsetX ) { var mu; var ix; var n; @@ -66,16 +64,16 @@ function dmeanwd( N, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; mu = 0.0; n = 0; for ( i = 0; i < N; i++ ) { n += 1; mu += ( x[ix]-mu ) / n; - ix += stride; + ix += strideX; } return mu; } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.native.js index 62d4010c78b0..01d8be8a1140 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmeanwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmeanwd.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmeanwd( N, x, 2, 1 ); +* var v = dmeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function dmeanwd( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmeanwd( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dmeanwd/manifest.json index 501d3831449c..99aaf0c4da72 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,73 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmeanwd/src/addon.c new file mode 100644 index 000000000000..01a7e13d9c03 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanwd)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmeanwd_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmeanwd/src/addon.cpp deleted file mode 100644 index 72b1780ed309..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanwd.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmeanwd { - - /** - * Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dmeanwd( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dmeanwd( N, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmeanwd, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmeanwd diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/src/dmeanwd.c b/lib/node_modules/@stdlib/stats/base/dmeanwd/src/dmeanwd.c deleted file mode 100644 index 0f4ed2bafdf7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/src/dmeanwd.c +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmeanwd.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. -* -* ## Method -* -* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows -* -* ```tex -* \begin{align*} -* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ -* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ -* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ -* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) -* \end{align*} -* ``` -* -* ## References -* -* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). -* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmeanwd( const int64_t N, const double *X, const int64_t stride ) { - int64_t ix; - int64_t i; - int64_t n; - double mu; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - n += 1; - mu += ( X[ix]-mu ) / (double)n; - ix += stride; - } - return mu; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/src/main.c b/lib/node_modules/@stdlib/stats/base/dmeanwd/src/main.c new file mode 100644 index 000000000000..64531e3d58e5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/src/main.c @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. +* +* ## Method +* +* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows +* +* ```tex +* \begin{align*} +* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ +* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ +* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ +* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) +* \end{align*} +* ``` +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmeanwd_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmeanwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + CBLAS_INT n; + double mu; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + ix = offsetX; + mu = 0.0; + n = 0; + for ( i = 0; i < N; i++ ) { + n += 1; + mu += ( X[ix]-mu ) / (double)n; + ix += strideX; + } + return mu; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.js index 00a2f320dee4..cea634e3a195 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanwd = require( './../lib/dmeanwd.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, 2 ); + v = dmeanwd( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, -2 ); + v = dmeanwd( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanwd( N, x1, 2 ); + v = dmeanwd( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.native.js index 15365660946a..ae8a6d6b55b8 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.dmeanwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, 2 ); + v = dmeanwd( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, -2 ); + v = dmeanwd( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmeanwd( N, x1, 2 ); + v = dmeanwd( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.js index 6e6afb21d0fb..a210a8b889b2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dmeanwd = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, 2, 0 ); + v = dmeanwd( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, -2, 6 ); + v = dmeanwd( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, 2, 1 ); + v = dmeanwd( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.native.js index 51caa5894140..4a7b88f4a894 100644 --- a/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmeanwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, 2, 0 ); + v = dmeanwd( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, -2, 6 ); + v = dmeanwd( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmeanwd( N, x, 2, 1 ); + v = dmeanwd( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md b/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md index a86ace776024..c2c224047c75 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var dmediansorted = require( '@stdlib/stats/base/dmediansorted' ); ``` -#### dmediansorted( N, x, stride ) +#### dmediansorted( N, x, strideX ) Computes the median value of a sorted double-precision floating-point strided array `x`. @@ -56,18 +56,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: index increment for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the median value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the median value of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dmediansorted( N, x, 2 ); +var v = dmediansorted( 4, x, 2 ); // returns 2.5 ``` @@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmediansorted( N, x1, 2 ); +var v = dmediansorted( 4, x1, 2 ); // returns 2.0 ``` -#### dmediansorted.ndarray( N, x, stride, offset ) +#### dmediansorted.ndarray( N, x, strideX, offsetX ) Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -96,9 +91,8 @@ Computes the median value of a sorted double-precision floating-point strided ar var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = dmediansorted.ndarray( N, x, 1, 0 ); +var v = dmediansorted.ndarray( x.length, x, 1, 0 ); // returns 2.0 ``` @@ -110,12 +104,10 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dmediansorted.ndarray( N, x, 2, 1 ); +var v = dmediansorted.ndarray( 4, x, 2, 1 ); // returns 2.0 ``` @@ -141,16 +133,13 @@ var v = dmediansorted.ndarray( N, x, 2, 1 ); ```javascript -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dmediansorted = require( '@stdlib/stats/base/dmediansorted' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dmediansorted( x.length, x, 1 ); @@ -161,6 +150,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmediansorted.h" +``` + +#### stdlib_strided_dmediansorted( N, \*X, strideX ) + +Computes the median value of a sorted double-precision floating-point strided array. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; + +double v = stdlib_strided_dmediansorted( 3, x, 1 ); +// returns 2.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmediansorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmediansorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; + +double v = stdlib_strided_dmediansorted_ndarray( 3, x, 1, 0 ); +// returns 2.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmediansorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmediansorted.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the median value: + double v = stdlib_strided_dmediansorted( N, x, strideX ); + + // Print the result: + printf( "median: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js index 184b2c1efdef..7693a0f7e852 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmediansorted = require( './../lib/dmediansorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dmediansorted = require( './../lib/dmediansorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js index 4f202cb30343..578bcca1f3e3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dmediansorted = tryRequire( resolve( __dirname, './../lib/dmediansorted.nati var opts = { 'skip': ( dmediansorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js index 97ccf335dda8..e4132087b0be 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dmediansorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dmediansorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js index fe0ffcb7aa53..dd02a5b23a63 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dmediansorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' var opts = { 'skip': ( dmediansorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c index b8e5967e30a8..061ceba5905a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmediansorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmediansorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt index fd26c4058719..6c61cc4090e0 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the median value of a sorted double-precision floating-point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,8 +22,8 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,20 +37,19 @@ > {{alias}}( x.length, x, 1 ) 2.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2 ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2 ) + > {{alias}}( 3, x1, 2 ) 2.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -66,10 +65,10 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts index b05f9ba8b8da..e5711bd766c1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns median value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dmediansorted( x.length, x, 1 ); * // returns 2.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns median value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dmediansorted.ndarray( x.length, x, 1, 0 ); * // returns 2.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns median value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c index 42339fe8638d..feabfd7f96f7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dmediansorted.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the median value: - double v = stdlib_strided_dmediansorted( N, x, stride ); + double v = stdlib_strided_dmediansorted( N, x, strideX ); // Print the result: printf( "median: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js index 405145bb3c3d..3dcbbbecf3ef 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dmediansorted = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dmediansorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi b/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the median value of a sorted double-precision floating-point strided array. */ -double stdlib_strided_dmediansorted( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js index e14e0db0fe2c..b4bfee2cfa35 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js @@ -20,7 +20,8 @@ // MODULES // -var floor = require( '@stdlib/math/base/special/floor' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,7 +31,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} median value * * @example @@ -41,27 +42,8 @@ var floor = require( '@stdlib/math/base/special/floor' ); * var v = dmediansorted( x.length, x, 1 ); * // returns 2.0 */ -function dmediansorted( N, x, stride ) { - var offset; - var n; - var m; - - if ( N <= 0 ) { - return NaN; - } - if ( stride < 0 ) { - offset = (1-N) * stride; - } else { - offset = 0; - } - n = N / 2; - m = floor( n ); - if ( n === m ) { - // Even number of elements... - return ( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0; - } - // Odd number of elements... - return x[ offset+(m*stride) ]; +function dmediansorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js index 70e8bbae3ca2..38fdc86ea147 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js @@ -30,7 +30,7 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} median value * * @example @@ -41,8 +41,8 @@ var addon = require( './../src/addon.node' ); * var v = dmediansorted( x.length, x, 1 ); * // returns 2.0 */ -function dmediansorted( N, x, stride ) { - return addon( N, x, stride ); +function dmediansorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js index 1af139ee2952..b2c68a1171ac 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js @@ -34,13 +34,11 @@ * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmediansorted = require( '@stdlib/stats/base/dmediansorted' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmediansorted.ndarray( N, x, 2, 1 ); +* var v = dmediansorted.ndarray( 4, x, 2, 1 ); * // returns 0.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js index 44227e8ef762..06c316be96aa 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js @@ -30,21 +30,19 @@ var floor = require( '@stdlib/math/base/special/floor' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} median value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmediansorted( N, x, 2, 1 ); +* var v = dmediansorted( 4, x, 2, 1 ); * // returns 0.0 */ -function dmediansorted( N, x, stride, offset ) { +function dmediansorted( N, x, strideX, offsetX ) { var n; var m; @@ -55,10 +53,10 @@ function dmediansorted( N, x, stride, offset ) { m = floor( n ); if ( n === m ) { // Even number of elements... - return ( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0; + return ( x[ offsetX+(m*strideX) ] + x[ offsetX+((m-1)*strideX) ] ) / 2.0; // eslint-disable-line max-len } // Odd number of elements... - return x[ offset+(m*stride) ]; + return x[ offsetX+(m*strideX) ]; } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js index 382a5046d062..4d196eeae4d2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dmediansorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dmediansorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} median value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmediansorted( N, x, 2, 1 ); +* var v = dmediansorted( 4, x, 2, 1 ); * // returns 0.0 */ -function dmediansorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dmediansorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json index 24ca1524a6d3..99aaf0c4da72 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,73 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dmediansorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c new file mode 100644 index 000000000000..8cc443aa4678 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmediansorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmediansorted)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp deleted file mode 100644 index 543b559d8533..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmediansorted.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmediansorted { - - /** - * Computes the median value of a sorted double-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: sorted input array - * - `stride`: stride length - */ - napi_value node_dmediansorted( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dmediansorted( N, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmediansorted, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmediansorted diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c deleted file mode 100644 index ca291663021b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c +++ /dev/null @@ -1,49 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmediansorted.h" -#include - -/** -* Computes the median value of a sorted double-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dmediansorted( const int64_t N, const double *X, const int64_t stride ) { - int64_t offset; - int64_t n; - - if ( N <= 0 ) { - return 0.0/0.0; // NaN - } - if ( stride < 0 ) { - offset = (1-N) * stride; - } else { - offset = 0; - } - n = N >> 1; - if ( N & 1 ) { - // Odd number of elements... - return X[ offset+(n*stride) ]; - } - // Even number of elements... - return ( X[ offset+(n*stride) ] + X[ offset+((n-1)*stride) ] ) / 2.0; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c new file mode 100644 index 000000000000..b19689cc85bf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmediansorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the median value of a sorted double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT n; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + n = N >> 1; + if ( N & 1 ) { + // Odd number of elements... + return X[ offsetX+(n*strideX) ]; + } + // Even number of elements... + return ( X[ offsetX+(n*strideX) ] + X[ offsetX+((n-1)*strideX) ] ) / 2.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js index b50972545782..3a34bce746bd 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, 2 ); + v = dmediansorted( 4, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, -2 ); + v = dmediansorted( 4, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -196,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmediansorted( N, x1, 2 ); + v = dmediansorted( 4, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js index ef6ef5d73c57..a4d235fe97a1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, 2 ); + v = dmediansorted( 4, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, -2 ); + v = dmediansorted( 4, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -205,9 +199,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dmediansorted( N, x1, 2 ); + v = dmediansorted( 4, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js index 4f876c6ee511..63ed480c3d3f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, 2, 0 ); + v = dmediansorted( 4, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, -2, 6 ); + v = dmediansorted( 4, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -178,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -192,9 +186,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, 2, 1 ); + v = dmediansorted( 4, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js index 90c791eaac10..ecd1bc06391d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, 2, 0 ); + v = dmediansorted( 4, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, -2, 6 ); + v = dmediansorted( 4, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -187,7 +182,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -201,9 +195,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dmediansorted( N, x, 2, 1 ); + v = dmediansorted( 4, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmidrange/README.md b/lib/node_modules/@stdlib/stats/base/dmidrange/README.md index 43f5729e3bfc..787aba49e521 100644 --- a/lib/node_modules/@stdlib/stats/base/dmidrange/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmidrange/README.md @@ -256,7 +256,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dmean`][@stdlib/stats/base/dmean]: calculate the arithmetic mean of a double-precision floating-point strided array. - [`@stdlib/stats/base/dmin`][@stdlib/stats/base/dmin]: calculate the minimum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/drange`][@stdlib/stats/base/drange]: calculate the range of a double-precision floating-point strided array. @@ -278,7 +278,7 @@ int main( void ) { -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/dmean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmean diff --git a/lib/node_modules/@stdlib/stats/base/dmidrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmidrange/docs/repl.txt index 0ed0c13e93c2..b32cd6680cb7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmidrange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmidrange/docs/repl.txt @@ -19,7 +19,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -62,7 +62,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dmidrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmidrange/src/addon.c index 583115c7d9df..5889e6a97fb1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmidrange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmidrange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmidrange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmidrange( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmidrange)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmidrange_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmidrange_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dmidrange/src/main.c b/lib/node_modules/@stdlib/stats/base/dmidrange/src/main.c index d6064ec05c45..92d1c047f371 100644 --- a/lib/node_modules/@stdlib/stats/base/dmidrange/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dmidrange/src/main.c @@ -37,7 +37,7 @@ double API_SUFFIX(stdlib_strided_dmidrange)( const CBLAS_INT N, const double *X, } /** -* Computes the mid-range of a double-precision floating-point strided array and using alternative indexing semantics. +* Computes the mid-range of a double-precision floating-point strided array using alternative indexing semantics. * * @param N number of indexed elements * @param X input array diff --git a/lib/node_modules/@stdlib/stats/base/dmin/README.md b/lib/node_modules/@stdlib/stats/base/dmin/README.md index 01eb2ff975ad..b34209ef2d29 100644 --- a/lib/node_modules/@stdlib/stats/base/dmin/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmin/README.md @@ -162,7 +162,7 @@ Computes the minimum value of a double-precision floating-point strided array. ```c const double x[] = { 1.0, -2.0, 2.0 }; -double v = stdlib_strided_dmin( 3, x, 2 ); +double v = stdlib_strided_dmin( 3, x, 1 ); // returns -2.0 ``` @@ -183,7 +183,7 @@ Computes the minimum value of a double-precision floating-point strided array us ```c const double x[] = { 1.0, -2.0, 2.0 }; -double v = stdlib_strided_dmin_ndarray( 3, x, 2, 0 ); +double v = stdlib_strided_dmin_ndarray( 3, x, 1, 0 ); // returns -2.0 ``` @@ -218,7 +218,6 @@ double stdlib_strided_dmin_ndarray( const CBLAS_INT N, const double *X, const CB ```c #include "stdlib/stats/base/dmin.h" -#include #include int main( void ) { @@ -255,7 +254,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dnanmin`][@stdlib/stats/base/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring NaN values. - [`@stdlib/stats/base/min`][@stdlib/stats/base/min]: calculate the minimum value of a strided array. - [`@stdlib/stats/base/smin`][@stdlib/stats/base/smin]: calculate the minimum value of a single-precision floating-point strided array. @@ -274,7 +273,7 @@ int main( void ) { -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/dnanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanmin diff --git a/lib/node_modules/@stdlib/stats/base/dmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmin/docs/repl.txt index b31a18a2d9a8..0ff6f0bdb902 100644 --- a/lib/node_modules/@stdlib/stats/base/dmin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmin/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -65,7 +65,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dmin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmin/examples/c/example.c index 5cdf717f8b80..6a0980c3fa8b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmin/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmin/examples/c/example.c @@ -17,7 +17,6 @@ */ #include "stdlib/stats/base/dmin.h" -#include #include int main( void ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmin/src/addon.c index b0c4bd173d0e..08354486e1eb 100644 --- a/lib/node_modules/@stdlib/stats/base/dmin/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmin/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmin.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmin( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmin)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmin_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmin_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dminabs/docs/repl.txt index f53dba5c58d1..93035c5e6b77 100644 --- a/lib/node_modules/@stdlib/stats/base/dminabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dminabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dminabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dminabs/src/addon.c index 5ae9e5aa316a..ac9a54c8f97f 100644 --- a/lib/node_modules/@stdlib/stats/base/dminabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dminabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dminabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dminabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dminabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dminabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dminabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/README.md b/lib/node_modules/@stdlib/stats/base/dminsorted/README.md index dd2101aa24ec..2d6641d11787 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var dminsorted = require( '@stdlib/stats/base/dminsorted' ); ``` -#### dminsorted( N, x, stride ) +#### dminsorted( N, x, strideX ) Computes the minimum value of a sorted double-precision floating-point strided array `x`. @@ -44,15 +44,13 @@ Computes the minimum value of a sorted double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = dminsorted( N, x, 1 ); +var v = dminsorted( x.length, x, 1 ); // returns 1.0 x = new Float64Array( [ 3.0, 2.0, 1.0 ] ); -N = x.length; -v = dminsorted( N, x, 1 ); +v = dminsorted( x.length, x, 1 ); // returns 1.0 ``` @@ -60,18 +58,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the minimum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum value of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dminsorted( N, x, 2 ); +var v = dminsorted( 4, x, 2 ); // returns 1.0 ``` @@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dminsorted( N, x1, 2 ); +var v = dminsorted( 4, x1, 2 ); // returns 1.0 ``` -#### dminsorted.ndarray( N, x, stride, offset ) +#### dminsorted.ndarray( N, x, strideX, offsetX ) Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -100,26 +93,23 @@ Computes the minimum value of a sorted double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = dminsorted.ndarray( N, x, 1, 0 ); +var v = dminsorted.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dminsorted.ndarray( N, x, 2, 1 ); +var v = dminsorted.ndarray( 4, x, 2, 1 ); // returns 1.0 ``` @@ -145,16 +135,13 @@ var v = dminsorted.ndarray( N, x, 2, 1 ); ```javascript -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dminsorted = require( '@stdlib/stats/base/dminsorted' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dminsorted( x.length, x, 1 ); @@ -165,6 +152,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dminsorted.h" +``` + +#### stdlib_strided_dminsorted( N, \*X, strideX ) + +Computes the minimum value of a sorted double-precision floating-point strided array. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; + +double v = stdlib_strided_dmax( 3, x, 1 ); +// returns 1.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dminsorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dminsorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; + +double v = stdlib_strided_dminsorted_ndarray( 3, x, 1, 0 ); +// returns 1.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dminsorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dminsorted.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the minimum value: + double v = stdlib_strided_dminsorted( N, x, strideX ); + + // Print the result: + printf( "min: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js index aadd35b05c54..e3e721d8f786 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dminsorted = require( './../lib/dminsorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dminsorted = require( './../lib/dminsorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js index 217b78e07218..899273284846 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dminsorted = tryRequire( resolve( __dirname, './../lib/dminsorted.native.js' var opts = { 'skip': ( dminsorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js index 52be5dc90355..5665272757d6 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dminsorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var dminsorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js index 47c7a80f80c3..a01ecfba9c49 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var dminsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dminsorted instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c index 285c5fe8b2b2..11f4b5a044c5 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dminsorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dminsorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt index a8c75a6241ff..dbdd064e0911 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt @@ -1,12 +1,12 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the minimum value of a sorted double-precision floating-point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed + The `N` and stride parameters determine which elements in `x` are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -22,8 +22,8 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,22 +37,19 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) -2.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -2.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float64Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts index 509a175c89aa..dc1fc8470079 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns minimum value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dminsorted( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns minimum value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dminsorted.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns minimum value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c index 2673519870b3..0e5c657e2864 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dminsorted.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the minimum value: - double v = stdlib_strided_dminsorted( N, x, stride ); + double v = stdlib_strided_dminsorted( N, x, strideX ); // Print the result: printf( "min: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js index c4a9be487cce..7acfb4f24877 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float64Array = require( '@stdlib/array/float64' ); +var linspace = require( '@stdlib/array/linspace' ); var dminsorted = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float64' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = dminsorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the minimum value of a sorted double-precision floating-point strided array. */ -double stdlib_strided_dminsorted( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dminsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dminsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js index b3e5d95f53fe..9d4deae34b6c 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,48 +31,19 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} minimum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = dminsorted( N, x, 1 ); +* var v = dminsorted( x.length, x, 1 ); * // returns 1.0 */ -function dminsorted( N, x, stride ) { - var v1; - var v2; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - v1 = x[ (1-N) * stride ]; - v2 = x[ 0 ]; - } else { - v1 = x[ 0 ]; - v2 = x[ (N-1) * stride ]; - } - if ( isnan( v1 ) || isnan( v2 ) ) { - return NaN; - } - if ( v1 === v2 ) { - if ( isNegativeZero( v1 ) || isNegativeZero( v2 ) ) { - return -0.0; - } - return v1; - } - if ( v1 < v2 ) { - return v1; - } - return v2; +function dminsorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js index 058184aa2c07..514252613c15 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} minimum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = dminsorted( N, x, 1 ); +* var v = dminsorted( x.length, x, 1 ); * // returns 1.0 */ -function dminsorted( N, x, stride ) { - return addon( N, x, stride ); +function dminsorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js index 4f5a123bf49e..49d6559c2f25 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js @@ -28,20 +28,17 @@ * var dminsorted = require( '@stdlib/stats/base/dminsorted' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = dminsorted( N, x, 1 ); +* var v = dminsorted( x.length, x, 1 ); * // returns 1.0 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dminsorted = require( '@stdlib/stats/base/dminsorted' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dminsorted.ndarray( N, x, 2, 1 ); +* var v = dminsorted.ndarray( 4, x, 2, 1 ); * // returns -3.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js index 65427fab99ea..7f6d85781721 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js @@ -31,32 +31,30 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} minimum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dminsorted( N, x, 2, 1 ); +* var v = dminsorted( 4, x, 2, 1 ); * // returns -3.0 */ -function dminsorted( N, x, stride, offset ) { +function dminsorted( N, x, strideX, offsetX ) { var v1; var v2; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return x[ 0 ]; } - v1 = x[ offset ]; - v2 = x[ offset + ((N-1)*stride) ]; + v1 = x[ offsetX ]; + v2 = x[ offsetX + ((N-1)*strideX) ]; if ( isnan( v1 ) || isnan( v2 ) ) { return NaN; } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js index 2503636150dc..2e898ee3cdbe 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dminsorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dminsorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} minimum value * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dminsorted( N, x, 2, 1 ); +* var v = dminsorted( 4, x, 2, 1 ); * // returns -3.0 */ -function dminsorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dminsorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json index 4e090b2f2400..badf40fc022a 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,19 +27,80 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dminsorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c new file mode 100644 index 000000000000..27a7016e84b5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dminsorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dminsorted)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dminsorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp deleted file mode 100644 index 756f45cb695e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dminsorted.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dminsorted { - - /** - * Computes the minimum value of a sorted double-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: sorted input array - * - `stride`: stride length - */ - napi_value node_dminsorted( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dminsorted( N, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dminsorted, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dminsorted diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/dminsorted.c b/lib/node_modules/@stdlib/stats/base/dminsorted/src/dminsorted.c deleted file mode 100644 index 36161f0d450c..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/src/dminsorted.c +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dminsorted.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_negative_zero.h" -#include - -/** -* Computes the minimum value of a sorted double-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dminsorted( const int64_t N, const double *X, const int64_t stride ) { - double v1; - double v2; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - v1 = X[ (1-N) * stride ]; - v2 = X[ 0 ]; - } else { - v1 = X[ 0 ]; - v2 = X[ (N-1) * stride ]; - } - if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) { - return 0.0 / 0.0; // NaN - } - if ( v1 == v2 ) { - if ( stdlib_base_is_negative_zero( v1 ) || stdlib_base_is_negative_zero( v2 ) ) { - return -0.0; - } - return v1; - } - if ( v1 < v2 ) { - return v1; - } - return v2; -} diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dminsorted/src/main.c new file mode 100644 index 000000000000..08a046f60271 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/src/main.c @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dminsorted.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_negative_zero.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the minimum value of a sorted double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dminsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dminsorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dminsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + double v1; + double v2; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + v1 = X[ offsetX ]; + v2 = X[ ( (N-1)*strideX ) + offsetX ]; + if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) { + return 0.0 / 0.0; // NaN + } + if ( v1 == v2 ) { + if ( stdlib_base_is_negative_zero( v1 ) || stdlib_base_is_negative_zero( v2 ) ) { + return -0.0; + } + return v1; + } + if ( v1 < v2 ) { + return v1; + } + return v2; +} diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js index 3eda0ff9c531..1232989ca5d3 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, 2 ); + v = dminsorted( 3, x, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, -2 ); + v = dminsorted( 4, x, -2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dminsorted( N, x1, 2 ); + v = dminsorted( 4, x1, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js index 9388005816c1..022906bbf870 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, 2 ); + v = dminsorted( 4, x, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, -2 ); + v = dminsorted( 4, x, -2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dminsorted( N, x1, 2 ); + v = dminsorted( 4, x1, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js index ea49cf494c20..7d289d3f98a5 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, 2, 0 ); + v = dminsorted( 4, x, 2, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, -2, 6 ); + v = dminsorted( 4, x, -2, 6 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, 2, 1 ); + v = dminsorted( 4, x, 2, 1 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js index 5dc9eb0b6d7c..01bfaffeaa52 100644 --- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, 2, 0 ); + v = dminsorted( 4, x, 2, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, -2, 6 ); + v = dminsorted( 4, x, -2, 6 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dminsorted( N, x, 2, 1 ); + v = dminsorted( 4, x, 2, 1 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/README.md b/lib/node_modules/@stdlib/stats/base/dmskmax/README.md index c9adb5ed4497..fe7854e8ce8e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/README.md @@ -38,7 +38,7 @@ var dmskmax = require( '@stdlib/stats/base/dmskmax' ); #### dmskmax( N, x, strideX, mask, strideMask ) -Computes the maximum value of a double-precision floating-point strided array `x` according to a `mask`. +Computes the maximum value of a double-precision floating-point strided array according to a mask. ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -55,22 +55,20 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation. -- **strideMask**: index increment for `mask`. +- **strideMask**: stride length for `mask`. -The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the maximum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = dmskmax( N, x, 2, mask, 2 ); +var v = dmskmax( 4, x, 2, mask, 2 ); // returns 4.0 ``` @@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element @@ -89,15 +86,13 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmskmax( N, x1, 2, mask1, 2 ); +var v = dmskmax( 4, x1, 2, mask1, 2 ); // returns 4.0 ``` #### dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) -Computes the maximum value of a double-precision floating-point strided array according to a `mask` and using alternative indexing semantics. +Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -115,18 +110,16 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetMask**: starting index for `mask`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the maximum value for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 ); +var v = dmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 ); // returns 4.0 ``` @@ -151,26 +144,19 @@ var v = dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var dmskmax = require( '@stdlib/stats/base/dmskmax' ); -var mask; -var x; -var i; - -x = new Float64Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); @@ -182,6 +168,125 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmskmax.h" +``` + +#### stdlib_strided_dmskmax( N, \*X, strideX, \*Mask, strideMask ) + +Computes the maximum value of a double-precision floating-point strided array according to a mask. + +```c +#include + +const double x[] = { 1.0, -2.0, 2.0 }; +const uint8_t mask[] = { 0, 1, 0 }; + +double v = stdlib_strided_dmskmax( 3, x, 1, mask, 1 ); +// returns 2.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. + +```c +double stdlib_strided_dmskmax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); +``` + + + +#### stdlib_strided_dmskmax_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask ) + +Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. + +```c +#include + +const double x[] = { 1.0, -2.0, 2.0 }; +const uint8_t mask[] = { 0, 1, 0 }; + +double v = stdlib_strided_dmskmax_ndarray( 3, x, 1, 0, mask, 1, 0 ); +// returns 2.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. +- **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`. + +```c +double stdlib_strided_dmskmax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmskmax.h" +#include +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + + // Create a mask array: + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride lengths: + const int strideX = 2; + const int strideMask = 2; + + // Compute the maximum value: + double v = stdlib_strided_dmskmax( N, x, strideX, mask, strideMask ); + + // Print the result: + printf( "max: %lf\n", v ); +} +``` + +
+ + + +
+ + +
@@ -190,7 +295,7 @@ console.log( v ); ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dmskmin`][@stdlib/stats/base/dmskmin]: calculate the minimum value of a double-precision floating-point strided array according to a mask. - [`@stdlib/stats/base/dnanmax`][@stdlib/stats/base/dnanmax]: calculate the maximum value of a double-precision floating-point strided array, ignoring NaN values. - [`@stdlib/stats/base/dnanmskmax`][@stdlib/stats/base/dnanmskmax]: calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring NaN values. @@ -213,7 +318,7 @@ console.log( v ); -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/dmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmskmin diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js index 017bba33ab46..b3b88720cac8 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var dmskmax = require( './../lib/dmskmax.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var dmskmax = require( './../lib/dmskmax.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js index f7d94111729f..f0bc0231eee6 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var dmskmax = tryRequire( resolve( __dirname, './../lib/dmskmax.native.js' ) ); var opts = { 'skip': ( dmskmax instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js index 6316a49b6db5..33ecb4344641 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var dmskmax = require( './../lib/ndarray.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var dmskmax = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js index 56e85488a506..bd313639b6bb 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var dmskmax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmskmax instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c index ce221703a44d..5a75cd73545b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { unsigned char mask[ len ]; double elapsed; double x[ len ]; @@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmskmax( len, x, 1, mask, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + unsigned char mask[ len ]; + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + mask[ i ] = 1; // missing + } else { + mask[ i ] = 0; + } + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmskmax_ndarray( len, x, 1, 0, mask, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -148,7 +189,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt index 88c817fd423e..338d5c73657c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt @@ -3,8 +3,8 @@ Computes the maximum value of a double-precision floating-point strided array according to a mask. - The `N` and `stride` parameters determine which elements are accessed at - runtime. + The `N` and stride parameters determine which elements in the strided + arrays are accessed at runtime. Indexing is relative to the first index. To introduce offsets, use a typed array views. @@ -26,13 +26,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. mask: Uint8Array Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. Returns ------- @@ -50,8 +50,7 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, mask, 2 ) + > {{alias}}( 3, x, 2, mask, 2 ) 2.0 // Using view offsets: @@ -59,10 +58,10 @@ > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, mask1, 2 ) + > {{alias}}( 3, x1, 2, mask1, 2 ) 2.0 + {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. @@ -80,7 +79,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -89,7 +88,7 @@ Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. offsetMask: integer Starting index for `mask`. @@ -110,8 +109,7 @@ // Using offset parameter: > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 ) 2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c index dc059d8a4d77..ba6fb4c28a3d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c @@ -22,17 +22,17 @@ int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; // Create a mask array: - uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; // Specify the number of elements: - int64_t N = 5; + const int N = 5; // Specify the stride lengths: - int64_t strideX = 2; - int64_t strideMask = 2; + const int strideX = 2; + const int strideMask = 2; // Compute the maximum value: double v = stdlib_strided_dmskmax( N, x, strideX, mask, strideMask ); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js index 5bf314a934d6..f6bb694a5032 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js @@ -18,26 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var dmskmax = require( './../lib' ); -var mask; -var x; -var i; +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; -x = new Float64Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi b/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' /* @@ -31,7 +32,12 @@ extern "C" { /** * Computes the maximum value of a double-precision floating-point strided array according to a mask. */ -double stdlib_strided_dmskmax( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ); +double API_SUFFIX(stdlib_strided_dmskmax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); + +/** +* Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmskmax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js index bdb0e82c57b4..bf50963f901c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -47,55 +47,9 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); * // returns 2.0 */ function dmskmax( N, x, strideX, mask, strideMask ) { - var max; - var ix; - var im; - var v; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( mask[ im ] === 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i === N ) { - return NaN; - } - max = x[ ix ]; - if ( isnan( max ) ) { - return max; - } - i += 1; - for ( i; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( mask[ im ] ) { - continue; - } - v = x[ ix ]; - if ( isnan( v ) ) { - return v; - } - if ( v > max || ( v === max && isPositiveZero( v ) ) ) { - max = v; - } - } - return max; + var ox = stride2offset( N, strideX ); + var om = stride2offset( N, strideMask ); + return ndarray( N, x, strideX, ox, mask, strideMask, om ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js index e6745a966dd8..d6901bc4dd38 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js @@ -37,14 +37,12 @@ * @example * var Float64Array = require( '@stdlib/array/float64' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmskmax = require( '@stdlib/stats/base/dmskmax' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 ); +* var v = dmskmax.ndarray( 5, x, 2, 1, mask, 2, 1 ); * // returns 4.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js index c5217a702896..59d7252f3db1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js @@ -41,13 +41,11 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); * @example * var Float64Array = require( '@stdlib/array/float64' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmskmax( N, x, 2, 1, mask, 2, 1 ); +* var v = dmskmax( 5, x, 2, 1, mask, 2, 1 ); * // returns 4.0 */ function dmskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js index 07cf4389d730..7d498b936dad 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); -var addon = require( './dmskmax.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -52,17 +50,7 @@ var addon = require( './dmskmax.native.js' ); * // returns 4.0 */ function dmskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { - var viewX; - var viewM; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideMask < 0 ) { - offsetMask += (N-1) * strideMask; - } - viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len - return addon( N, viewX, strideX, viewM, strideMask ); + return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json b/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json index 02276c182f12..b2a745931681 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,79 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dmskmax.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-positive-zero", + "@stdlib/math/base/assert/is-nan", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/argv-strided-uint8array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-positive-zero" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-positive-zero" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-positive-zero" ] diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c new file mode 100644 index 000000000000..f5baff502e37 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmskmax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/argv_strided_uint8array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmskmax)( N, X, strideX, Mask, strideMask ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmskmax_ndarray)( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp deleted file mode 100644 index 19c5d537daf3..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp +++ /dev/null @@ -1,153 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmskmax.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmskmax { - - /** - * Computes the maximum value of a double-precision floating-point strided array according to a mask. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Mask`: mask array - * - `strideMask`: `Mask` stride length - */ - napi_value node_dmskmax( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideMask; - status = napi_get_value_int64( env, argv[ 4 ], &strideMask ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t mlen; - void *Mask; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_uint8_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dmskmax( N, (double *)X, strideX, (uint8_t *)Mask, strideMask ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmskmax, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmskmax diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/dmskmax.c b/lib/node_modules/@stdlib/stats/base/dmskmax/src/dmskmax.c deleted file mode 100644 index d3848b86b995..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/src/dmskmax.c +++ /dev/null @@ -1,84 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmskmax.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_positive_zero.h" -#include - -/** -* Computes the maximum value of a double-precision floating-point strided array according to a mask. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Mask mask array -* @param strideMask Mask stride length -* @return output value -*/ -double stdlib_strided_dmskmax( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) { - double max; - int64_t ix; - int64_t im; - int64_t i; - double v; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( Mask[ im ] == 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i == N ) { - return 0.0 / 0.0; // NaN - } - max = X[ ix ]; - if ( stdlib_base_is_nan( max ) ) { - return 0.0 / 0.0; // NaN - } - i += 1; - for (; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( Mask[ im ] ) { - continue; - } - v = X[ ix ]; - if ( stdlib_base_is_nan( v ) ) { - return 0.0 / 0.0; // NaN - } - if ( v > max || ( v == max && stdlib_base_is_positive_zero( v ) ) ) { - max = v; - } - } - return max; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/main.c b/lib/node_modules/@stdlib/stats/base/dmskmax/src/main.c new file mode 100644 index 000000000000..63f2bfc3297f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmskmax.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_positive_zero.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include + +/** +* Computes the maximum value of a double-precision floating-point strided array according to a mask. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Mask mask array +* @param strideMask Mask stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmskmax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask ); + return API_SUFFIX(stdlib_strided_dmskmax_ndarray)( N, X, strideX, ox, Mask, strideMask, om ); +} + +/** +* Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Mask mask array +* @param strideMask Mask stride length +* @param offsetMask starting index for Mask +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmskmax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) { + CBLAS_INT ix; + CBLAS_INT im; + CBLAS_INT i; + double max; + double v; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + ix = offsetX; + im = offsetMask; + for ( i = 0; i < N; i++ ) { + if ( Mask[ im ] == 0 ) { + break; + } + ix += strideX; + im += strideMask; + } + if ( i == N ) { + return 0.0 / 0.0; // NaN + } + max = X[ ix ]; + if ( stdlib_base_is_nan( max ) ) { + return 0.0 / 0.0; // NaN + } + i += 1; + for (; i < N; i++ ) { + ix += strideX; + im += strideMask; + if ( Mask[ im ] ) { + continue; + } + v = X[ ix ]; + if ( stdlib_base_is_nan( v ) ) { + return 0.0 / 0.0; // NaN + } + if ( v > max || ( v == max && stdlib_base_is_positive_zero( v ) ) ) { + max = v; + } + } + return max; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js index c3c6c35d213e..9b89cea89358 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, 2, mask, 2 ); + v = dmskmax( 5, x, 2, mask, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, -2, mask, -2 ); + v = dmskmax( 5, x, -2, mask, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = dmskmax( N, x1, 2, mask1, 2 ); + v = dmskmax( 5, x1, 2, mask1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js index 8630ceda8a96..583a745ead4f 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, 2, mask, 2 ); + v = dmskmax( 5, x, 2, mask, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, -2, mask, -2 ); + v = dmskmax( 5, x, -2, mask, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = dmskmax( N, x1, 2, mask1, 2 ); + v = dmskmax( 5, x1, 2, mask1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js index abd8a7319f58..57945b91c24a 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, 2, 0, mask, 2, 0 ); + v = dmskmax( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, -2, 8, mask, -2, 8 ); + v = dmskmax( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { tape( 'the function supports `offset` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, 2, 1, mask, 2, 1 ); + v = dmskmax( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js index ed6c5d1b9010..aaa0cc9723ae 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu v = dmskmax( 0, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dmskmax( -1, x, 1, 0, mask, 1 ); + v = dmskmax( -1, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, 2, 0, mask, 2, 0 ); + v = dmskmax( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, -2, 8, mask, -2, 8 ); + v = dmskmax( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test( tape( 'the function supports `offset` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = dmskmax( N, x, 2, 1, mask, 2, 1 ); + v = dmskmax( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/README.md b/lib/node_modules/@stdlib/stats/base/dmskmin/README.md index 7f15599fe02c..7886fb7cb0e3 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/README.md +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/README.md @@ -38,7 +38,7 @@ var dmskmin = require( '@stdlib/stats/base/dmskmin' ); #### dmskmin( N, x, strideX, mask, strideMask ) -Computes the minimum value of a double-precision floating-point strided array `x` according to a `mask`. +Computes the minimum value of a double-precision floating-point strided array according to a mask. ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -55,22 +55,20 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation. -- **strideMask**: index increment for `mask`. +- **strideMask**: stride length for `mask`. -The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the minimum value of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 7.0, -2.0, -4.0, 3.0, -5.0, -6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = dmskmin( N, x, 2, mask, 2 ); +var v = dmskmin( 4, x, 2, mask, 2 ); // returns -4.0 ``` @@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element @@ -89,15 +86,13 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dmskmin( N, x1, 2, mask1, 2 ); +var v = dmskmin( 4, x1, 2, mask1, 2 ); // returns -2.0 ``` #### dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) -Computes the minimum value of a double-precision floating-point strided array according to a `mask` and using alternative indexing semantics. +Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. ```javascript var Float64Array = require( '@stdlib/array/float64' ); @@ -115,18 +110,16 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetMask**: starting index for `mask`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the minimum value for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 ); +var v = dmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 ); // returns -2.0 ``` @@ -151,26 +144,19 @@ var v = dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var dmskmin = require( '@stdlib/stats/base/dmskmin' ); -var mask; -var x; -var i; - -x = new Float64Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); @@ -182,6 +168,125 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dmskmin.h" +``` + +#### stdlib_strided_dmskmin( N, \*X, strideX, \*Mask, strideMask ) + +Computes the minimum value of a double-precision floating-point strided array according to a mask. + +```c +#include + +const double x[] = { 1.0, -2.0, 2.0 }; +const uint8_t mask[] = { 0, 1, 0 }; + +double v = stdlib_strided_dmskmin( 3, x, 1, mask, 1 ); +// returns 1.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. + +```c +double stdlib_strided_dmskmin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); +``` + + + +#### stdlib_strided_dmskmin_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask ) + +Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. + +```c +#include + +const double x[] = { 1.0, -2.0, 2.0 }; +const uint8_t mask[] = { 0, 1, 0 }; + +double v = stdlib_strided_dmskmin( 3, x, 1, 0, mask, 1, 0 ); +// returns 1.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. +- **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`. + +```c +double stdlib_strided_dmskmin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dmskmin.h" +#include +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + + // Create a mask array: + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride lengths: + const int strideX = 2; + const int strideMask = 2; + + // Compute the minimum value: + double v = stdlib_strided_dmskmin( N, x, strideX, mask, strideMask ); + + // Print the result: + printf( "min: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js index 50b44e6d5266..3dd78bbe6c98 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var dmskmin = require( './../lib/dmskmin.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var dmskmin = require( './../lib/dmskmin.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js index b757c6df95d4..b5774740b75e 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var dmskmin = tryRequire( resolve( __dirname, './../lib/dmskmin.native.js' ) ); var opts = { 'skip': ( dmskmin instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js index 902a67af63eb..da95dc91adf4 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var dmskmin = require( './../lib/ndarray.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var dmskmin = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js index 6d8897c6dd31..6e7b504fd865 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var dmskmin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dmskmin instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float64Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c index 81bbf03e14a5..eb44fa95f589 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { unsigned char mask[ len ]; double elapsed; double x[ len ]; @@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dmskmin( len, x, 1, mask, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + unsigned char mask[ len ]; + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + mask[ i ] = 1; // missing + } else { + mask[ i ] = 0; + } + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmskmin_ndarray( len, x, 1, 0, mask, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -148,7 +189,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt index 8205792a6759..f55894ee9e97 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt @@ -3,8 +3,8 @@ Computes the minimum value of a double-precision floating-point strided array according to a mask. - The `N` and `stride` parameters determine which elements are accessed at - runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce offsets, use a typed array views. @@ -26,13 +26,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. mask: Uint8Array Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. Returns ------- @@ -47,11 +47,10 @@ > {{alias}}( x.length, x, 1, mask, 1 ) -2.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, mask, 2 ) + > {{alias}}( 3, x, 2, mask, 2 ) -2.0 // Using view offsets: @@ -59,10 +58,10 @@ > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, mask1, 2 ) + > {{alias}}( 3, x1, 2, mask1, 2 ) -2.0 + {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. @@ -80,7 +79,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -89,7 +88,7 @@ Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. offsetMask: integer Starting index for `mask`. @@ -110,8 +109,7 @@ // Using offset parameter: > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 ) -2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c index 5d83cdd2c079..9fa5cafa30f6 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c @@ -22,17 +22,17 @@ int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; // Create a mask array: - uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; // Specify the number of elements: - int64_t N = 5; + const int N = 5; // Specify the stride lengths: - int64_t strideX = 2; - int64_t strideMask = 2; + const int strideX = 2; + const int strideMask = 2; // Compute the minimum value: double v = stdlib_strided_dmskmin( N, x, strideX, mask, strideMask ); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js index ccdc244a1c2b..cd17ef2d8fd1 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js @@ -18,26 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var dmskmin = require( './../lib' ); -var mask; -var x; -var i; +var uniformOptions = { + 'dtype': 'float64' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; -x = new Float64Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi b/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' /* @@ -31,7 +32,12 @@ extern "C" { /** * Computes the minimum value of a double-precision floating-point strided array according to a mask. */ -double stdlib_strided_dmskmin( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ); +double API_SUFFIX(stdlib_strided_dmskmin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); + +/** +* Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dmskmin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js index 86d2e78c4626..c3d59d082840 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js @@ -20,8 +20,8 @@ // MODULES // -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -47,55 +47,9 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); * // returns -2.0 */ function dmskmin( N, x, strideX, mask, strideMask ) { - var min; - var ix; - var im; - var v; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( mask[ im ] === 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i === N ) { - return NaN; - } - min = x[ ix ]; - if ( isnan( min ) ) { - return min; - } - i += 1; - for ( i; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( mask[ im ] ) { - continue; - } - v = x[ ix ]; - if ( isnan( v ) ) { - return v; - } - if ( v < min || ( v === min && isNegativeZero( v ) ) ) { - min = v; - } - } - return min; + var ox = stride2offset( N, strideX ); + var om = stride2offset( N, strideMask ); + return ndarray( N, x, strideX, ox, mask, strideMask, om ); } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js index 12a4a30d4a40..8bfd1833449b 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js @@ -37,14 +37,12 @@ * @example * var Float64Array = require( '@stdlib/array/float64' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dmskmin = require( '@stdlib/stats/base/dmskmin' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 ); +* var v = dmskmin.ndarray( 5, x, 2, 1, mask, 2, 1 ); * // returns -2.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js index 6bcbe3bbe996..20258d249ac7 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js @@ -45,9 +45,8 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmskmin( N, x, 2, 1, mask, 2, 1 ); +* var v = dmskmin( 5, x, 2, 1, mask, 2, 1 ); * // returns -2.0 */ function dmskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js index 3a19aef5489e..46405c90df59 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var Uint8Array = require( '@stdlib/array/uint8' ); -var addon = require( './dmskmin.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -42,27 +40,15 @@ var addon = require( './dmskmin.native.js' ); * @example * var Float64Array = require( '@stdlib/array/float64' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = dmskmin( N, x, 2, 1, mask, 2, 1 ); +* var v = dmskmin( 5, x, 2, 1, mask, 2, 1 ); * // returns -2.0 */ function dmskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { - var viewX; - var viewM; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideMask < 0 ) { - offsetMask += (N-1) * strideMask; - } - viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len - return addon( N, viewX, strideX, viewM, strideMask ); + return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json b/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json index 6481051a91a9..3f0b4cbbc446 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,79 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dmskmin.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/math/base/assert/is-nan", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/argv-strided-uint8array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-negative-zero" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/assert/is-negative-zero" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-negative-zero" ] diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c new file mode 100644 index 000000000000..db97644fc91d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmskmin.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/argv_strided_uint8array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmskmin)( N, X, strideX, Mask, strideMask ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmskmin_ndarray)( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp deleted file mode 100644 index 86acb4265ca2..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp +++ /dev/null @@ -1,153 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmskmin.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dmskmin { - - /** - * Computes the minimum value of a double-precision floating-point strided array according to a mask. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Mask`: mask array - * - `strideMask`: `Mask` stride length - */ - napi_value node_dmskmin( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideMask; - status = napi_get_value_int64( env, argv[ 4 ], &strideMask ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t mlen; - void *Mask; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_uint8_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dmskmin( N, (double *)X, strideX, (uint8_t *)Mask, strideMask ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmskmin, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dmskmin diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/dmskmin.c b/lib/node_modules/@stdlib/stats/base/dmskmin/src/dmskmin.c deleted file mode 100644 index dab8ccf3c9eb..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/src/dmskmin.c +++ /dev/null @@ -1,84 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dmskmin.h" -#include "stdlib/math/base/assert/is_nan.h" -#include "stdlib/math/base/assert/is_negative_zero.h" -#include - -/** -* Computes the minimum value of a double-precision floating-point strided array according to a mask. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Mask mask array -* @param strideMask Mask stride length -* @return output value -*/ -double stdlib_strided_dmskmin( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) { - double min; - int64_t ix; - int64_t im; - int64_t i; - double v; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( Mask[ im ] == 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i == N ) { - return 0.0 / 0.0; // NaN - } - min = X[ ix ]; - if ( stdlib_base_is_nan( min ) ) { - return 0.0 / 0.0; // NaN - } - i += 1; - for (; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( Mask[ im ] ) { - continue; - } - v = X[ ix ]; - if ( stdlib_base_is_nan( v ) ) { - return 0.0 / 0.0; // NaN - } - if ( v < min || ( v == min && stdlib_base_is_negative_zero( v ) ) ) { - min = v; - } - } - return min; -} diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/main.c b/lib/node_modules/@stdlib/stats/base/dmskmin/src/main.c new file mode 100644 index 000000000000..5d1dd57d6b8d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dmskmin.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_negative_zero.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include + +/** +* Computes the minimum value of a double-precision floating-point strided array according to a mask. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Mask mask array +* @param strideMask Mask stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmskmin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask ); + return API_SUFFIX(stdlib_strided_dmskmin_ndarray)( N, X, strideX, ox, Mask, strideMask, om ); +} + +/** +* Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Mask mask array +* @param strideMask Mask stride length +* @param offsetMask starting index for Mask +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmskmin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) { + CBLAS_INT ix; + CBLAS_INT im; + CBLAS_INT i; + double min; + double v; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + ix = offsetX; + im = offsetMask; + for ( i = 0; i < N; i++ ) { + if ( Mask[ im ] == 0 ) { + break; + } + ix += strideX; + im += strideMask; + } + if ( i == N ) { + return 0.0 / 0.0; // NaN + } + min = X[ ix ]; + if ( stdlib_base_is_nan( min ) ) { + return 0.0 / 0.0; // NaN + } + i += 1; + for (; i < N; i++ ) { + ix += strideX; + im += strideMask; + if ( Mask[ im ] ) { + continue; + } + v = X[ ix ]; + if ( stdlib_base_is_nan( v ) ) { + return 0.0 / 0.0; // NaN + } + if ( v < min || ( v == min && stdlib_base_is_negative_zero( v ) ) ) { + min = v; + } + } + return min; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js index 0ef22637413f..5fbaf3ed47b2 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, 2, mask, 2 ); + v = dmskmin( 5, x, 2, mask, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, -2, mask, -2 ); + v = dmskmin( 5, x, -2, mask, -2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = dmskmin( N, x1, 2, mask1, 2 ); + v = dmskmin( 5, x1, 2, mask1, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js index dfb405f17387..a31ba1a8d3b8 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, 2, mask, 2 ); + v = dmskmin( 5, x, 2, mask, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, -2, mask, -2 ); + v = dmskmin( 5, x, -2, mask, -2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = dmskmin( N, x1, 2, mask1, 2 ); + v = dmskmin( 5, x1, 2, mask1, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js index 2756d56e6da2..cb0c228316bf 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, 2, 0, mask, 2, 0 ); + v = dmskmin( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, -2, 8, mask, -2, 8 ); + v = dmskmin( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { tape( 'the function supports `offset` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, 2, 1, mask, 2, 1 ); + v = dmskmin( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js index 2c8edd097d19..ab53ffece127 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu v = dmskmin( 0, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dmskmin( -1, x, 1, 0, mask, 1 ); + v = dmskmin( -1, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, 2, 0, mask, 2, 0 ); + v = dmskmin( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, -2, 8, mask, -2, 8 ); + v = dmskmin( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test( tape( 'the function supports `offset` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = dmskmin( N, x, 2, 1, mask, 2, 1 ); + v = dmskmin( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dmskrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmskrange/docs/repl.txt index 113310bd5c94..ec5040421e5d 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskrange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dmskrange/docs/repl.txt @@ -26,13 +26,13 @@ Input array. strideX: integer - Stride Length for `x`. + Stride length for `x`. mask: Uint8Array Mask array. strideMask: integer - Stride Length for `mask`. + Stride length for `mask`. Returns ------- @@ -79,7 +79,7 @@ Input array. strideX: integer - Stride Length for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -88,7 +88,7 @@ Mask array. strideMask: integer - Stride Length for `mask`. + Stride length for `mask`. offsetMask: integer Starting index for `mask`. diff --git a/lib/node_modules/@stdlib/stats/base/dmskrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmskrange/src/addon.c index 98e63671555e..80541b7b2e4c 100644 --- a/lib/node_modules/@stdlib/stats/base/dmskrange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dmskrange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dmskrange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -39,7 +40,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmskrange( N, X, strideX, Mask, strideMask ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmskrange)( N, X, strideX, Mask, strideMask ), v ); return v; } @@ -59,7 +60,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmskrange_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmskrange_ndarray)( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmax/README.md b/lib/node_modules/@stdlib/stats/base/dnanmax/README.md index cc415efacf2a..46f960770949 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmax/README.md +++ b/lib/node_modules/@stdlib/stats/base/dnanmax/README.md @@ -129,22 +129,19 @@ var v = dnanmax.ndarray( 4, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var dnanmax = require( '@stdlib/stats/base/dnanmax' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = dnanmax( x.length, x, 1 ); @@ -265,7 +262,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dnanmin`][@stdlib/stats/base/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring NaN values. - [`@stdlib/stats/base/nanmax`][@stdlib/stats/base/nanmax]: calculate the maximum value of a strided array, ignoring NaN values. - [`@stdlib/stats/base/snanmax`][@stdlib/stats/base/snanmax]: calculate the maximum value of a single-precision floating-point strided array, ignoring NaN values. @@ -284,7 +281,7 @@ int main( void ) { -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/dnanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanmin diff --git a/lib/node_modules/@stdlib/stats/base/dnanmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanmax/docs/repl.txt index 289112fcb73b..8e88e67e8862 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanmax/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dnanmax/examples/index.js b/lib/node_modules/@stdlib/stats/base/dnanmax/examples/index.js index b851d6b67aab..bbc19d234717 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmax/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmax/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var dnanmax = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = dnanmax( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanmax/src/addon.c index a137a99a29f0..4101477b872a 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmax/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmax/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dnanmax.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmax( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmax)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmax_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmax_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanmaxabs/docs/repl.txt index 46ca21ade5a4..4d06d2be5bef 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmaxabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanmaxabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -64,7 +64,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dnanmaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanmaxabs/src/addon.c index 3e1823e87f77..27e5ac7f55f5 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmaxabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmaxabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dnanmaxabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmaxabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmaxabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmaxabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmaxabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/README.md b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/README.md index 64b1e5cc791c..f4b35440d552 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/README.md +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dnanmeanpw = require( '@stdlib/stats/base/dnanmeanpw' ); ``` -#### dnanmeanpw( N, x, stride ) +#### dnanmeanpw( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x`, ignoring `NaN` values and using pairwise summation. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -var N = x.length; -var v = dnanmeanpw( N, x, 1 ); +var v = dnanmeanpw( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,39 +68,34 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element: ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] ); -var N = floor( x.length / 2 ); -var v = dnanmeanpw( N, x, 2 ); +var v = dnanmeanpw( 5, x, 2 ); // returns 1.25 ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - + ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dnanmeanpw( N, x1, 2 ); +var v = dnanmeanpw( 5, x1, 2 ); // returns 1.25 ``` -#### dnanmeanpw.ndarray( N, x, stride, offset ) +#### dnanmeanpw.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. @@ -109,26 +103,25 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -var N = x.length; -var v = dnanmeanpw.ndarray( N, x, 1, 0 ); +var v = dnanmeanpw.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element starting from the second element: + + ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -var N = floor( x.length / 2 ); +var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); -var v = dnanmeanpw.ndarray( N, x, 2, 1 ); +var v = dnanmeanpw.ndarray( 5, x, 2, 1 ); // returns 1.25 ``` @@ -155,22 +148,19 @@ var v = dnanmeanpw.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var dnanmeanpw = require( '@stdlib/stats/base/dnanmeanpw' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = dnanmeanpw( x.length, x, 1 ); @@ -181,6 +171,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dnanmeanpw.h" +``` + +#### stdlib_strided_dnanmeanpw( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. + +```c +const double x[] = { 1.0, -2.0, 0.0/0.0, 2.0 }; + +double v = stdlib_strided_dnanmeanpw( 4, x, 1 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +double stdlib_strided_dnanmeanpw( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dnanmeanpw_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 0.0/0.0, 2.0 }; + +double v = stdlib_strided_dnanmeanpw_ndarray( 4, x, 1, 0 ); +// returns ~0.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +double stdlib_strided_dnanmeanpw_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dnanmeanpw.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + + // Specify the number of elements: + const int N = 6; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dnanmeanpw( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.js index bae6b7038a84..a91ac201e6e9 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.js @@ -21,16 +21,30 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var pkg = require( './../package.json' ).name; var dnanmeanpw = require( './../lib/dnanmeanpw.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -39,17 +53,7 @@ var dnanmeanpw = require( './../lib/dnanmeanpw.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.native.js index e0e8d2cf706e..7ca7567fdcfb 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.native.js @@ -22,10 +22,11 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,6 +41,19 @@ var opts = { // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -48,17 +62,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.js index 7104cfe4056b..a684a244af05 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.js @@ -21,16 +21,30 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var pkg = require( './../package.json' ).name; var dnanmeanpw = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -39,17 +53,7 @@ var dnanmeanpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.native.js index 36385906f0f7..4d0bdc919f51 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,11 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,6 +41,19 @@ var opts = { // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -48,17 +62,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/c/benchmark.length.c index 863be218f0d3..aad8317a1bee 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -102,11 +102,16 @@ static double benchmark( int iterations, int len ) { int i; for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } } v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dnanmeanpw( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +125,44 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dnanmeanpw_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +185,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/repl.txt index 48f29a8f7e28..d3a20624cee7 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -21,8 +21,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -36,22 +36,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 4, x, 2 ) ~0.3333 // Using view offsets: - > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -87,9 +84,8 @@ ~0.3333 // Using offset parameter: - > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); + > {{alias}}.ndarray( 4, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/types/index.d.ts index cf12016fb6f7..a8e7f8401428 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dnanmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dnanmeanpw.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/c/example.c index 2d2e043bd4e0..8aa7092a52b9 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dnanmeanpw.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; // Specify the number of elements: - int64_t N = 6; + const int N = 6; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dnanmeanpw( N, x, stride ); + double v = stdlib_strided_dnanmeanpw( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/index.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/index.js index 6f4e4256aff0..46cec3efa2a9 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var dnanmeanpw = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var v = dnanmeanpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/include/stdlib/stats/base/dnanmeanpw.h b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/include/stdlib/stats/base/dnanmeanpw.h index 62aa75c4b89d..201f0ae79b6c 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/include/stdlib/stats/base/dnanmeanpw.h +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/include/stdlib/stats/base/dnanmeanpw.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DNANMEANPW_H #define STDLIB_STATS_BASE_DNANMEANPW_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. */ -double stdlib_strided_dnanmeanpw( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dnanmeanpw)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dnanmeanpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.js index 148e0b9939a8..22d157af6fd3 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.js @@ -20,7 +20,8 @@ // MODULES // -var mean = require( './ndarray.js' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,54 +31,19 @@ var mean = require( './ndarray.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dnanmeanpw( N, x, 1 ); +* var v = dnanmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ -function dnanmeanpw( N, x, stride ) { - var ix; - var v; - var s; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( v === v ) { - s += v; - n += 1; - } - ix += stride; - } - if ( n === 0 ) { - return NaN; - } - return s / n; - } - return mean( N, x, stride, ix ); +function dnanmeanpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.native.js index 5c0646585329..1ac9fb9fc363 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnanmeanpw.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dnanmeanpw( N, x, 1 ); +* var v = dnanmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ -function dnanmeanpw( N, x, stride ) { - return addon( N, x, stride ); +function dnanmeanpw( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnansumpw.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnansumpw.js deleted file mode 100644 index d3877df88dd4..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/dnansumpw.js +++ /dev/null @@ -1,197 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var floor = require( '@stdlib/math/base/special/floor' ); - - -// VARIABLES // - -// Blocksize for pairwise summation (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.): -var BLOCKSIZE = 128; - - -// MAIN // - -/** -* Computes the sum of a double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation. -* -* ## Method -* -* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. -* -* ## References -* -* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). -* -* @private -* @param {PositiveInteger} N - number of indexed elements -* @param {NumericArray} out - two-element output array whose first element is the accumulated sum and whose second element is the accumulated number of summed values -* @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index -* @returns {NumericArray} output array -* -* @example -* var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); -* -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); -* var N = floor( x.length / 2 ); -* -* var out = [ 0.0, 0 ]; -* var v = dnansumpw( N, out, x, 2, 1 ); -* // returns [ 5.0, 4 ] -*/ -function dnansumpw( N, out, x, stride, offset ) { - var ix; - var s0; - var s1; - var s2; - var s3; - var s4; - var s5; - var s6; - var s7; - var M; - var s; - var n; - var v; - var i; - - if ( N <= 0 ) { - return out; - } - if ( N === 1 || stride === 0 ) { - if ( isnan( x[ offset ] ) ) { - return out; - } - out[ 0 ] += x[ offset ]; - out[ 1 ] += 1; - return out; - } - ix = offset; - if ( N < 8 ) { - // Use simple summation... - s = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( v === v ) { - s += v; - n += 1; - } - ix += stride; - } - out[ 0 ] += s; - out[ 1 ] += n; - return out; - } - if ( N <= BLOCKSIZE ) { - // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... - s0 = 0.0; - s1 = 0.0; - s2 = 0.0; - s3 = 0.0; - s4 = 0.0; - s5 = 0.0; - s6 = 0.0; - s7 = 0.0; - n = 0; - - M = N % 8; - for ( i = 0; i < N-M; i += 8 ) { - v = x[ ix ]; - if ( v === v ) { - s0 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s1 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s2 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s3 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s4 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s5 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s6 += v; - n += 1; - } - ix += stride; - v = x[ ix ]; - if ( v === v ) { - s7 += v; - n += 1; - } - ix += stride; - } - // Pairwise sum the accumulators: - s = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); - - // Clean-up loop... - for ( i; i < N; i++ ) { - v = x[ ix ]; - if ( v === v ) { - s += v; - n += 1; - } - ix += stride; - } - out[ 0 ] += s; - out[ 1 ] += n; - return out; - } - // Recurse by dividing by two, but avoiding non-multiples of unroll factor... - n = floor( N/2 ); - n -= n % 8; - return dnansumpw( n, out, x, stride, ix ) + dnansumpw( N-n, out, x, stride, ix+(n*stride) ); // eslint-disable-line max-len -} - - -// EXPORTS // - -module.exports = dnansumpw; diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/index.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/index.js index 50c645b68992..7c0a6bf03e4f 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/index.js @@ -28,20 +28,17 @@ * var dnanmeanpw = require( '@stdlib/stats/base/dnanmeanpw' ); * * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = 3; * -* var v = dnanmeanpw( N, x, 1 ); +* var v = dnanmeanpw( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dnanmeanpw = require( '@stdlib/stats/base/dnanmeanpw' ); * -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); * -* var v = dnanmeanpw.ndarray( N, x, 2, 1 ); +* var v = dnanmeanpw.ndarray( 5, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.js index 7fd658ecce11..ae2496485b6b 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.js @@ -20,12 +20,13 @@ // MODULES // -var dnansumpw = require( './dnansumpw.js' ); +var dnannsumpw = require( '@stdlib/blas/ext/base/dnannsumpw' ).ndarray; +var Float64Array = require( '@stdlib/array/float64' ); // VARIABLES // -var WORKSPACE = [ 0.0, 0 ]; +var WORKSPACE = new Float64Array( 2 ); // MAIN // @@ -35,24 +36,22 @@ var WORKSPACE = [ 0.0, 0 ]; * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); * -* var v = dnanmeanpw( N, x, 2, 1 ); +* var v = dnanmeanpw( 5, x, 2, 1 ); * // returns 1.25 */ -function dnanmeanpw( N, x, stride, offset ) { +function dnanmeanpw( N, x, strideX, offsetX ) { WORKSPACE[ 0 ] = 0.0; WORKSPACE[ 1 ] = 0; - dnansumpw( N, WORKSPACE, x, stride, offset ); + dnannsumpw( N, x, strideX, offsetX, WORKSPACE, 1, 0 ); return WORKSPACE[ 0 ] / WORKSPACE[ 1 ]; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.native.js index 241199f9aef3..5dad77fb72c7 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dnanmeanpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dnanmeanpw.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * -* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); * -* var v = dnanmeanpw( N, x, 2, 1 ); +* var v = dnanmeanpw( 5, x, 2, 1 ); * // returns 1.25 */ -function dnanmeanpw( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dnanmeanpw( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/manifest.json b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/manifest.json index 6b5be4a87f18..ff8e210b1c4c 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,77 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dnanmeanpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dnannsumpw", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dnannsumpw" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dnannsumpw" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dnannsumpw" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/addon.c new file mode 100644 index 000000000000..bd4dc00f0ae8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dnanmeanpw.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmeanpw)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmeanpw_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/addon.cpp deleted file mode 100644 index 382efc2b92fc..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanmeanpw.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanmeanpw { - - /** - * Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanmeanpw( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanmeanpw( N, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanmeanpw, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanmeanpw diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/dnanmeanpw.c b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/dnanmeanpw.c deleted file mode 100644 index b5472760d8fd..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/dnanmeanpw.c +++ /dev/null @@ -1,195 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanmeanpw.h" -#include - -/** -* Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation. -* -* ## Method -* -* - This implementation uses pairwise summation, which accrues rounding error `O(log2 N)` instead of `O(N)`. The recursion depth is also `O(log2 N)`. -* -* ## References -* -* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). -* -* @param N number of indexed elements -* @param W two-element output array -* @param X input array -* @param stride stride length -* @return output value -*/ -static void dnansumpw( const int64_t N, double *W, const double *X, const int64_t stride ) { - double *xp1; - double *xp2; - double sum; - int64_t ix; - int64_t M; - int64_t n; - int64_t i; - double s0; - double s1; - double s2; - double s3; - double s4; - double s5; - double s6; - double s7; - double v; - - if ( N <= 0 ) { - return; - } - if ( N == 1 || stride == 0 ) { - if ( X[ 0 ] == X[ 0 ] ) { - W[ 0 ] += X[ 0 ]; - W[ 1 ] += 1; - return; - } - return; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - if ( N < 8 ) { - // Use simple summation... - sum = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - if ( v == v ) { - sum += X[ ix ]; - n += 1; - } - ix += stride; - } - W[ 0 ] += sum; - W[ 1 ] += n; - return; - } - // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) - if ( N <= 128 ) { - // Sum a block with 8 accumulators (by loop unrolling, we lower the effective blocksize to 16)... - s0 = 0.0; - s1 = 0.0; - s2 = 0.0; - s3 = 0.0; - s4 = 0.0; - s5 = 0.0; - s6 = 0.0; - s7 = 0.0; - n = 0; - - M = N % 8; - for ( i = 0; i < N-M; i += 8 ) { - v = X[ ix ]; - if ( v == v ) { - s0 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s1 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s2 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s3 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s4 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s5 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s6 += v; - n += 1; - } - ix += stride; - v = X[ ix ]; - if ( v == v ) { - s7 += v; - n += 1; - } - ix += stride; - } - // Pairwise sum the accumulators: - sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); - - // Clean-up loop... - for (; i < N; i++ ) { - v = X[ ix ]; - if ( v == v ) { - sum += X[ ix ]; - n += 1; - } - ix += stride; - } - W[ 0 ] += sum; - W[ 1 ] += n; - return; - } - // Recurse by dividing by two, but avoiding non-multiples of unroll factor... - n = N / 2; - n -= n % 8; - if ( stride < 0 ) { - xp1 = (double *)X + ( (n-N)*stride ); - xp2 = (double *)X; - } else { - xp1 = (double *)X; - xp2 = (double *)X + ( n*stride ); - } - dnansumpw( n, W, xp1, stride ); - dnansumpw( N-n, W, xp2, stride ); -} - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dnanmeanpw( const int64_t N, const double *X, const int64_t stride ) { - double W[] = { 0.0, 0.0 }; - dnansumpw( N, W, X, stride ); - return W[ 0 ] / W[ 1 ]; -} diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/main.c b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/main.c new file mode 100644 index 000000000000..62c2d5ef9f0f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dnanmeanpw.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/blas/ext/base/dnannsumpw.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dnanmeanpw)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dnanmeanpw_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dnanmeanpw_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT n; // variable to store number of non `NaN` elements + + const double sum = API_SUFFIX(stdlib_strided_dnannsumpw_ndarray)( N, X, strideX, offsetX, &n ); + return sum / (double)n; +} diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.js index eef10e6ddc60..6964306de331 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dnanmeanpw = require( './../lib/dnanmeanpw.js' ); @@ -122,7 +121,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -138,15 +136,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, 2 ); + v = dnanmeanpw( 5, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; var i; @@ -162,9 +158,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0, NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, -2 ); + v = dnanmeanpw( 5, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); x = new Float64Array( 1e3 ); @@ -192,7 +187,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -209,9 +203,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dnanmeanpw( N, x1, 2 ); + v = dnanmeanpw( 5, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.native.js index 0d28a6494a72..c150aecde591 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.dnanmeanpw.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -213,7 +212,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -229,15 +227,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, 2 ); + v = dnanmeanpw( 5, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; var i; @@ -253,9 +249,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0, NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, -2 ); + v = dnanmeanpw( 5, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); x = new Float64Array( 1e3 ); @@ -283,7 +278,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -300,9 +294,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dnanmeanpw( N, x1, 2 ); + v = dnanmeanpw( 5, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.js index fe82c4108d3b..b28f43fb2f59 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dnanmeanpw = require( './../lib/ndarray.js' ); @@ -122,7 +121,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -138,15 +136,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, 2, 0 ); + v = dnanmeanpw( 5, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; var i; @@ -162,9 +158,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0, NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, -2, 6 ); + v = dnanmeanpw( 5, x, -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); x = new Float64Array( 1e3 ); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -206,9 +200,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, 2, 1 ); + v = dnanmeanpw( 5, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.native.js index c19044922de3..531b43c47a38 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanpw/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -131,7 +130,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -147,15 +145,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, 2, 0 ); + v = dnanmeanpw( 5, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; var i; @@ -171,9 +167,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0, NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, -2, 6 ); + v = dnanmeanpw( 5, x, -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); x = new Float64Array( 1e3 ); @@ -199,7 +194,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -215,9 +209,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanpw( N, x, 2, 1 ); + v = dnanmeanpw( 5, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md index 8392e1999459..2bc5dd63a3d8 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dnanmeanwd = require( '@stdlib/stats/base/dnanmeanwd' ); ``` -#### dnanmeanwd( N, x, stride ) +#### dnanmeanwd( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x`, using Welford's algorithm and ignoring `NaN` values. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -var N = x.length; -var v = dnanmeanwd( N, x, 1 ); +var v = dnanmeanwd( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: index increment for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] ); -var N = floor( x.length / 2 ); -var v = dnanmeanwd( N, x, 2 ); +var v = dnanmeanwd( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dnanmeanwd( N, x1, 2 ); +var v = dnanmeanwd( 4, x1, 2 ); // returns 1.25 ``` -#### dnanmeanwd.ndarray( N, x, stride, offset ) +#### dnanmeanwd.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -var N = x.length; -var v = dnanmeanwd.ndarray( N, x, 1, 0 ); +var v = dnanmeanwd.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -var N = floor( x.length / 2 ); -var v = dnanmeanwd.ndarray( N, x, 2, 1 ); +var v = dnanmeanwd.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -180,6 +171,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dnanmeanwd.h" +``` + +#### stdlib_strided_dnanmeanwd( N, \*X, strideX ) + +Computes the arithmetic mean of a double-precision floating-point strided array `x`, using Welford's algorithm and ignoring `NaN` values. + +```c +const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + +double v = stdlib_strided_dnanmeanwd( 6, x, 2 ); +// returns ~4.67 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dnanmeanwd( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dnanmeanwd_ndarray( N, \*X, strideX, offsetX ) + +Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + +double v = stdlib_strided_dnanmeanwd_ndarray( 6, x, 2, 0 ); +// returns ~4.67 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dnanmeanwd_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dnanmeanwd.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + + // Specify the number of elements: + const int N = 6; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dnanmeanwd( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js index 725749785047..5b3d7bd98e6f 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js @@ -21,16 +21,30 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dnanmeanwd = require( './../lib/dnanmeanwd.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -39,17 +53,7 @@ var dnanmeanwd = require( './../lib/dnanmeanwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js index 49d5321307e9..45aaba61cc4c 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js @@ -22,10 +22,11 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,6 +41,19 @@ var opts = { // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -48,17 +62,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js index f2e9d31a0fc1..c22b93247335 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js @@ -21,16 +21,30 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dnanmeanwd = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -39,17 +53,7 @@ var dnanmeanwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js index a62fc15c5406..77bdfc9108e7 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,11 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,6 +41,19 @@ var opts = { // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.2 ) ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -48,17 +62,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float64', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c index 3dce6d5a6c7f..7876ee3ceac5 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dnanmeanwd( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,44 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_double() < 0.2 ) { + x[ i ] = 0.0 / 0.0; // NaN + } else { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dnanmeanwd_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +181,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt index 33f938b1969d..9a707a6850a8 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -21,8 +21,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -36,28 +36,25 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -68,10 +65,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts index d674d840c966..9c5697ea52ca 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float64Array, stride: number ): number; + ( N: number, x: Float64Array, strideX: number ): number; /** * Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dnanmeanwd.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c index 03e6af11ea32..8d795c27ee78 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dnanmeanwd.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; // Specify the number of elements: - int64_t N = 6; + const int N = 6; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dnanmeanwd( N, x, stride ); + double v = stdlib_strided_dnanmeanwd( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h index aefd7c9a8c10..8cbe79514434 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DNANMEANWD_H #define STDLIB_STATS_BASE_DNANMEANWD_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. */ -double stdlib_strided_dnanmeanwd( const int64_t N, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dnanmeanwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js index a258c5ddbb53..26f73054c35b 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -43,50 +49,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dnanmeanwd( N, x, 1 ); +* var v = dnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dnanmeanwd( N, x, stride ) { - var mu; - var ix; - var v; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( v === v ) { - n += 1; - mu += ( v-mu ) / n; - } - ix += stride; - } - if ( n === 0 ) { - return NaN; - } - return mu; +function dnanmeanwd( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js index 453518fe3e67..758ec4ccd4f5 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dnanmeanwd( N, x, 1 ); +* var v = dnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dnanmeanwd( N, x, stride ) { - return addon( N, x, stride ); +function dnanmeanwd( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js index 9bf3e4eb75e7..9f251ed36e80 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js @@ -28,20 +28,17 @@ * var dnanmeanwd = require( '@stdlib/stats/base/dnanmeanwd' ); * * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = 3; * -* var v = dnanmeanwd( N, x, 1 ); +* var v = dnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dnanmeanwd = require( '@stdlib/stats/base/dnanmeanwd' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); * -* var v = dnanmeanwd.ndarray( N, x, 2, 1 ); +* var v = dnanmeanwd.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js index 3f76936b2e87..4beb52be8514 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js @@ -43,21 +43,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); * -* var v = dnanmeanwd( N, x, 2, 1 ); +* var v = dnanmeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function dnanmeanwd( N, x, stride, offset ) { +function dnanmeanwd( N, x, strideX, offsetX ) { var mu; var ix; var v; @@ -67,10 +65,10 @@ function dnanmeanwd( N, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; mu = 0.0; n = 0; for ( i = 0; i < N; i++ ) { @@ -79,7 +77,7 @@ function dnanmeanwd( N, x, stride, offset ) { n += 1; mu += ( v-mu ) / n; } - ix += stride; + ix += strideX; } if ( n === 0 ) { return NaN; diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js index 3acbd37309a2..b10036df551d 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dnanmeanwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dnanmeanwd.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); * -* var v = dnanmeanwd( N, x, 2, 1 ); +* var v = dnanmeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function dnanmeanwd( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dnanmeanwd( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json index 8bdb968d02e5..99aaf0c4da72 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task":"build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dnanmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -47,31 +49,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dnanmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dnanmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c index 89c2a60995db..4e057854c562 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c @@ -17,12 +17,12 @@ */ #include "stdlib/stats/base/dnanmeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float64array.h" #include "stdlib/napi/create_double.h" -#include "stdlib/napi/export.h" -#include /** * Receives JavaScript callback invocation data. @@ -34,10 +34,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmeanwd( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmeanwd)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( N, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c deleted file mode 100644 index ba1d54d3a05f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanmeanwd.h" -#include - -/** -* Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. -* -* ## Method -* -* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows -* -* ```tex -* \begin{align*} -* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ -* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ -* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ -* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) -* \end{align*} -* ``` -* -* ## References -* -* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). -* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dnanmeanwd( const int64_t N, const double *X, const int64_t stride ) { - int64_t ix; - int64_t i; - int64_t n; - double mu; - double v; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - if ( v == v ) { - n += 1; - mu += ( v-mu ) / (double)n; - } - ix += stride; - } - if ( n == 0 ) { - return 0.0 / 0.0; // NaN; - } - return mu; -} diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c new file mode 100644 index 000000000000..45806c5705d1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dnanmeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values. +* +* ## Method +* +* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows +* +* ```tex +* \begin{align*} +* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ +* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ +* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ +* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) +* \end{align*} +* ``` +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dnanmeanwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + CBLAS_INT n; + double mu; + double v; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + ix = offsetX; + mu = 0.0; + n = 0; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + if ( v == v ) { + n += 1; + mu += ( v-mu ) / (double)n; + } + ix += strideX; + } + if ( n == 0 ) { + return 0.0 / 0.0; // NaN; + } + return mu; +} diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js index 8d3e5c441607..5d8dfac2ea9e 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dnanmeanwd = require( './../lib/dnanmeanwd.js' ); @@ -90,7 +89,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -106,15 +104,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, 2 ); + v = dnanmeanwd( 5, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -130,8 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, -2 ); + v = dnanmeanwd( 5, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -152,7 +147,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -169,9 +163,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dnanmeanwd( N, x1, 2 ); + v = dnanmeanwd( 5, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js index 86d88d56366d..ccad2611f919 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -181,7 +180,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,15 +195,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, 2 ); + v = dnanmeanwd( 5, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -221,8 +217,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, -2 ); + v = dnanmeanwd( 5, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -243,7 +238,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -260,9 +254,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dnanmeanwd( N, x1, 2 ); + v = dnanmeanwd( 5, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js index 7dd106806e3e..fe56b5994118 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dnanmeanwd = require( './../lib/ndarray.js' ); @@ -90,7 +89,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -106,15 +104,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, 2, 0 ); + v = dnanmeanwd( 5, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -130,8 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, -2, 6 ); + v = dnanmeanwd( 5, x, -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -150,7 +145,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -166,9 +160,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, 2, 1 ); + v = dnanmeanwd( 5, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js index b6e78c8c14ab..3160f0db750f 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -99,7 +98,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -115,15 +113,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, 2, 0 ); + v = dnanmeanwd( 5, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -139,8 +135,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test NaN // 0 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, -2, 6 ); + v = dnanmeanwd( 5, x, -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -159,7 +154,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -175,9 +169,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = dnanmeanwd( N, x, 2, 1 ); + v = dnanmeanwd( 5, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dnanmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanmin/docs/repl.txt index 3a77999e6649..853168839a15 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanmin/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dnanmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanmin/src/addon.c index 8d8192bd6078..3aae54db887b 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanmin/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dnanmin/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dnanmin.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmin( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmin)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmin_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanmin_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanminabs/docs/repl.txt index 1049e8054100..663b2e2635df 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanminabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanminabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -64,7 +64,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dnanminabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanminabs/src/addon.c index 880a9f51d26b..b4940450c186 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanminabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dnanminabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dnanminabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanminabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanminabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanminabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanminabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanrange/docs/repl.txt index 3816f150889b..d51284684265 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanrange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dnanrange/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/dnanrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanrange/src/addon.c index 35c004a3e5b7..e8c668c83fa3 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanrange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dnanrange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dnanrange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanrange( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanrange)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanrange_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dnanrange_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevch/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanstdevch/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevch/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanstdevch/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanstdevch( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevch/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanstdevch/src/addon.cpp deleted file mode 100644 index 042b081059d5..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevch/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanstdevch.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanstdevch { - - /** - * Computes the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanstdevch( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanstdevch( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanstdevch, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanstdevch diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevpn/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanstdevpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanstdevpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanstdevpn( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanstdevpn/src/addon.cpp deleted file mode 100644 index 41f92df3f08b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevpn/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanstdevpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanstdevpn { - - /** - * Computes the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanstdevpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanstdevpn( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanstdevpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanstdevpn diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevtk/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanstdevtk/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevtk/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanstdevtk/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanstdevtk( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevtk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanstdevtk/src/addon.cpp deleted file mode 100644 index f5c0a7ca77e7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevtk/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanstdevtk.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanstdevtk { - - /** - * Computes the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanstdevtk( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanstdevtk( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanstdevtk, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanstdevtk diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevyc/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanstdevyc/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevyc/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanstdevyc/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanstdevyc( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanstdevyc/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanstdevyc/src/addon.cpp deleted file mode 100644 index 5d8d4f55725f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanstdevyc/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanstdevyc.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanstdevyc { - - /** - * Computes the standard deviation of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanstdevyc( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanstdevyc( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanstdevyc, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanstdevyc diff --git a/lib/node_modules/@stdlib/stats/base/dnanvariancech/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanvariancech/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanvariancech/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanvariancech/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanvariancech( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanvariancech/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanvariancech/src/addon.cpp deleted file mode 100644 index 01b9d05c8dbe..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanvariancech/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanvariancech.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanvariancech { - - /** - * Computes the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanvariancech( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanvariancech( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanvariancech, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanvariancech diff --git a/lib/node_modules/@stdlib/stats/base/dnanvariancepn/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanvariancepn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanvariancepn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanvariancepn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanvariancepn( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanvariancepn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanvariancepn/src/addon.cpp deleted file mode 100644 index 01c5aa3d59c6..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanvariancepn/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanvariancepn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanvariancepn { - - /** - * Computes the variance of a double-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanvariancepn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanvariancepn( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanvariancepn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanvariancepn diff --git a/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/include.gypi b/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanvarianceyc( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/src/addon.cpp deleted file mode 100644 index 51573d38fd17..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dnanvarianceyc/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dnanvarianceyc.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dnanvarianceyc { - - /** - * Computes the variance of a double-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dnanvarianceyc( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float64_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float64Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dnanvarianceyc( N, correction, (double *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dnanvarianceyc, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dnanvarianceyc diff --git a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts index f29e2223adb3..62b1fd635cf9 100644 --- a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts @@ -24,12 +24,10 @@ import cumax = require( '@stdlib/stats/base/cumax' ); import cumaxabs = require( '@stdlib/stats/base/cumaxabs' ); import cumin = require( '@stdlib/stats/base/cumin' ); import cuminabs = require( '@stdlib/stats/base/cuminabs' ); -import dcumax = require( '@stdlib/stats/base/dcumax' ); -import dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' ); +import dcumaxabs = require( '@stdlib/stats/strided/dcumaxabs' ); import dcumin = require( '@stdlib/stats/base/dcumin' ); import dcuminabs = require( '@stdlib/stats/base/dcuminabs' ); import dists = require( '@stdlib/stats/base/dists' ); -import dmax = require( '@stdlib/stats/base/dmax' ); import dmaxabs = require( '@stdlib/stats/base/dmaxabs' ); import dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' ); import dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' ); @@ -347,36 +345,6 @@ interface Namespace { */ cuminabs: typeof cuminabs; - /** - * Computes the cumulative maximum of double-precision floating-point strided array elements. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - `x` stride length - * @param y - output array - * @param strideY - `y` stride length - * @returns output array - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * var y = new Float64Array( x.length ); - * - * ns.dcumax( x.length, x, 1, y, 1 ); - * // y => [ 1.0, 1.0, 2.0 ] - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * var y = new Float64Array( x.length ); - * - * ns.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 ); - * // y => [ 1.0, 1.0, 2.0 ] - */ - dcumax: typeof dcumax; - /** * Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. * @@ -472,32 +440,6 @@ interface Namespace { */ dists: typeof dists; - /** - * Computes the maximum value of a double-precision floating-point strided array. - * - * @param N - number of indexed elements - * @param x - input array - * @param strideX - stride length - * @returns maximum value - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmax( x.length, x, 1 ); - * // returns 2.0 - * - * @example - * var Float64Array = require( '@stdlib/array/float64' ); - * - * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); - * - * var v = ns.dmax.ndarray( x.length, x, 1, 0 ); - * // returns 2.0 - */ - dmax: typeof dmax; - /** * Computes the maximum absolute value of a double-precision floating-point strided array. * @@ -529,7 +471,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum absolute value * * @example @@ -555,7 +497,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum value * * @example @@ -607,7 +549,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -633,7 +575,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -659,7 +601,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -711,7 +653,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -763,7 +705,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -913,7 +855,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -939,7 +881,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns median value * * @example @@ -1043,7 +985,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns minimum value * * @example @@ -1295,7 +1237,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -1321,7 +1263,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -1899,7 +1841,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -1953,7 +1895,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -1980,7 +1922,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -2007,7 +1949,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -2059,7 +2001,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -2085,7 +2027,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -2111,7 +2053,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -2137,7 +2079,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -2295,7 +2237,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -2349,7 +2291,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -2376,7 +2318,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -2403,7 +2345,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -2411,7 +2353,7 @@ interface Namespace { * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * - * var v = ns.dstdevyc( x.length, 1, x, 1 ); + * var v = ns.dstdevyc( x.length, 1.0, x, 1 ); * // returns ~2.0817 * * @example @@ -2419,7 +2361,7 @@ interface Namespace { * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * - * var v = ns.dstdevyc.ndarray( x.length, 1, x, 1, 0 ); + * var v = ns.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 ); * // returns ~2.0817 */ dstdevyc: typeof dstdevyc; @@ -2511,7 +2453,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -2565,7 +2507,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -2592,7 +2534,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -2619,7 +2561,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -2703,7 +2645,7 @@ interface Namespace { * @param mean - mean * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -4105,7 +4047,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -4261,7 +4203,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum value * * @example @@ -4365,7 +4307,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -4495,7 +4437,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -4521,7 +4463,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns median value * * @example @@ -4625,7 +4567,7 @@ interface Namespace { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns minimum value * * @example @@ -5455,7 +5397,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -5509,7 +5451,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -5755,7 +5697,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -5809,7 +5751,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -5863,7 +5805,7 @@ interface Namespace { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/drange/README.md b/lib/node_modules/@stdlib/stats/base/drange/README.md index cbc87d1bfead..264f4cf1fb0a 100644 --- a/lib/node_modules/@stdlib/stats/base/drange/README.md +++ b/lib/node_modules/@stdlib/stats/base/drange/README.md @@ -273,7 +273,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dmin`][@stdlib/stats/base/dmin]: calculate the minimum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/dnanrange`][@stdlib/stats/base/dnanrange]: calculate the range of a double-precision floating-point strided array, ignoring NaN values. - [`@stdlib/stats/base/range`][@stdlib/stats/base/range]: calculate the range of a strided array. @@ -295,7 +295,7 @@ int main( void ) { -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/dmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmin diff --git a/lib/node_modules/@stdlib/stats/base/drange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/drange/docs/repl.txt index c202b69c9fcb..017b57af1482 100644 --- a/lib/node_modules/@stdlib/stats/base/drange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/drange/docs/repl.txt @@ -19,7 +19,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/drange/src/addon.c b/lib/node_modules/@stdlib/stats/base/drange/src/addon.c index 0fcc975c7458..91e57ae44eca 100644 --- a/lib/node_modules/@stdlib/stats/base/drange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/drange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/drange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_drange( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_drange)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_drange_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_drange_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/README.md b/lib/node_modules/@stdlib/stats/base/dsemch/README.md index 041f4cca147b..a3aeb5ee759a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsemch/README.md @@ -70,7 +70,7 @@ where `s` is the sample [standard deviation][standard-deviation]. var dsemch = require( '@stdlib/stats/base/dsemch' ); ``` -#### dsemch( N, correction, x, stride ) +#### dsemch( N, correction, x, strideX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -78,9 +78,8 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemch( N, 1, x, 1 ); +var v = dsemch( x.length, 1, x, 1 ); // returns ~1.20185 ``` @@ -89,18 +88,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemch( N, 1, x, 2 ); +var v = dsemch( 4, 1, x, 2 ); // returns 1.25 ``` @@ -110,18 +107,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsemch( N, 1, x1, 2 ); +var v = dsemch( 4, 1, x1, 2 ); // returns 1.25 ``` -#### dsemch.ndarray( N, correction, x, stride, offset ) +#### dsemch.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -129,26 +123,23 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemch.ndarray( N, 1, x, 1, 0 ); +var v = dsemch.ndarray( x.length, 1, x, 1, 0 ); // returns ~1.20185 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemch.ndarray( N, 1, x, 2, 1 ); +var v = dsemch.ndarray( 4, 1, x, 2, 1 ); // returns 1.25 ``` @@ -175,18 +166,12 @@ var v = dsemch.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemch = require( '@stdlib/stats/base/dsemch' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemch( x.length, 1, x, 1 ); @@ -197,6 +182,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsemch.h" +``` + +#### stdlib_strided_dsemch( N, correction, \*X, strideX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemch( 3, 1.0, x, 1 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsemch( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsemch_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemch_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsemch_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsemch.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the standard error of the mean: + double v = stdlib_strided_dsemch( N, 1.0, x, strideX ); + + // Print the result: + printf( "standard error of the mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.js index bdda08b18894..731a607e2a5a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemch = require( './../lib/dsemch.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemch = require( './../lib/dsemch.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.native.js index cbdf2e52a2ae..e3bc32fa8efc 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemch = tryRequire( resolve( __dirname, './../lib/dsemch.native.js' ) ); var opts = { 'skip': ( dsemch instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.js index 25dfc554f7f5..b473ccdb0a31 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemch = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemch = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.native.js index 5f38ff7b8a6b..f00b8c81df76 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemch = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsemch instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/c/benchmark.length.c index 56179cd0aef0..bc1fc6a63c72 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsemch/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,7 +107,42 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { - v = stdlib_strided_dsemch( len, 1, x, 1 ); + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemch( len, 1.0, x, 1 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemch_ndarray( len, 1.0, x, 1, 0 ); if ( v != v ) { printf( "should not return NaN\n" ); break; @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsemch/docs/repl.txt index 2b814a441db2..054f5eb74eb7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsemch/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard error of the mean for a double-precision floating- point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~1.20185 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~1.20185 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~1.20185 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard error of the mean for a double-precision floating- point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~1.20185 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsemch/docs/types/index.d.ts index 7d03bbd84042..df8eb72cdd06 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsemch/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dsemch( x.length, 1, x, 1 ); * // returns ~1.20185 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard error of the mean * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dsemch.ndarray( x.length, 1, x, 1, 0 ); * // returns ~1.20185 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard error of the mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsemch/examples/c/example.c index bb5d65f6a8f7..3fc66e0a5536 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsemch/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsemch.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard error of the mean: - double v = stdlib_strided_dsemch( N, 1, x, stride ); + double v = stdlib_strided_dsemch( N, 1.0, x, strideX ); // Print the result: printf( "standard error of the mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsemch/examples/index.js index 95e35a1ca45c..dced37dc3536 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemch = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemch( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/include/stdlib/stats/base/dsemch.h b/lib/node_modules/@stdlib/stats/base/dsemch/include/stdlib/stats/base/dsemch.h index 191e1c1c58b7..c0b72ef3bab2 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/include/stdlib/stats/base/dsemch.h +++ b/lib/node_modules/@stdlib/stats/base/dsemch/include/stdlib/stats/base/dsemch.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSEMCH_H #define STDLIB_STATS_BASE_DSEMCH_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass trial mean algorithm. */ -double stdlib_strided_dsemch( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsemch)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsemch_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.js b/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.js index 673ebbde16c7..23ac8a3d1d6c 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.js @@ -20,8 +20,8 @@ // MODULES // -var dvariancech = require( '@stdlib/stats/base/dvariancech' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemch( N, 1, x, 1 ); +* var v = dsemch( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemch( N, correction, x, stride ) { - return sqrt( dvariancech( N, correction, x, stride ) / N ); +function dsemch( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.native.js b/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.native.js index 3d8e63ab74e6..5a830f600dcf 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/lib/dsemch.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemch( N, 1, x, 1 ); +* var v = dsemch( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemch( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dsemch( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsemch/lib/index.js index d98bffc4793e..dc6a93fa23f6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/lib/index.js @@ -28,20 +28,17 @@ * var dsemch = require( '@stdlib/stats/base/dsemch' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemch( N, 1, x, 1 ); +* var v = dsemch( x.length, 1, x, 1 ); * // returns ~1.20185 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsemch = require( '@stdlib/stats/base/dsemch' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemch.ndarray( N, 1, x, 2, 1 ); +* var v = dsemch.ndarray( 4, 1, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.js index a89d54ef3f02..fae0331d9ae7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.js @@ -32,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemch( N, 1, x, 2, 1 ); +* var v = dsemch( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemch( N, correction, x, stride, offset ) { - return sqrt( dvariancech( N, correction, x, stride, offset ) / N ); +function dsemch( N, correction, x, strideX, offsetX ) { + return sqrt( dvariancech( N, correction, x, strideX, offsetX ) / N ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.native.js index 96f9ba396999..f011bf242bb5 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dsemch.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dsemch.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemch( N, 1, x, 2, 1 ); +* var v = dsemch( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemch( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dsemch( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/manifest.json b/lib/node_modules/@stdlib/stats/base/dsemch/manifest.json index 078490afb8b9..a12f1212f754 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsemch/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -25,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dsemch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancech", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -47,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dsemch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancech" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dsemch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvariancech" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancech" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsemch/src/addon.c index 6b093b249499..827e53212235 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dsemch/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dsemch.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dsemch( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemch)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemch_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/src/dsemch.c b/lib/node_modules/@stdlib/stats/base/dsemch/src/dsemch.c deleted file mode 100644 index de4ceb9e44c7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsemch/src/dsemch.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsemch.h" -#include "stdlib/stats/base/dvariancech.h" -#include -#include - -/** -* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass trial mean algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsemch( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvariancech( N, correction, X, stride ) / (double)N ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/src/main.c b/lib/node_modules/@stdlib/stats/base/dsemch/src/main.c new file mode 100644 index 000000000000..30381ec7f28a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsemch/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsemch.h" +#include "stdlib/stats/base/dvariancech.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/special/sqrt.h" + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass trial mean algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemch)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsemch_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemch_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvariancech_ndarray)( N, correction, X, strideX, offsetX ) / (double)N ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.js b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.js index ca5d41e7941c..126c1f78d7ff 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, 2 ); + v = dsemch( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, -2 ); + v = dsemch( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -198,7 +193,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -214,9 +208,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemch( N, 1, x1, 2 ); + v = dsemch( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.native.js b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.native.js index cffa92e5d31f..281aa6036d43 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.dsemch.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, 2 ); + v = dsemch( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, -2 ); + v = dsemch( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -207,7 +202,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -223,9 +217,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemch( N, 1, x1, 2 ); + v = dsemch( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.js index d1e4497a4e9a..797b67660671 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, 2, 0 ); + v = dsemch( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, -2, 6 ); + v = dsemch( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -196,7 +191,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -210,9 +204,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, 2, 1 ); + v = dsemch( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.native.js index a4acef5ae318..f687d666e2ef 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemch/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, 2, 0 ); + v = dsemch( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, -2, 6 ); + v = dsemch( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -205,7 +200,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -219,9 +213,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemch( N, 1, x, 2, 1 ); + v = dsemch( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/README.md b/lib/node_modules/@stdlib/stats/base/dsemtk/README.md index ab6c894ee1e7..590416bb2599 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/README.md @@ -70,7 +70,7 @@ where `s` is the sample [standard deviation][standard-deviation]. var dsemtk = require( '@stdlib/stats/base/dsemtk' ); ``` -#### dsemtk( N, correction, x, stride ) +#### dsemtk( N, correction, x, strideX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array `x` using a one-pass textbook algorithm. @@ -78,9 +78,8 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemtk( N, 1, x, 1 ); +var v = dsemtk( x.length, 1, x, 1 ); // returns ~1.20185 ``` @@ -89,18 +88,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemtk( N, 1, x, 2 ); +var v = dsemtk( 4, 1, x, 2 ); // returns 1.25 ``` @@ -110,18 +107,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsemtk( N, 1, x1, 2 ); +var v = dsemtk( 4, 1, x1, 2 ); // returns 1.25 ``` -#### dsemtk.ndarray( N, correction, x, stride, offset ) +#### dsemtk.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -129,26 +123,23 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemtk.ndarray( N, 1, x, 1, 0 ); +var v = dsemtk.ndarray( x.length, 1, x, 1, 0 ); // returns ~1.20185 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemtk.ndarray( N, 1, x, 2, 1 ); +var v = dsemtk.ndarray( 4, 1, x, 2, 1 ); // returns 1.25 ``` @@ -175,18 +166,12 @@ var v = dsemtk.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemtk = require( '@stdlib/stats/base/dsemtk' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemtk( x.length, 1, x, 1 ); @@ -197,6 +182,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsemtk.h" +``` + +#### stdlib_strided_dsemtk( N, correction, \*X, strideX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass textbook algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemtk( 3, 1.0, x, 1 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsemtk( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsemtk_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemtk_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsemtk_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsemtk.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the standard error of the mean: + double v = stdlib_strided_dsemtk( N, 1.0, x, strideX ); + + // Print the result: + printf( "standard error of the mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.js index 07f45d370e55..4685f6178690 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemtk = require( './../lib/dsemtk.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemtk = require( './../lib/dsemtk.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.native.js index 36612f9d9729..ffb4af57a46a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemtk = tryRequire( resolve( __dirname, './../lib/dsemtk.native.js' ) ); var opts = { 'skip': ( dsemtk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.js index 2e866e0d6f4b..ef133aca2a3a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemtk = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemtk = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.native.js index 848773954fcb..ce90d1f80671 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemtk = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsemtk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/c/benchmark.length.c index 074389f5ea25..b5975a8c4276 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,7 +107,42 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { - v = stdlib_strided_dsemtk( len, 1, x, 1 ); + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemtk( len, 1.0, x, 1 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemtk_ndarray( len, 1.0, x, 1, 0 ); if ( v != v ) { printf( "should not return NaN\n" ); break; @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsemtk/docs/repl.txt index 29a5ab921185..4b1dcac937eb 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard error of the mean for a double-precision floating- point strided array using a one-pass textbook algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~1.20185 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~1.20185 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~1.20185 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard error of the mean for a double-precision floating- point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~1.20185 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsemtk/docs/types/index.d.ts index e77cc3a94b0b..8ac10926a502 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dsemtk( x.length, 1, x, 1 ); * // returns ~1.20185 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard error of the mean * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dsemtk.ndarray( x.length, 1, x, 1, 0 ); * // returns ~1.20185 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard error of the mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsemtk/examples/c/example.c index be514d8dea00..c02ca19f9b5a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsemtk.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard error of the mean: - double v = stdlib_strided_dsemtk( N, 1, x, stride ); + double v = stdlib_strided_dsemtk( N, 1.0, x, strideX ); // Print the result: printf( "standard error of the mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsemtk/examples/index.js index 797d57de3d00..01ab9a7441a6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemtk = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemtk( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/include/stdlib/stats/base/dsemtk.h b/lib/node_modules/@stdlib/stats/base/dsemtk/include/stdlib/stats/base/dsemtk.h index 40f28d288a53..4c4711844c3b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/include/stdlib/stats/base/dsemtk.h +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/include/stdlib/stats/base/dsemtk.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSEMTK_H #define STDLIB_STATS_BASE_DSEMTK_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass textbook algorithm. */ -double stdlib_strided_dsemtk( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsemtk)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsemtk_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.js b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.js index f9e91a1555c6..d9cdf64caaee 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.js @@ -20,8 +20,8 @@ // MODULES // -var dvariancetk = require( '@stdlib/stats/base/dvariancetk' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemtk( N, 1, x, 1 ); +* var v = dsemtk( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemtk( N, correction, x, stride ) { - return sqrt( dvariancetk( N, correction, x, stride ) / N ); +function dsemtk( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.native.js b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.native.js index d6f7cff1eda1..713cee2148d5 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/dsemtk.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemtk( N, 1, x, 1 ); +* var v = dsemtk( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemtk( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dsemtk( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/index.js index 65e282fee5d7..c5423a42818f 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/index.js @@ -28,20 +28,17 @@ * var dsemtk = require( '@stdlib/stats/base/dsemtk' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemtk( N, 1, x, 1 ); +* var v = dsemtk( x.length, 1, x, 1 ); * // returns ~1.20185 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsemtk = require( '@stdlib/stats/base/dsemtk' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemtk.ndarray( N, 1, x, 2, 1 ); +* var v = dsemtk.ndarray( 4, 1, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.js index 9108ed6673a3..47699799db57 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.js @@ -32,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemtk( N, 1, x, 2, 1 ); +* var v = dsemtk( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemtk( N, correction, x, stride, offset ) { - return sqrt( dvariancetk( N, correction, x, stride, offset ) / N ); +function dsemtk( N, correction, x, strideX, offsetX ) { + return sqrt( dvariancetk( N, correction, x, strideX, offsetX ) / N ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.native.js index 32e220b529ba..792f7a9c8c9c 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dsemtk.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dsemtk.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemtk( N, 1, x, 2, 1 ); +* var v = dsemtk( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemtk( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dsemtk( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/manifest.json b/lib/node_modules/@stdlib/stats/base/dsemtk/manifest.json index 54348e4c6d8c..a816ad11dae6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dsemtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancetk", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -49,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dsemtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancetk" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dsemtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvariancetk" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancetk" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsemtk/src/addon.c index 277e474f2286..51f956bcf606 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dsemtk.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dsemtk( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemtk)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemtk_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/src/dsemtk.c b/lib/node_modules/@stdlib/stats/base/dsemtk/src/dsemtk.c deleted file mode 100644 index 160366af09b2..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/src/dsemtk.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsemtk.h" -#include "stdlib/stats/base/dvariancetk.h" -#include -#include - -/** -* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass textbook algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsemtk( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvariancetk( N, correction, X, stride ) / (double)N ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/src/main.c b/lib/node_modules/@stdlib/stats/base/dsemtk/src/main.c new file mode 100644 index 000000000000..e5615b483bb9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsemtk.h" +#include "stdlib/stats/base/dvariancetk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/special/sqrt.h" + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass textbook algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemtk)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsemtk_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemtk_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvariancetk_ndarray)( N, correction, X, strideX, offsetX ) / (double)N ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.js b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.js index bf6b78482e41..a7f9fddbb025 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, 2 ); + v = dsemtk( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, -2 ); + v = dsemtk( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -198,7 +193,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -214,9 +208,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemtk( N, 1, x1, 2 ); + v = dsemtk( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.native.js b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.native.js index 3ac7cda52e25..94b899510f5d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.dsemtk.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, 2 ); + v = dsemtk( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, -2 ); + v = dsemtk( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -207,7 +202,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -223,9 +217,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemtk( N, 1, x1, 2 ); + v = dsemtk( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.js index 93fbabb61f8b..5f0899cf8be9 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, 2, 0 ); + v = dsemtk( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, -2, 6 ); + v = dsemtk( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -196,7 +191,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -210,9 +204,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, 2, 1 ); + v = dsemtk( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.native.js index 55aacc40245d..c69684647980 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemtk/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, 2, 0 ); + v = dsemtk( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, -2, 6 ); + v = dsemtk( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -205,7 +200,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -219,9 +213,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemtk( N, 1, x, 2, 1 ); + v = dsemtk( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/README.md b/lib/node_modules/@stdlib/stats/base/dsemwd/README.md index ea94c1ec11a2..4452bb90c96d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/README.md @@ -70,7 +70,7 @@ where `s` is the sample [standard deviation][standard-deviation]. var dsemwd = require( '@stdlib/stats/base/dsemwd' ); ``` -#### dsemwd( N, correction, x, stride ) +#### dsemwd( N, correction, x, strideX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array `x` using Welford's algorithm. @@ -78,9 +78,8 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemwd( N, 1, x, 1 ); +var v = dsemwd( x.length, 1, x, 1 ); // returns ~1.20185 ``` @@ -89,18 +88,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemwd( N, 1, x, 2 ); +var v = dsemwd( 4, 1, x, 2 ); // returns 1.25 ``` @@ -110,18 +107,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsemwd( N, 1, x1, 2 ); +var v = dsemwd( 4, 1, x1, 2 ); // returns 1.25 ``` -#### dsemwd.ndarray( N, correction, x, stride, offset ) +#### dsemwd.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -129,26 +123,23 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemwd.ndarray( N, 1, x, 1, 0 ); +var v = dsemwd.ndarray( x.length, 1, x, 1, 0 ); // returns ~1.20185 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemwd.ndarray( N, 1, x, 2, 1 ); +var v = dsemwd.ndarray( 4, 1, x, 2, 1 ); // returns 1.25 ``` @@ -174,18 +165,12 @@ var v = dsemwd.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemwd = require( '@stdlib/stats/base/dsemwd' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemwd( x.length, 1, x, 1 ); @@ -196,6 +181,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsemwd.h" +``` + +#### stdlib_strided_dsemwd( N, correction, \*X, strideX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using Welford's algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemwd( 3, 1.0, x, 1 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsemwd( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsemwd_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemwd_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsemwd_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsemwd.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the standard error of the mean: + double v = stdlib_strided_dsemwd( N, 1.0, x, strideX ); + + // Print the result: + printf( "standard error of the mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.js index 7ec3bd232308..aade64e74fe3 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemwd = require( './../lib/dsemwd.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemwd = require( './../lib/dsemwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.native.js index ebea48f7c9f6..d18c3254fe62 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemwd = tryRequire( resolve( __dirname, './../lib/dsemwd.native.js' ) ); var opts = { 'skip': ( dsemwd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.js index 1bf3e7d55536..ae70d5fa81b7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemwd = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.native.js index 768df1bef7d9..a0b49c572468 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsemwd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/c/benchmark.length.c index a9ee4e0a8fb9..08896a71fd47 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,7 +107,42 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { - v = stdlib_strided_dsemwd( len, 1, x, 1 ); + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemwd( len, 1.0, x, 1 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemwd_ndarray( len, 1.0, x, 1, 0 ); if ( v != v ) { printf( "should not return NaN\n" ); break; @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsemwd/docs/repl.txt index bfbfb83f4a2a..86f0d75f37a4 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard error of the mean for a double-precision floating- point strided array using Welford's algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~1.20185 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~1.20185 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~1.20185 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard error of the mean for a double-precision floating- point strided array using Welford's algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~1.20185 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsemwd/docs/types/index.d.ts index b846584de3ac..9e8316ad7f68 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dsemwd( x.length, 1, x, 1 ); * // returns ~1.20185 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard error of the mean for a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard error of the mean * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dsemwd.ndarray( x.length, 1, x, 1, 0 ); * // returns ~1.20185 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard error of the mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsemwd/examples/c/example.c index 16366f10e684..20c7e066b867 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsemwd.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard error of the mean: - double v = stdlib_strided_dsemwd( N, 1, x, stride ); + double v = stdlib_strided_dsemwd( N, 1.0, x, strideX ); // Print the result: printf( "standard error of the mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsemwd/examples/index.js index ef3d50750ebc..3adce88be613 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemwd = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemwd( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/include/stdlib/stats/base/dsemwd.h b/lib/node_modules/@stdlib/stats/base/dsemwd/include/stdlib/stats/base/dsemwd.h index 3c55176e0933..7203c05cdb73 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/include/stdlib/stats/base/dsemwd.h +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/include/stdlib/stats/base/dsemwd.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSEMWD_H #define STDLIB_STATS_BASE_DSEMWD_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard error of the mean for a double-precision floating-point strided array using Welford's algorithm. */ -double stdlib_strided_dsemwd( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsemwd)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsemwd_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.js b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.js index 6421bae1f60c..e0c1c6112181 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.js @@ -20,8 +20,8 @@ // MODULES // -var dvariancewd = require( '@stdlib/stats/base/dvariancewd' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemwd( N, 1, x, 1 ); +* var v = dsemwd( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemwd( N, correction, x, stride ) { - return sqrt( dvariancewd( N, correction, x, stride ) / N ); +function dsemwd( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.native.js b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.native.js index 896b9ba0a644..ac7ecbb5c75f 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/dsemwd.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemwd( N, 1, x, 1 ); +* var v = dsemwd( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemwd( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dsemwd( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/index.js index fb4b4ab048b0..e8eba5642d81 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/index.js @@ -28,20 +28,17 @@ * var dsemwd = require( '@stdlib/stats/base/dsemwd' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemwd( N, 1, x, 1 ); +* var v = dsemwd( x.length, 1, x, 1 ); * // returns ~1.20185 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsemwd = require( '@stdlib/stats/base/dsemwd' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemwd.ndarray( N, 1, x, 2, 1 ); +* var v = dsemwd.ndarray( 4, 1, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.js index 20b8d12e1793..6bdc8f31632f 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.js @@ -32,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemwd( N, 1, x, 2, 1 ); +* var v = dsemwd( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemwd( N, correction, x, stride, offset ) { - return sqrt( dvariancewd( N, correction, x, stride, offset ) / N ); +function dsemwd( N, correction, x, strideX, offsetX ) { + return sqrt( dvariancewd( N, correction, x, strideX, offsetX ) / N ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.native.js index 3f1e906da33b..561ecbd2cfa2 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dsemwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dsemwd.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemwd( N, 1, x, 2, 1 ); +* var v = dsemwd( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemwd( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dsemwd( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dsemwd/manifest.json index ab8264b2e36f..dd5060f5aa7d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dsemwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancewd", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -49,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dsemwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancewd" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dsemwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvariancewd" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancewd" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsemwd/src/addon.c index d4c2c96f7106..714a14c1dfe8 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dsemwd.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dsemwd( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemwd)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemwd_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/src/dsemwd.c b/lib/node_modules/@stdlib/stats/base/dsemwd/src/dsemwd.c deleted file mode 100644 index 8bc8a92ae2f6..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/src/dsemwd.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsemwd.h" -#include "stdlib/stats/base/dvariancewd.h" -#include -#include - -/** -* Computes the standard error of the mean for a double-precision floating-point strided array using Welford's algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsemwd( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvariancewd( N, correction, X, stride ) / (double)N ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/src/main.c b/lib/node_modules/@stdlib/stats/base/dsemwd/src/main.c new file mode 100644 index 000000000000..6dadbfed0f44 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsemwd.h" +#include "stdlib/stats/base/dvariancewd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/special/sqrt.h" + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using Welford's algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemwd)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsemwd_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemwd_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvariancewd_ndarray)( N, correction, X, strideX, offsetX ) / (double)N ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.js b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.js index 30202b1a2432..62ecdf1d0f03 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, 2 ); + v = dsemwd( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, -2 ); + v = dsemwd( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -198,7 +193,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -214,9 +208,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemwd( N, 1, x1, 2 ); + v = dsemwd( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.native.js b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.native.js index 91b20c0b704b..0b808e1ce7e0 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.dsemwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, 2 ); + v = dsemwd( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, -2 ); + v = dsemwd( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -207,7 +202,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -223,9 +217,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemwd( N, 1, x1, 2 ); + v = dsemwd( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.js index cbb8b786cc7b..7f0139063c0d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, 2, 0 ); + v = dsemwd( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, -2, 6 ); + v = dsemwd( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -196,7 +191,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -210,9 +204,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, 2, 1 ); + v = dsemwd( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.native.js index 7e128e73ce8c..745152740110 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, 2, 0 ); + v = dsemwd( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, -2, 6 ); + v = dsemwd( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -205,7 +200,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -219,9 +213,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemwd( N, 1, x, 2, 1 ); + v = dsemwd( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/README.md b/lib/node_modules/@stdlib/stats/base/dsemyc/README.md index c9cdcc5014b0..5784f3100af3 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/README.md @@ -70,7 +70,7 @@ where `s` is the sample [standard deviation][standard-deviation]. var dsemyc = require( '@stdlib/stats/base/dsemyc' ); ``` -#### dsemyc( N, correction, x, stride ) +#### dsemyc( N, correction, x, strideX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array `x` using a one-pass algorithm proposed by Youngs and Cramer. @@ -78,9 +78,8 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemyc( N, 1, x, 1 ); +var v = dsemyc( x.length, 1, x, 1 ); // returns ~1.20185 ``` @@ -89,18 +88,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemyc( N, 1, x, 2 ); +var v = dsemyc( 4, 1, x, 2 ); // returns 1.25 ``` @@ -110,18 +107,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsemyc( N, 1, x1, 2 ); +var v = dsemyc( 4, 1, x1, 2 ); // returns 1.25 ``` -#### dsemyc.ndarray( N, correction, x, stride, offset ) +#### dsemyc.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -129,26 +123,23 @@ Computes the [standard error of the mean][standard-error] of a double-precision var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsemyc.ndarray( N, 1, x, 1, 0 ); +var v = dsemyc.ndarray( x.length, 1, x, 1, 0 ); // returns ~1.20185 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsemyc.ndarray( N, 1, x, 2, 1 ); +var v = dsemyc.ndarray( 4, 1, x, 2, 1 ); // returns 1.25 ``` @@ -174,18 +165,12 @@ var v = dsemyc.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemyc = require( '@stdlib/stats/base/dsemyc' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemyc( x.length, 1, x, 1 ); @@ -196,6 +181,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsemyc.h" +``` + +#### stdlib_strided_dsemyc( N, correction, \*X, strideX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemyc( 3, 1.0, x, 1 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsemyc( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsemyc_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dsemyc_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~1.20185 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsemyc_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsemyc.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the standard error of the mean: + double v = stdlib_strided_dsemyc( N, 1.0, x, strideX ); + + // Print the result: + printf( "standard error of the mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.js index 8b68b0e4f879..ca263eec94c5 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemyc = require( './../lib/dsemyc.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemyc = require( './../lib/dsemyc.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.native.js index 077253659ec8..18a75fa0a9b1 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemyc = tryRequire( resolve( __dirname, './../lib/dsemyc.native.js' ) ); var opts = { 'skip': ( dsemyc instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.js index 3dd132fedc25..f06c6b525d57 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dsemyc = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsemyc = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.native.js index 8d3d5523acb8..7e31296e4d77 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsemyc = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsemyc instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/c/benchmark.length.c index f01eb33a2adb..b884be64c66f 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,7 +107,42 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { - v = stdlib_strided_dsemyc( len, 1, x, 1 ); + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemyc( len, 1.0, x, 1 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsemyc_ndarray( len, 1.0, x, 1, 0 ); if ( v != v ) { printf( "should not return NaN\n" ); break; @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsemyc/docs/repl.txt index bc8f60494cc5..87e6c0c33b0b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/docs/repl.txt @@ -1,11 +1,11 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard error of the mean for a double-precision floating- point strided array using a one-pass algorithm proposed by Youngs and Cramer. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -32,8 +32,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -47,22 +47,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~1.20185 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~1.20185 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~1.20185 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard error of the mean for a double-precision floating- point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -91,10 +88,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -111,8 +108,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~1.20185 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsemyc/docs/types/index.d.ts index 8877713b76eb..55113b0f037c 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard error of the mean * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dsemyc( x.length, 1, x, 1 ); * // returns ~1.20185 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard error of the mean * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dsemyc.ndarray( x.length, 1, x, 1, 0 ); * // returns ~1.20185 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard error of the mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsemyc/examples/c/example.c index 1abfeaf05dd8..66e09cbbd379 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsemyc.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard error of the mean: - double v = stdlib_strided_dsemyc( N, 1, x, stride ); + double v = stdlib_strided_dsemyc( N, 1.0, x, strideX ); // Print the result: printf( "standard error of the mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsemyc/examples/index.js index 6c9e7ea1df55..9fc0317715de 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsemyc = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dsemyc( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/include/stdlib/stats/base/dsemyc.h b/lib/node_modules/@stdlib/stats/base/dsemyc/include/stdlib/stats/base/dsemyc.h index c8685e6a06aa..0ee4fca34b2d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/include/stdlib/stats/base/dsemyc.h +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/include/stdlib/stats/base/dsemyc.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSEMYC_H #define STDLIB_STATS_BASE_DSEMYC_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. */ -double stdlib_strided_dsemyc( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsemyc)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsemyc_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.js b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.js index ec579ada7f50..f4253c08c4f0 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.js @@ -20,8 +20,8 @@ // MODULES // -var dvarianceyc = require( '@stdlib/stats/base/dvarianceyc' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemyc( N, 1, x, 1 ); +* var v = dsemyc( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemyc( N, correction, x, stride ) { - return sqrt( dvarianceyc( N, correction, x, stride ) / N ); +function dsemyc( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.native.js b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.native.js index 57c75e9ca887..45d4556593ce 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/dsemyc.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemyc( N, 1, x, 1 ); +* var v = dsemyc( x.length, 1, x, 1 ); * // returns ~1.20185 */ -function dsemyc( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dsemyc( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/index.js index 0d60c61a2eec..d0779f16732d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/index.js @@ -28,20 +28,17 @@ * var dsemyc = require( '@stdlib/stats/base/dsemyc' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsemyc( N, 1, x, 1 ); +* var v = dsemyc( x.length, 1, x, 1 ); * // returns ~1.20185 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsemyc = require( '@stdlib/stats/base/dsemyc' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemyc.ndarray( N, 1, x, 2, 1 ); +* var v = dsemyc.ndarray( 4, 1, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.js index 307187116be5..2bc8d40ce7a7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.js @@ -32,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemyc( N, 1, x, 2, 1 ); +* var v = dsemyc( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemyc( N, correction, x, stride, offset ) { - return sqrt( dvarianceyc( N, correction, x, stride, offset ) / N ); +function dsemyc( N, correction, x, strideX, offsetX ) { + return sqrt( dvarianceyc( N, correction, x, strideX, offsetX ) / N ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.native.js index 82269709311b..419f84ddd017 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dsemyc.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dsemyc.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard error of the mean * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsemyc( N, 1, x, 2, 1 ); +* var v = dsemyc( 4, 1, x, 2, 1 ); * // returns 1.25 */ -function dsemyc( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dsemyc( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/manifest.json b/lib/node_modules/@stdlib/stats/base/dsemyc/manifest.json index 1241b68020ff..db81f65afb3a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dsemyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvarianceyc", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -49,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dsemyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvarianceyc" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dsemyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvarianceyc" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvarianceyc" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsemyc/src/addon.c index 561b4d233fcc..70c62d74b39d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dsemyc.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dsemyc( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemyc)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsemyc_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/src/dsemyc.c b/lib/node_modules/@stdlib/stats/base/dsemyc/src/dsemyc.c deleted file mode 100644 index 3781a4125cfc..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/src/dsemyc.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsemyc.h" -#include "stdlib/stats/base/dvarianceyc.h" -#include -#include - -/** -* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsemyc( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvarianceyc( N, correction, X, stride ) / (double)N ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/src/main.c b/lib/node_modules/@stdlib/stats/base/dsemyc/src/main.c new file mode 100644 index 000000000000..2d3ac2fad79f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsemyc.h" +#include "stdlib/stats/base/dvarianceyc.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/special/sqrt.h" + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemyc)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsemyc_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard error of the mean for a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsemyc_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvarianceyc_ndarray)( N, correction, X, strideX, offsetX ) / (double)N ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.js b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.js index 281aa09e6c37..1708a8891a14 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, 2 ); + v = dsemyc( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, -2 ); + v = dsemyc( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -198,7 +193,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -214,9 +208,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemyc( N, 1, x1, 2 ); + v = dsemyc( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.native.js b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.native.js index 74e5640c30d0..32246f566614 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.dsemyc.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, 2 ); + v = dsemyc( 4, 1, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, -2 ); + v = dsemyc( 4, 1, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -207,7 +202,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -223,9 +217,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsemyc( N, 1, x1, 2 ); + v = dsemyc( 4, 1, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.js index cb749f4289e2..9bcb8eb50f04 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -138,7 +137,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -153,15 +151,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, 2, 0 ); + v = dsemyc( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -176,8 +172,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, -2, 6 ); + v = dsemyc( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -196,7 +191,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -210,9 +204,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, 2, 1 ); + v = dsemyc( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.native.js index 4c2f9b083666..0d84cea7b091 100644 --- a/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsemyc/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -147,7 +146,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -162,15 +160,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, 2, 0 ); + v = dsemyc( 4, 1, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -185,8 +181,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, -2, 6 ); + v = dsemyc( 4, 1, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -205,7 +200,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -219,9 +213,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsemyc( N, 1, x, 2, 1 ); + v = dsemyc( 4, 1, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmean/include.gypi b/lib/node_modules/@stdlib/stats/base/dsmean/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmean/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dsmean/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dsmean( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/dsmean/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dsmean/src/addon.cpp deleted file mode 100644 index ef7724d20424..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmean/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmean.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dsmean { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dsmean( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dsmean( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsmean, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dsmean diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/README.md b/lib/node_modules/@stdlib/stats/base/dsmeanors/README.md index 47c4ca5ee399..4506d90f1f4a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dsmeanors = require( '@stdlib/stats/base/dsmeanors' ); ``` -#### dsmeanors( N, x, stride ) +#### dsmeanors( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using ordinary recursive summation with extended accumulation and returning an extended precision result. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanors( N, x, 1 ); +var v = dsmeanors( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanors( N, x, 2 ); +var v = dsmeanors( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsmeanors( N, x1, 2 ); +var v = dsmeanors( 4, x1, 2 ); // returns 1.25 ``` -#### dsmeanors.ndarray( N, x, stride, offset ) +#### dsmeanors.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics and returning an extended precision result. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanors.ndarray( N, x, 1, 0 ); +var v = dsmeanors.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanors.ndarray( N, x, 2, 1 ); +var v = dsmeanors.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -155,18 +146,12 @@ var v = dsmeanors.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanors = require( '@stdlib/stats/base/dsmeanors' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanors( x.length, x, 1 ); @@ -177,6 +162,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsmeanors.h" +``` + +#### stdlib_strided_dsmeanors( N, \*X, strideX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanors( 4, x, 2 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsmeanors( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsmeanors_ndarray( N, \*X, strideX, offsetX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanors_ndarray( 4, x, 2, 0 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsmeanors_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsmeanors.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dsmeanors( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.js index f68b0fa0cf1f..ace9e1da533e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanors = require( './../lib/dsmeanors.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanors = require( './../lib/dsmeanors.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.native.js index a7cb469f12a7..4bb23569a0d6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanors = tryRequire( resolve( __dirname, './../lib/dsmeanors.native.js' ) var opts = { 'skip': ( dsmeanors instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.js index 01def84741aa..195d3881bbda 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.native.js index 8a8d29206cfa..bc585b7082fd 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( dsmeanors instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/c/benchmark.length.c index f7fe783174ff..90c5a11928b4 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsmeanors( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsmeanors_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/repl.txt index 59bbf9b5c70f..22a3732ae4ec 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/repl.txt @@ -1,11 +1,11 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,8 +20,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -35,28 +35,25 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics and returning an extended precision result. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -67,10 +64,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -87,8 +84,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/types/index.d.ts index 3b776cb27992..d23d6d012a68 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsmeanors( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics and returning an extended precision result. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsmeanors.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/c/example.c index d72047bbbc45..4727af8572b6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsmeanors.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dsmeanors( N, x, stride ); + double v = stdlib_strided_dsmeanors( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/index.js index bb4c6501d077..2289efa668ac 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanors = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/include.gypi b/lib/node_modules/@stdlib/stats/base/dsmeanors/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. */ -double stdlib_strided_dsmeanors( const int64_t N, const float *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsmeanors)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean value of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics and returning an extended precision result. +*/ +double API_SUFFIX(stdlib_strided_dsmeanors_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.js index 62a50574bf1c..e6ae5ba9c467 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.js @@ -20,7 +20,8 @@ // MODULES // -var dssumors = require( '@stdlib/blas/ext/base/dssumors' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,26 +31,19 @@ var dssumors = require( '@stdlib/blas/ext/base/dssumors' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanors( N, x, 1 ); +* var v = dsmeanors( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanors( N, x, stride ) { - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - return dssumors( N, x, stride ) / N; +function dsmeanors( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.native.js index 150b7a331448..b46d1ab06e30 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/dsmeanors.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanors( N, x, 1 ); +* var v = dsmeanors( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanors( N, x, stride ) { - return addon( N, x, stride ); +function dsmeanors( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/index.js index 7ca2fc5374d8..309f3d56ca79 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/index.js @@ -28,20 +28,17 @@ * var dsmeanors = require( '@stdlib/stats/base/dsmeanors' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanors( N, x, 1 ); +* var v = dsmeanors( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsmeanors = require( '@stdlib/stats/base/dsmeanors' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanors.ndarray( N, x, 2, 1 ); +* var v = dsmeanors.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.js index 9cb867d7b56a..8fd1ac01c88e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.js @@ -30,28 +30,26 @@ var dssumors = require( '@stdlib/blas/ext/base/dssumors' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanors( N, x, 2, 1 ); +* var v = dsmeanors( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanors( N, x, stride, offset ) { +function dsmeanors( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return dssumors( N, x, stride, offset ) / N; + return dssumors( N, x, strideX, offsetX ) / N; } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.native.js index 493aff51b1b0..0a0d8189aaf0 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './dsmeanors.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dsmeanors.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanors( N, x, 2, 1 ); +* var v = dsmeanors( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanors( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dsmeanors( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/manifest.json b/lib/node_modules/@stdlib/stats/base/dsmeanors/manifest.json index 3c7ff4b5010a..f55b17149918 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,75 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dsmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumors", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumors" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumors" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dssumors" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsmeanors/src/addon.c new file mode 100644 index 000000000000..04752a50fb15 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/src/addon.c @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanors.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/blas/base/shared.h" + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanors)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanors_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dsmeanors/src/addon.cpp deleted file mode 100644 index 0b019c9ab838..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanors.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dsmeanors { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dsmeanors( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dsmeanors( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsmeanors, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dsmeanors diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/src/dsmeanors.c b/lib/node_modules/@stdlib/stats/base/dsmeanors/src/dsmeanors.c deleted file mode 100644 index f934752d03a8..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/src/dsmeanors.c +++ /dev/null @@ -1,39 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanors.h" -#include "stdlib/blas/ext/base/dssumors.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsmeanors( const int64_t N, const float *X, const int64_t stride ) { - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - return stdlib_strided_dssumors( N, X, stride ) / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/src/main.c b/lib/node_modules/@stdlib/stats/base/dsmeanors/src/main.c new file mode 100644 index 000000000000..fc51c869bd93 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/src/main.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanors.h" +#include "stdlib/blas/ext/base/dssumors.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and returning an extended precision result. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanors)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsmeanors_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics and returning an extended precision result. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanors_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return stdlib_strided_dssumors_ndarray( N, X, strideX, offsetX ) / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.js index aa1fc582ae7b..f708637b7924 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanors = require( './../lib/dsmeanors.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, 2 ); + v = dsmeanors( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, -2 ); + v = dsmeanors( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanors( N, x1, 2 ); + v = dsmeanors( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.native.js index dbf77715be2f..06b952d066d7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.dsmeanors.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, 2 ); + v = dsmeanors( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, -2 ); + v = dsmeanors( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanors( N, x1, 2 ); + v = dsmeanors( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.js index 69101e09859e..5438a56f6e25 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanors = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, 2, 0 ); + v = dsmeanors( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, -2, 6 ); + v = dsmeanors( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, 2, 1 ); + v = dsmeanors( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.native.js index 5c9f4d93c6c6..2ad93ad93f23 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanors/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, 2, 0 ); + v = dsmeanors( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, -2, 6 ); + v = dsmeanors( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanors( N, x, 2, 1 ); + v = dsmeanors( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/README.md b/lib/node_modules/@stdlib/stats/base/dsmeanpn/README.md index 53fd8f36ebde..b2a4a7bd69a2 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dsmeanpn = require( '@stdlib/stats/base/dsmeanpn' ); ``` -#### dsmeanpn( N, x, stride ) +#### dsmeanpn( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanpn( N, x, 1 ); +var v = dsmeanpn( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanpn( N, x, 2 ); +var v = dsmeanpn( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsmeanpn( N, x1, 2 ); +var v = dsmeanpn( 4, x1, 2 ); // returns 1.25 ``` -#### dsmeanpn.ndarray( N, x, stride, offset ) +#### dsmeanpn.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanpn.ndarray( N, x, 1, 0 ); +var v = dsmeanpn.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanpn.ndarray( N, x, 2, 1 ); +var v = dsmeanpn.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -141,7 +132,7 @@ var v = dsmeanpn.ndarray( N, x, 2, 1 ); ## Notes - If `N <= 0`, both functions return `NaN`. -- Accumulated intermediate values are stored as double-precision floating-point numbers. +- Accumulated intermediate values are stored as double-precision floating-point numbers.
@@ -154,18 +145,12 @@ var v = dsmeanpn.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanpn = require( '@stdlib/stats/base/dsmeanpn' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanpn( x.length, x, 1 ); @@ -176,6 +161,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsmeanpn.h" +``` + +#### stdlib_strided_dsmeanpn( N, \*X, strideX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanpn( 4, x, 2 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsmeanpn( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsmeanpn_ndarray( N, \*X, strideX, offsetX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanpn_ndarray( 4, x, 2, 0 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsmeanpn_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsmeanpn.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dsmeanpn( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.js index dbd7345e9bd6..bfa72150ee19 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanpn = require( './../lib/dsmeanpn.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanpn = require( './../lib/dsmeanpn.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.native.js index 48bcd698263e..e43e166b47e3 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanpn = tryRequire( resolve( __dirname, './../lib/dsmeanpn.native.js' ) ) var opts = { 'skip': ( dsmeanpn instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.js index b389eb8ff4f6..222fcc8b0c17 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanpn = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanpn = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.native.js index 872ee1c618fd..3d2ae53c0061 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanpn = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsmeanpn instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/c/benchmark.length.c index 4f61ba9a5a43..58668a419185 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsmeanpn( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsmeanpn_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/repl.txt index ff00930bf3ed..e4b7fb60d7dc 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/repl.txt @@ -1,11 +1,11 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,8 +20,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -35,29 +35,26 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -68,10 +65,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/types/index.d.ts index 05bdcb04b8a2..3730bb968d5e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsmeanpn( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsmeanpn.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/c/example.c index 78f2d0e47eb4..eaa61e87ca5e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsmeanpn.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dsmeanpn( N, x, stride ); + double v = stdlib_strided_dsmeanpn( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/index.js index bf531337b342..107e3446d22a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanpn = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanpn( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/include.gypi b/lib/node_modules/@stdlib/stats/base/dsmeanpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. */ -double stdlib_strided_dsmeanpn( const int64_t N, const float *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsmeanpn)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. +*/ +double API_SUFFIX(stdlib_strided_dsmeanpn_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.js index 4ad062b26b4b..c3b98b92323f 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.js @@ -20,8 +20,8 @@ // MODULES // -var dssum = require( '@stdlib/blas/ext/base/dssum' ); -var dsapxsum = require( '@stdlib/blas/ext/base/dsapxsum' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -40,35 +40,19 @@ var dsapxsum = require( '@stdlib/blas/ext/base/dsapxsum' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanpn( N, x, 1 ); +* var v = dsmeanpn( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanpn( N, x, stride ) { - var mu; - var c; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - // Compute an estimate for the mean: - mu = dssum( N, x, stride ) / N; - - // Compute an error term: - c = dsapxsum( N, -mu, x, stride ) / N; - - return mu + c; +function dsmeanpn( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.native.js index acf084321502..309d8ecbc44a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/dsmeanpn.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanpn( N, x, 1 ); +* var v = dsmeanpn( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanpn( N, x, stride ) { - return addon( N, x, stride ); +function dsmeanpn( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/index.js index 8ada2c75159a..0a0be229cb8b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/index.js @@ -28,20 +28,17 @@ * var dsmeanpn = require( '@stdlib/stats/base/dsmeanpn' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanpn( N, x, 1 ); +* var v = dsmeanpn( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsmeanpn = require( '@stdlib/stats/base/dsmeanpn' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanpn.ndarray( N, x, 2, 1 ); +* var v = dsmeanpn.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.js index f12097ba300b..c30e19087800 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.js @@ -40,35 +40,33 @@ var dsapxsum = require( '@stdlib/blas/ext/base/dsapxsum' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanpn( N, x, 2, 1 ); +* var v = dsmeanpn( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanpn( N, x, stride, offset ) { +function dsmeanpn( N, x, strideX, offsetX ) { var mu; var c; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } // Compute an estimate for the mean: - mu = dssum( N, x, stride, offset ) / N; + mu = dssum( N, x, strideX, offsetX ) / N; // Compute an error term... - c = dsapxsum( N, -mu, x, stride, offset ) / N; + c = dsapxsum( N, -mu, x, strideX, offsetX ) / N; return mu + c; } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.native.js index fac3955f3c20..a1d9e67e7ea6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './dsmeanpn.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dsmeanpn.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanpn( N, x, 2, 1 ); +* var v = dsmeanpn( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanpn( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dsmeanpn( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/manifest.json b/lib/node_modules/@stdlib/stats/base/dsmeanpn/manifest.json index f443c27cf443..0ec3f61f8a39 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,78 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dsmeanpn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double", + "@stdlib/blas/ext/base/dssum", + "@stdlib/blas/ext/base/dsapxsum" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssum", + "@stdlib/blas/ext/base/dsapxsum" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssum", + "@stdlib/blas/ext/base/dsapxsum" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/dssum", "@stdlib/blas/ext/base/dsapxsum" ] diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/addon.c new file mode 100644 index 000000000000..a3b66a1c6e16 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/addon.c @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanpn.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/blas/base/shared.h" + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanpn)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanpn_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/addon.cpp deleted file mode 100644 index b82ed4f7652e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dsmeanpn { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dsmeanpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dsmeanpn( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsmeanpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dsmeanpn diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/dsmeanpn.c b/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/dsmeanpn.c deleted file mode 100644 index 5589d14727b3..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/dsmeanpn.c +++ /dev/null @@ -1,63 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanpn.h" -#include "stdlib/blas/ext/base/dssum.h" -#include "stdlib/blas/ext/base/dsapxsum.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. -* -* ## Method -* -* - This implementation uses a two-pass approach, as suggested by Neely (1966). -* -* ## References -* -* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). -* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsmeanpn( const int64_t N, const float *X, const int64_t stride ) { - double dN; - double mu; - double c; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - dN = (double)N; - - // Compute an estimate for the mean: - mu = stdlib_strided_dssum( N, X, stride ); - mu /= dN; - - // Compute an error term: - c = stdlib_strided_dsapxsum( N, -mu, X, stride ); - c /= dN; - - return mu + c; -} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/main.c b/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/main.c new file mode 100644 index 000000000000..7b890728979f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/src/main.c @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanpn.h" +#include "stdlib/blas/ext/base/dssum.h" +#include "stdlib/blas/ext/base/dsapxsum.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result. +* +* ## Method +* +* - This implementation uses a two-pass approach, as suggested by Neely (1966). +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanpn)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsmeanpn_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanpn_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + double dN; + double mu; + double c; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + dN = (double)N; + + // Compute an estimate for the mean: + mu = stdlib_strided_dssum_ndarray( N, X, strideX, offsetX ); + mu /= dN; + + // Compute an error term: + c = stdlib_strided_dsapxsum_ndarray( N, -mu, X, strideX, offsetX ); + c /= dN; + + return mu + c; +} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.js index f05932869e7f..821d3a86dfea 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanpn = require( './../lib/dsmeanpn.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, 2 ); + v = dsmeanpn( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, -2 ); + v = dsmeanpn( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanpn( N, x1, 2 ); + v = dsmeanpn( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.native.js index 1d85b95b81dd..a646afe4864d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.dsmeanpn.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, 2 ); + v = dsmeanpn( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, -2 ); + v = dsmeanpn( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanpn( N, x1, 2 ); + v = dsmeanpn( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.js index 904727e3230f..15a185685b72 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanpn = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, 2, 0 ); + v = dsmeanpn( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, -2, 6 ); + v = dsmeanpn( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, 2, 1 ); + v = dsmeanpn( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.native.js index f9417b6d3f21..4615f9ef7d27 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpn/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, 2, 0 ); + v = dsmeanpn( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, -2, 6 ); + v = dsmeanpn( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanpn( N, x, 2, 1 ); + v = dsmeanpn( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/README.md b/lib/node_modules/@stdlib/stats/base/dsmeanpw/README.md index 08cb8e5b71c2..60cd2a7552ce 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dsmeanpw = require( '@stdlib/stats/base/dsmeanpw' ); ``` -#### dsmeanpw( N, x, stride ) +#### dsmeanpw( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using pairwise summation with extended accumulation and returning an extended precision result. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanpw( N, x, 1 ); +var v = dsmeanpw( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanpw( N, x, 2 ); +var v = dsmeanpw( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsmeanpw( N, x1, 2 ); +var v = dsmeanpw( 4, x1, 2 ); // returns 1.25 ``` -#### dsmeanpw.ndarray( N, x, stride, offset ) +#### dsmeanpw.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanpw.ndarray( N, x, 1, 0 ); +var v = dsmeanpw.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanpw.ndarray( N, x, 2, 1 ); +var v = dsmeanpw.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -155,18 +146,12 @@ var v = dsmeanpw.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanpw = require( '@stdlib/stats/base/dsmeanpw' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanpw( x.length, x, 1 ); @@ -177,6 +162,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsmeanpw.h" +``` + +#### stdlib_strided_dsmeanpw( N, \*X, strideX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanpw( 4, x, 2 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsmeanpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsmeanpw_ndarray( N, \*X, strideX, offsetX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanpw_ndarray( 4, x, 2, 0 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsmeanpw_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsmeanpw.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dsmeanpw( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.js index 595f9577839d..33e6624bd039 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanpw = require( './../lib/dsmeanpw.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanpw = require( './../lib/dsmeanpw.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.native.js index 5599ec545bce..c006a32f1264 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanpw = tryRequire( resolve( __dirname, './../lib/dsmeanpw.native.js' ) ) var opts = { 'skip': ( dsmeanpw instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.js index 36c729b1439a..4f2cfe31dd0c 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanpw = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanpw = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.native.js index 30e5b9023736..261cf45f0562 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanpw = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsmeanpw instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/c/benchmark.length.c index 2d580bf22b88..eadbf381da6d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsmeanpw( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,39 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsmeanpw_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} /** * Main execution sequence. */ @@ -142,7 +176,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/repl.txt index 7f1540e314a6..2e84eb006a13 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/repl.txt @@ -1,11 +1,11 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,8 +20,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -35,28 +35,25 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -67,10 +64,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -87,8 +84,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/types/index.d.ts index 144e85d015d0..d0550d56a129 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsmeanpw.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/c/example.c index 5d71b2ea2480..f1af15a83567 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsmeanpw.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dsmeanpw( N, x, stride ); + double v = stdlib_strided_dsmeanpw( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/index.js index 1a12da96b044..12699b5238c6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanpw = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanpw( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/include.gypi b/lib/node_modules/@stdlib/stats/base/dsmeanpw/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. */ -double stdlib_strided_dsmeanpw( const int64_t N, const float *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsmeanpw)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result. +*/ +double API_SUFFIX(stdlib_strided_dsmeanpw_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.js index c777e92bfbdc..63f0f41dec90 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.js @@ -20,7 +20,8 @@ // MODULES // -var dssumpw = require( '@stdlib/blas/ext/base/dssumpw' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,26 +31,19 @@ var dssumpw = require( '@stdlib/blas/ext/base/dssumpw' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanpw( N, x, 1 ); +* var v = dsmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanpw( N, x, stride ) { - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - return dssumpw( N, x, stride ) / N; +function dsmeanpw( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.native.js index a6a00fa12e23..5ad94060c750 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/dsmeanpw.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanpw( N, x, 1 ); +* var v = dsmeanpw( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanpw( N, x, stride ) { - return addon( N, x, stride ); +function dsmeanpw( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/index.js index cee16d6f7c5d..86fe54eb58a6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/index.js @@ -28,20 +28,17 @@ * var dsmeanpw = require( '@stdlib/stats/base/dsmeanpw' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanpw( N, x, 1 ); +* var v = dsmeanpw( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsmeanpw = require( '@stdlib/stats/base/dsmeanpw' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanpw.ndarray( N, x, 2, 1 ); +* var v = dsmeanpw.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.js index 9402aa032639..668c099fd327 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.js @@ -30,28 +30,26 @@ var dssumpw = require( '@stdlib/blas/ext/base/dssumpw' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanpw( N, x, 2, 1 ); +* var v = dsmeanpw( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanpw( N, x, stride, offset ) { +function dsmeanpw( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return dssumpw( N, x, stride, offset ) / N; + return dssumpw( N, x, strideX, offsetX ) / N; } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.native.js index 4a1dc9f50804..a4cd2a3f8125 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './dsmeanpw.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dsmeanpw.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanpw( N, x, 2, 1 ); +* var v = dsmeanpw( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanpw( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dsmeanpw( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/manifest.json b/lib/node_modules/@stdlib/stats/base/dsmeanpw/manifest.json index 596460860f1e..ff2f26c0a708 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,18 +27,76 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dsmeanpw.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumpw", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumpw" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumpw" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/blas/ext/base/dssum" + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/dssumpw" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/addon.c new file mode 100644 index 000000000000..b7a0bbf9e160 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/addon.c @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanpw.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/blas/base/shared.h" + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanpw)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanpw_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/addon.cpp deleted file mode 100644 index ab37491b4668..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanpw.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dsmeanpw { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dsmeanpw( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dsmeanpw( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsmeanpw, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dsmeanpw diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/dsmeanpw.c b/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/dsmeanpw.c deleted file mode 100644 index 679904b23e70..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/dsmeanpw.c +++ /dev/null @@ -1,39 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanpw.h" -#include "stdlib/blas/ext/base/dssum.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsmeanpw( const int64_t N, const float *X, const int64_t stride ) { - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - return stdlib_strided_dssum( N, X, stride ) / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/main.c b/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/main.c new file mode 100644 index 000000000000..277c63176be2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/src/main.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanpw.h" +#include "stdlib/blas/ext/base/dssumpw.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanpw)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsmeanpw_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and alternative indexing semantics and returning an extended precision result. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanpw_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return stdlib_strided_dssumpw_ndarray( N, X, strideX, offsetX ) / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.js index d6afb34e9ba3..77de914f2d98 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanpw = require( './../lib/dsmeanpw.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, 2 ); + v = dsmeanpw( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, -2 ); + v = dsmeanpw( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanpw( N, x1, 2 ); + v = dsmeanpw( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.native.js index 39896d88a42a..0876072e69c8 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.dsmeanpw.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, 2 ); + v = dsmeanpw( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, -2 ); + v = dsmeanpw( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanpw( N, x1, 2 ); + v = dsmeanpw( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.js index 50f5a9d634e0..c4b6a28bb0dd 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanpw = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, 2, 0 ); + v = dsmeanpw( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, -2, 6 ); + v = dsmeanpw( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, 2, 1 ); + v = dsmeanpw( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.native.js index 35df641f4ce5..b01b351ccb9b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanpw/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, 2, 0 ); + v = dsmeanpw( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, -2, 6 ); + v = dsmeanpw( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanpw( N, x, 2, 1 ); + v = dsmeanpw( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dsmeanwd/README.md index 977729836d8f..ae43d8291b6d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dsmeanwd = require( '@stdlib/stats/base/dsmeanwd' ); ``` -#### dsmeanwd( N, x, stride ) +#### dsmeanwd( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using Welford's algorithm with extended accumulation and returning an extended precision result. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanwd( N, x, 1 ); +var v = dsmeanwd( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanwd( N, x, 2 ); +var v = dsmeanwd( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsmeanwd( N, x1, 2 ); +var v = dsmeanwd( 4, x1, 2 ); // returns 1.25 ``` -#### dsmeanwd.ndarray( N, x, stride, offset ) +#### dsmeanwd.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. @@ -109,9 +103,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dsmeanwd.ndarray( N, x, 1, 0 ); +var v = dsmeanwd.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` @@ -123,12 +116,10 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dsmeanwd.ndarray( N, x, 2, 1 ); +var v = dsmeanwd.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -141,7 +132,7 @@ var v = dsmeanwd.ndarray( N, x, 2, 1 ); ## Notes - If `N <= 0`, both functions return `NaN`. -- Accumulated intermediate values are stored as double-precision floating-point numbers. +- Accumulated intermediate values are stored as double-precision floating-point numbers.
@@ -154,18 +145,12 @@ var v = dsmeanwd.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanwd = require( '@stdlib/stats/base/dsmeanwd' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanwd( x.length, x, 1 ); @@ -176,6 +161,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsmeanwd.h" +``` + +#### stdlib_strided_dsmeanwd( N, \*X, strideX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanwd( 4, x, 2 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsmeanwd( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsmeanwd_ndarray( N, \*X, strideX, offsetX ) + +Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + +double v = stdlib_strided_dsmeanwd_ndarray( 4, x, 2, 0 ); +// returns 4.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsmeanwd_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsmeanwd.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dsmeanwd( N, x, strideX ); + + // Print the result: + printf( "mean: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.js index d5e6790bd110..3fcdbf882bc4 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanwd = require( './../lib/dsmeanwd.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanwd = require( './../lib/dsmeanwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.native.js index 479f0260c0f1..440108e0f4f7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanwd = tryRequire( resolve( __dirname, './../lib/dsmeanwd.native.js' ) ) var opts = { 'skip': ( dsmeanwd instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.js index b36bab63602a..86ef4e86f35a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsmeanwd = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dsmeanwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.native.js index aad2a69676e3..cf0105580099 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dsmeanwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dsmeanwd instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/c/benchmark.length.c index 5e5bf17bf223..3f480da98e49 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsmeanwd( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsmeanwd_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/repl.txt index c849cc2c9c1f..97591d58be30 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/repl.txt @@ -1,10 +1,11 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. - The `N` and `stride` parameters determine which elements in `x` are accessed + The `N` and stride parameters determine which elements in the strided array + are accessed. at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -20,8 +21,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -35,28 +36,25 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -67,10 +65,10 @@ x: Float32Array Input array. - stride: integer + strideX: integer Index increment. - offset: integer + offsetX: integer Starting index. Returns @@ -87,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/types/index.d.ts index 0f5d86942a1f..df5079cad82c 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = dsmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsmeanwd.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/c/example.c index c090beb38721..59dcd28b41cf 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsmeanwd.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dsmeanwd( N, x, stride ); + double v = stdlib_strided_dsmeanwd( N, x, strideX ); // Print the result: printf( "mean: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/index.js index 0f66c7a3c6bb..3ea2c89b12e7 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dsmeanwd = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = dsmeanwd( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/include.gypi b/lib/node_modules/@stdlib/stats/base/dsmeanwd/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' - +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. */ @@ -29,9 +28,14 @@ extern "C" { #endif /** -* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. +* Computes the arithmetic mean of a single-precision floating-point strided array `x ` using Welford's algorithm with extended accumulation and returning an extended precision result. +*/ +double API_SUFFIX(stdlib_strided_dsmeanwd)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array `x` using Welford's algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. */ -double stdlib_strided_dsmeanwd( const int64_t N, const float *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsmeanwd_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.js index 145f4703d966..371fa09b9999 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -43,43 +49,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanwd( N, x, 1 ); +* var v = dsmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanwd( N, x, stride ) { - var mu; - var ix; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - n += 1; - mu += ( x[ix]-mu ) / n; - ix += stride; - } - return mu; +function dsmeanwd( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.native.js index 3098c6c9398d..a5021176773e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/dsmeanwd.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanwd( N, x, 1 ); +* var v = dsmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dsmeanwd( N, x, stride ) { - return addon( N, x, stride ); +function dsmeanwd( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/index.js index 296a10b9071c..11cc615aad26 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/index.js @@ -28,20 +28,17 @@ * var dsmeanwd = require( '@stdlib/stats/base/dsmeanwd' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dsmeanwd( N, x, 1 ); +* var v = dsmeanwd( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsmeanwd = require( '@stdlib/stats/base/dsmeanwd' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanwd.ndarray( N, x, 2, 1 ); +* var v = dsmeanwd.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.js index 703769242ff2..d7451da49fb2 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.js @@ -43,21 +43,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanwd( N, x, 2, 1 ); +* var v = dsmeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanwd( N, x, stride, offset ) { +function dsmeanwd( N, x, strideX, offsetX ) { var mu; var ix; var n; @@ -66,16 +64,16 @@ function dsmeanwd( N, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; mu = 0.0; n = 0; for ( i = 0; i < N; i++ ) { n += 1; mu += ( x[ix]-mu ) / n; - ix += stride; + ix += strideX; } return mu; } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.native.js index 17fe07bab008..b20e79af3b75 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './dsmeanwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dsmeanwd.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dsmeanwd( N, x, 2, 1 ); +* var v = dsmeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function dsmeanwd( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dsmeanwd( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dsmeanwd/manifest.json index 6752f317467e..7a0fdb1d890b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,73 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/dsmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/addon.c new file mode 100644 index 000000000000..c36eb5b7ea34 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/addon.c @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanwd.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/blas/base/shared.h" + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanwd)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsmeanwd_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/addon.cpp deleted file mode 100644 index 964fe15d4b98..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanwd.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_dsmeanwd { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_dsmeanwd( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, stdlib_strided_dsmeanwd( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dsmeanwd, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_dsmeanwd diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/dsmeanwd.c b/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/dsmeanwd.c deleted file mode 100644 index 128c683c69b9..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/dsmeanwd.c +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dsmeanwd.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. -* -* ## Method -* -* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows -* -* ```tex -* \begin{align*} -* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ -* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ -* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ -* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) -* \end{align*} -* ``` -* -* ## References -* -* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). -* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dsmeanwd( const int64_t N, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - int64_t n; - double mu; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - n += 1; - mu += ( (double)X[ix]-mu ) / (double)n; - ix += stride; - } - return mu; -} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/main.c b/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/main.c new file mode 100644 index 000000000000..37aba94b00ef --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/src/main.c @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dsmeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and returning an extended precision result. +* +* ## Method +* +* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows +* +* ```tex +* \begin{align*} +* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ +* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ +* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ +* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) +* \end{align*} +* ``` +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanwd)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsmeanwd_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsmeanwd_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + CBLAS_INT n; + double mu; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + ix = offsetX; + mu = 0.0; + n = 0; + for ( i = 0; i < N; i++ ) { + n += 1; + mu += ( (double)X[ix]-mu ) / (double)n; + ix += strideX; + } + return mu; +} diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.js index de59955668d4..fa8bc3d7051d 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanwd = require( './../lib/dsmeanwd.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, 2 ); + v = dsmeanwd( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, -2 ); + v = dsmeanwd( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanwd( N, x1, 2 ); + v = dsmeanwd( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.native.js index 7794cc741c0a..db93db657a16 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.dsmeanwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, 2 ); + v = dsmeanwd( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, -2 ); + v = dsmeanwd( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsmeanwd( N, x1, 2 ); + v = dsmeanwd( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.js index fe5c62427148..dd9acd1c58b3 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsmeanwd = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, 2, 0 ); + v = dsmeanwd( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, -2, 6 ); + v = dsmeanwd( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, 2, 1 ); + v = dsmeanwd( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.native.js index 35f0294e3f4a..41faa64f5f08 100644 --- a/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsmeanwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, 2, 0 ); + v = dsmeanwd( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, -2, 6 ); + v = dsmeanwd( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dsmeanwd( N, x, 2, 1 ); + v = dsmeanwd( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/README.md b/lib/node_modules/@stdlib/stats/base/dstdevch/README.md index 0e57659268a2..f1ab60fa9e9e 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dstdevch = require( '@stdlib/stats/base/dstdevch' ); ``` -#### dstdevch( N, correction, x, stride ) +#### dstdevch( N, correction, x, strideX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -106,9 +106,8 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevch( N, 1, x, 1 ); +var v = dstdevch( x.length, 1, x, 1 ); // returns ~2.0817 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevch( N, 1, x, 2 ); +var v = dstdevch( 4, 1, x, 2 ); // returns 2.5 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dstdevch( N, 1, x1, 2 ); +var v = dstdevch( 4, 1, x1, 2 ); // returns 2.5 ``` -#### dstdevch.ndarray( N, correction, x, stride, offset ) +#### dstdevch.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevch.ndarray( N, 1, x, 1, 0 ); +var v = dstdevch.ndarray( x.length, 1, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevch.ndarray( N, 1, x, 2, 1 ); +var v = dstdevch.ndarray( 4, 1, x, 2, 1 ); // returns 2.5 ``` @@ -203,18 +194,12 @@ var v = dstdevch.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevch = require( '@stdlib/stats/base/dstdevch' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dstdevch( x.length, 1, x, 1 ); @@ -225,6 +210,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dstdevch.h" +``` + +#### stdlib_strided_dstdevch( N, correction, \*X, strideX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevch( 3, 1.0, x, 1 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dstdevch( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dstdevch_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevch_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dstdevch_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dstdevch.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dstdevch( N, 1.0, x, strideX ); + + // Print the result: + printf( "sample standard deviation: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.js index 7f1e67c4c979..d2bdd4788c62 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevch = require( './../lib/dstdevch.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevch = require( './../lib/dstdevch.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.native.js index 9d2e93215336..127416ef3e7c 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevch = tryRequire( resolve( __dirname, './../lib/dstdevch.native.js' ) ) var opts = { 'skip': ( dstdevch instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.js index 38aacc50aa49..98badf9513c2 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevch = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevch = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.native.js index 07b389c92adc..48ede1027f09 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevch = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dstdevch instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/c/benchmark.length.c index cdf36bf0d604..d6f1bf4f4c19 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dstdevch( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dstdevch_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dstdevch/docs/repl.txt index e537c6751d74..1583cbcd801f 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~2.0817 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dstdevch/docs/types/index.d.ts index 302bba706a6a..3b438b4a7703 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dstdevch.ndarray( x.length, 1, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dstdevch/examples/c/example.c index 5865ab94f81d..458d30e10f7e 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dstdevch.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard deviation: - double v = stdlib_strided_dstdevch( N, 1, x, stride ); + double v = stdlib_strided_dstdevch( N, 1.0, x, strideX ); // Print the result: printf( "sample standard deviation: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/examples/index.js b/lib/node_modules/@stdlib/stats/base/dstdevch/examples/index.js index 8f38cf5b1421..726cdb24d17a 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevch = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dstdevch( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/include/stdlib/stats/base/dstdevch.h b/lib/node_modules/@stdlib/stats/base/dstdevch/include/stdlib/stats/base/dstdevch.h index 861793409d2e..2c4d209f7097 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/include/stdlib/stats/base/dstdevch.h +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/include/stdlib/stats/base/dstdevch.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSTDEVCH_H #define STDLIB_STATS_BASE_DSTDEVCH_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. */ -double stdlib_strided_dstdevch( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dstdevch)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dstdevch_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.js b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.js index 7fe2c32a1327..d23b6c6850bc 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.js @@ -20,8 +20,8 @@ // MODULES // -var dvariancech = require( '@stdlib/stats/base/dvariancech' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevch( N, 1, x, 1 ); +* var v = dstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function dstdevch( N, correction, x, stride ) { - return sqrt( dvariancech( N, correction, x, stride ) ); +function dstdevch( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.native.js b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.native.js index 47f9d4c0fd41..ec883b34b822 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/dstdevch.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevch( N, 1, x, 1 ); +* var v = dstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function dstdevch( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dstdevch( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/index.js b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/index.js index 781d466707c9..8b40a05694cb 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/index.js @@ -28,20 +28,17 @@ * var dstdevch = require( '@stdlib/stats/base/dstdevch' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevch( N, 1, x, 1 ); +* var v = dstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dstdevch = require( '@stdlib/stats/base/dstdevch' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevch.ndarray( N, 1, x, 2, 1 ); +* var v = dstdevch.ndarray( 4, 1, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.js index f9de92884823..92f5a9e5294e 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.js @@ -32,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevch( N, 1, x, 2, 1 ); +* var v = dstdevch( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function dstdevch( N, correction, x, stride, offset ) { - return sqrt( dvariancech( N, correction, x, stride, offset ) ); +function dstdevch( N, correction, x, strideX, offsetX ) { + return sqrt( dvariancech( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.native.js index 5919db1ac482..560ff706d9ab 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dstdevch.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dstdevch.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevch( N, 1, x, 2, 1 ); +* var v = dstdevch( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function dstdevch( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dstdevch( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/manifest.json b/lib/node_modules/@stdlib/stats/base/dstdevch/manifest.json index 2309a3ad0e12..a12f1212f754 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -25,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dstdevch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancech", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -47,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dstdevch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancech" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dstdevch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvariancech" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancech" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/src/addon.c b/lib/node_modules/@stdlib/stats/base/dstdevch/src/addon.c index 5e25745d6723..712762ae5aa8 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dstdevch.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dstdevch( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevch)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevch_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/src/dstdevch.c b/lib/node_modules/@stdlib/stats/base/dstdevch/src/dstdevch.c deleted file mode 100644 index e7d426b43594..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/src/dstdevch.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dstdevch.h" -#include "stdlib/stats/base/dvariancech.h" -#include -#include - -/** -* Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dstdevch( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvariancech( N, correction, X, stride ) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/src/main.c b/lib/node_modules/@stdlib/stats/base/dstdevch/src/main.c new file mode 100644 index 000000000000..2b5e910cfdf9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dstdevch.h" +#include "stdlib/stats/base/dvariancech.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevch)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dstdevch_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevch_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvariancech_ndarray)( N, correction, X, strideX, offsetX ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.js b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.js index 4c7fe3c5833e..aad5970bd653 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, 2 ); + v = dstdevch( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, -2 ); + v = dstdevch( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevch( N, 1, x1, 2 ); + v = dstdevch( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.native.js b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.native.js index 22ecbc1f3245..93d4cfddcb20 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.dstdevch.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, 2 ); + v = dstdevch( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, -2 ); + v = dstdevch( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevch( N, 1, x1, 2 ); + v = dstdevch( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.js index 4006c9ae768f..effab8f76e43 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, 2, 0 ); + v = dstdevch( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, -2, 6 ); + v = dstdevch( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, 2, 1 ); + v = dstdevch( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.native.js index c6c34dea6fa0..f8755294a5c4 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevch/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, 2, 0 ); + v = dstdevch( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, -2, 6 ); + v = dstdevch( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevch( N, 1, x, 2, 1 ); + v = dstdevch( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/README.md b/lib/node_modules/@stdlib/stats/base/dstdevtk/README.md index bdaf224d6b67..9674a117887d 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dstdevtk = require( '@stdlib/stats/base/dstdevtk' ); ``` -#### dstdevtk( N, correction, x, stride ) +#### dstdevtk( N, correction, x, strideX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array `x` using a one-pass textbook algorithm. @@ -106,9 +106,8 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevtk( N, 1, x, 1 ); +var v = dstdevtk( x.length, 1.0, x, 1 ); // returns ~2.0817 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevtk( N, 1, x, 2 ); +var v = dstdevtk( 4, 1.0, x, 2 ); // returns 2.5 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dstdevtk( N, 1, x1, 2 ); +var v = dstdevtk( 4, 1.0, x1, 2 ); // returns 2.5 ``` -#### dstdevtk.ndarray( N, correction, x, stride, offset ) +#### dstdevtk.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevtk.ndarray( N, 1, x, 1, 0 ); +var v = dstdevtk.ndarray( x.length, 1.0, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevtk.ndarray( N, 1, x, 2, 1 ); +var v = dstdevtk.ndarray( 4, 1.0, x, 2, 1 ); // returns 2.5 ``` @@ -203,21 +194,15 @@ var v = dstdevtk.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevtk = require( '@stdlib/stats/base/dstdevtk' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); -var v = dstdevtk( x.length, 1, x, 1 ); +var v = dstdevtk( x.length, 1.0, x, 1 ); console.log( v ); ``` @@ -225,6 +210,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dstdevtk.h" +``` + +#### stdlib_strided_dstdevtk( N, correction, \*X, strideX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass textbook algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevtk( 3, 1.0, x, 1 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dstdevtk( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dstdevtk_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevtk_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dstdevtk_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dstdevtk.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dstdevtk( N, 1.0, x, strideX ); + + // Print the result: + printf( "sample standard deviation: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.js index 6fe71c1a93c7..1537fb9d90a2 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevtk = require( './../lib/dstdevtk.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevtk = require( './../lib/dstdevtk.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.native.js index 84ce9e97e91b..0ea098f180ee 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevtk = tryRequire( resolve( __dirname, './../lib/dstdevtk.native.js' ) ) var opts = { 'skip': ( dstdevtk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.js index f679e9ed9392..578f20f050a0 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevtk = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevtk = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.native.js index 239a8eb406c3..401e767eeffe 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevtk = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dstdevtk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/c/benchmark.length.c index 58399664a2c4..b7f25c8c6fbc 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dstdevtk( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dstdevtk_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/repl.txt index 52340c74496a..eb38d0514907 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~2.0817 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/types/index.d.ts index d8ac926b6c38..4921da5da270 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dstdevtk.ndarray( x.length, 1, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/c/example.c index 7514c7ef5be7..c00b0bc80a19 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dstdevtk.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard deviation: - double v = stdlib_strided_dstdevtk( N, 1, x, stride ); + double v = stdlib_strided_dstdevtk( N, 1.0, x, strideX ); // Print the result: printf( "sample standard deviation: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/index.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/index.js index af84c2fd5590..0589b0b3b4c5 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevtk = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dstdevtk( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/include/stdlib/stats/base/dstdevtk.h b/lib/node_modules/@stdlib/stats/base/dstdevtk/include/stdlib/stats/base/dstdevtk.h index 87328e14cb60..93cd0af51dcd 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/include/stdlib/stats/base/dstdevtk.h +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/include/stdlib/stats/base/dstdevtk.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSTDEVTK_H #define STDLIB_STATS_BASE_DSTDEVTK_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. */ -double stdlib_strided_dstdevtk( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dstdevtk)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dstdevtk_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.js index 683a54ba3b01..24e51b7d61b2 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.js @@ -20,8 +20,8 @@ // MODULES // -var dvariancetk = require( '@stdlib/stats/base/dvariancetk' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevtk( N, 1, x, 1 ); +* var v = dstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function dstdevtk( N, correction, x, stride ) { - return sqrt( dvariancetk( N, correction, x, stride ) ); +function dstdevtk( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.native.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.native.js index 3ac98d1002df..5f1d4a0c505a 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/dstdevtk.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevtk( N, 1, x, 1 ); +* var v = dstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function dstdevtk( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dstdevtk( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/index.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/index.js index 2ab6e47005fa..52f47c55db68 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/index.js @@ -28,20 +28,17 @@ * var dstdevtk = require( '@stdlib/stats/base/dstdevtk' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevtk( N, 1, x, 1 ); +* var v = dstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dstdevtk = require( '@stdlib/stats/base/dstdevtk' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevtk.ndarray( N, 1, x, 2, 1 ); +* var v = dstdevtk.ndarray( 4, 1, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.js index 7e74a8c4ab43..a1b2249fa093 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.js @@ -32,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevtk( N, 1, x, 2, 1 ); +* var v = dstdevtk( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function dstdevtk( N, correction, x, stride, offset ) { - return sqrt( dvariancetk( N, correction, x, stride, offset ) ); +function dstdevtk( N, correction, x, strideX, offsetX ) { + return sqrt( dvariancetk( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.native.js index c3cc13d1ecc6..a1158781df49 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dstdevtk.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dstdevtk.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevtk( N, 1, x, 2, 1 ); +* var v = dstdevtk( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function dstdevtk( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dstdevtk( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/manifest.json b/lib/node_modules/@stdlib/stats/base/dstdevtk/manifest.json index 500141185ed2..a816ad11dae6 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dstdevtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancetk", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -49,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dstdevtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancetk" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dstdevtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvariancetk" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancetk" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/dstdevtk/src/addon.c index 80373bd061f2..a0dacade0986 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dstdevtk.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dstdevtk( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevtk)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevtk_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/src/dstdevtk.c b/lib/node_modules/@stdlib/stats/base/dstdevtk/src/dstdevtk.c deleted file mode 100644 index a8a1198e3ca8..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/src/dstdevtk.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dstdevtk.h" -#include "stdlib/stats/base/dvariancetk.h" -#include -#include - -/** -* Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dstdevtk( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvariancetk( N, correction, X, stride ) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/src/main.c b/lib/node_modules/@stdlib/stats/base/dstdevtk/src/main.c new file mode 100644 index 000000000000..6d56af603e80 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dstdevtk.h" +#include "stdlib/stats/base/dvariancetk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevtk)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dstdevtk_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevtk_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvariancetk_ndarray)( N, correction, X, strideX, offsetX ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.js index 0cd5671af88a..8cb3def2d21a 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, 2 ); + v = dstdevtk( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, -2 ); + v = dstdevtk( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevtk( N, 1, x1, 2 ); + v = dstdevtk( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.native.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.native.js index 1353729ed58a..0835d85879a0 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.dstdevtk.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, 2 ); + v = dstdevtk( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, -2 ); + v = dstdevtk( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevtk( N, 1, x1, 2 ); + v = dstdevtk( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.js index c8441321399c..073d6f5b66c0 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, 2, 0 ); + v = dstdevtk( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, -2, 6 ); + v = dstdevtk( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, 2, 1 ); + v = dstdevtk( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.native.js index c9548a4c20dd..fb8c41d28428 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevtk/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, 2, 0 ); + v = dstdevtk( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, -2, 6 ); + v = dstdevtk( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevtk( N, 1, x, 2, 1 ); + v = dstdevtk( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/README.md b/lib/node_modules/@stdlib/stats/base/dstdevwd/README.md index 6c59790179e0..dc3f86f433f2 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dstdevwd = require( '@stdlib/stats/base/dstdevwd' ); ``` -#### dstdevwd( N, correction, x, stride ) +#### dstdevwd( N, correction, x, strideX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array `x` using Welford's algorithm. @@ -106,9 +106,8 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevwd( N, 1, x, 1 ); +var v = dstdevwd( x.length, 1.0, x, 1 ); // returns ~2.0817 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevwd( N, 1, x, 2 ); +var v = dstdevwd( 4, 1.0, x, 2 ); // returns 2.5 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dstdevwd( N, 1, x1, 2 ); +var v = dstdevwd( 4, 1.0, x1, 2 ); // returns 2.5 ``` -#### dstdevwd.ndarray( N, correction, x, stride, offset ) +#### dstdevwd.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevwd.ndarray( N, 1, x, 1, 0 ); +var v = dstdevwd.ndarray( x.length, 1.0, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevwd.ndarray( N, 1, x, 2, 1 ); +var v = dstdevwd.ndarray( 4, 1.0, x, 2, 1 ); // returns 2.5 ``` @@ -202,21 +193,15 @@ var v = dstdevwd.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevwd = require( '@stdlib/stats/base/dstdevwd' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); -var v = dstdevwd( x.length, 1, x, 1 ); +var v = dstdevwd( x.length, 1.0, x, 1 ); console.log( v ); ``` @@ -224,6 +209,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dstdevwd.h" +``` + +#### stdlib_strided_dstdevwd( N, correction, \*X, strideX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using Welford's algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevwd( 3, 1.0, x, 1 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dstdevwd( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dstdevwd_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevwd_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dstdevwd_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dstdevwd.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dstdevwd( N, 1.0, x, strideX ); + + // Print the result: + printf( "sample standard deviation: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.js index b0ba9be596fd..4b1a0c2b7d9a 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevwd = require( './../lib/dstdevwd.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevwd = require( './../lib/dstdevwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.native.js index 8c4d2a86dbe3..06428bdfd047 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevwd = tryRequire( resolve( __dirname, './../lib/dstdevwd.native.js' ) ) var opts = { 'skip': ( dstdevwd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.js index a2600eb1f686..b05e6cef288e 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevwd = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.native.js index 973fa98eab12..57d4f25c6eeb 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dstdevwd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/c/benchmark.length.c index 7882be6e4f92..e5ef9f8d8df8 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dstdevwd( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dstdevwd_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/repl.txt index af68a536b60e..695d7e789a92 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~2.0817 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -89,10 +86,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -109,8 +106,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/types/index.d.ts index 52d9d850246a..1389e3727265 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dstdevwd( x.length, 1, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dstdevwd.ndarray( x.length, 1, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/c/example.c index 54b09978a102..ad16d279f6a0 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dstdevwd.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard deviation: - double v = stdlib_strided_dstdevwd( N, 1, x, stride ); + double v = stdlib_strided_dstdevwd( N, 1.0, x, strideX ); // Print the result: printf( "sample standard deviation: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/index.js index f330b75d4ca0..141fc67cb50c 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevwd = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dstdevwd( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/include/stdlib/stats/base/dstdevwd.h b/lib/node_modules/@stdlib/stats/base/dstdevwd/include/stdlib/stats/base/dstdevwd.h index 42fb72ba995d..e9f5103f32cc 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/include/stdlib/stats/base/dstdevwd.h +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/include/stdlib/stats/base/dstdevwd.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSTDEVWD_H #define STDLIB_STATS_BASE_DSTDEVWD_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm. */ -double stdlib_strided_dstdevwd( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dstdevwd)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dstdevwd_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.js index e35105a75d42..fc3c36da00dd 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.js @@ -20,8 +20,8 @@ // MODULES // -var dvariancewd = require( '@stdlib/stats/base/dvariancewd' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -37,20 +37,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevwd( N, 1, x, 1 ); +* var v = dstdevwd( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function dstdevwd( N, correction, x, stride ) { - return sqrt( dvariancewd( N, correction, x, stride ) ); +function dstdevwd( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.native.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.native.js index a97b4a9a8977..3fbaadb3fdef 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/dstdevwd.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevwd( N, 1, x, 1 ); +* var v = dstdevwd( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function dstdevwd( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dstdevwd( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/index.js index a6d02522d47d..4b1d6acae446 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/index.js @@ -28,20 +28,17 @@ * var dstdevwd = require( '@stdlib/stats/base/dstdevwd' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevwd( N, 1, x, 1 ); +* var v = dstdevwd( x.length, 1, x, 1 ); * // returns ~2.0817 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dstdevwd = require( '@stdlib/stats/base/dstdevwd' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevwd.ndarray( N, 1, x, 2, 1 ); +* var v = dstdevwd.ndarray( 4, 1, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.js index 210be95f0056..88faaefddfe8 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.js @@ -37,22 +37,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevwd( N, 1, x, 2, 1 ); +* var v = dstdevwd( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function dstdevwd( N, correction, x, stride, offset ) { - return sqrt( dvariancewd( N, correction, x, stride, offset ) ); +function dstdevwd( N, correction, x, strideX, offsetX ) { + return sqrt( dvariancewd( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.native.js index 0e1fc3bf65e1..5b7a0aeadd4f 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dstdevwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dstdevwd.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevwd( N, 1, x, 2, 1 ); +* var v = dstdevwd( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function dstdevwd( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dstdevwd( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dstdevwd/manifest.json index 90c5b8331e71..dd5060f5aa7d 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dstdevwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancewd", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -49,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dstdevwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancewd" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dstdevwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvariancewd" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvariancewd" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dstdevwd/src/addon.c index 1fe9439fae64..c88c66fa8506 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dstdevwd.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dstdevwd( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevwd)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevwd_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/src/dstdevwd.c b/lib/node_modules/@stdlib/stats/base/dstdevwd/src/dstdevwd.c deleted file mode 100644 index b2d7d4316a84..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/src/dstdevwd.c +++ /dev/null @@ -1,40 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dstdevwd.h" -#include "stdlib/stats/base/dvariancewd.h" -#include -#include - -/** -* Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm. -* -* ## References -* -* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). -* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dstdevwd( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvariancewd( N, correction, X, stride ) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/src/main.c b/lib/node_modules/@stdlib/stats/base/dstdevwd/src/main.c new file mode 100644 index 000000000000..382c44ed9635 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/src/main.c @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dstdevwd.h" +#include "stdlib/stats/base/dvariancewd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm. +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevwd)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dstdevwd_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard deviation of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevwd_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvariancewd_ndarray)( N, correction, X, strideX, offsetX ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.js index 565f285c0aec..cf8823ea639b 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, 2 ); + v = dstdevwd( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, -2 ); + v = dstdevwd( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevwd( N, 1, x1, 2 ); + v = dstdevwd( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.native.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.native.js index aba05072952c..a2724e98d2a2 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.dstdevwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, 2 ); + v = dstdevwd( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, -2 ); + v = dstdevwd( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevwd( N, 1, x1, 2 ); + v = dstdevwd( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.js index 85096d8abc34..1ce2ac028961 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, 2, 0 ); + v = dstdevwd( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, -2, 6 ); + v = dstdevwd( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, 2, 1 ); + v = dstdevwd( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.native.js index 0aa92ca6b9d5..15feb9a9653b 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, 2, 0 ); + v = dstdevwd( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, -2, 6 ); + v = dstdevwd( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevwd( N, 1, x, 2, 1 ); + v = dstdevwd( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/README.md b/lib/node_modules/@stdlib/stats/base/dstdevyc/README.md index 768af0905646..6b927257be01 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/README.md +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dstdevyc = require( '@stdlib/stats/base/dstdevyc' ); ``` -#### dstdevyc( N, correction, x, stride ) +#### dstdevyc( N, correction, x, strideX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array `x` using a one-pass algorithm proposed by Youngs and Cramer. @@ -106,9 +106,8 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevyc( N, 1, x, 1 ); +var v = dstdevyc( x.length, 1.0, x, 1 ); // returns ~2.0817 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevyc( N, 1, x, 2 ); +var v = dstdevyc( 4, 1.0, x, 2 ); // returns 2.5 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dstdevyc( N, 1, x1, 2 ); +var v = dstdevyc( 4, 1.0, x1, 2 ); // returns 2.5 ``` -#### dstdevyc.ndarray( N, correction, x, stride, offset ) +#### dstdevyc.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [standard deviation][standard-deviation] of a double-precision floa var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dstdevyc.ndarray( N, 1, x, 1, 0 ); +var v = dstdevyc.ndarray( x.length, 1.0, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dstdevyc.ndarray( N, 1, x, 2, 1 ); +var v = dstdevyc.ndarray( 4, 1.0, x, 2, 1 ); // returns 2.5 ``` @@ -202,21 +193,15 @@ var v = dstdevyc.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevyc = require( '@stdlib/stats/base/dstdevyc' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); -var v = dstdevyc( x.length, 1, x, 1 ); +var v = dstdevyc( x.length, 1.0, x, 1 ); console.log( v ); ``` @@ -224,6 +209,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dstdevyc.h" +``` + +#### stdlib_strided_dstdevyc( N, correction, \*X, strideX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevyc( 3, 1.0, x, 1 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dstdevyc( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dstdevyc_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard deviation][standard-deviation] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dstdevyc_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~2.0817 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dstdevyc_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dstdevyc.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dstdevyc( N, 1.0, x, strideX ); + + // Print the result: + printf( "sample standard deviation: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.js index c7ab1cac4426..ee12c4736465 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevyc = require( './../lib/dstdevyc.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevyc = require( './../lib/dstdevyc.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { @@ -54,7 +54,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.native.js index b9d6ccef2cf7..3fa5f9ea3860 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevyc = tryRequire( resolve( __dirname, './../lib/dstdevyc.native.js' ) ) var opts = { 'skip': ( dstdevyc instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { @@ -63,7 +59,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.js index 7dfbb13b5579..4f8c661eb5ce 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dstdevyc = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dstdevyc = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { @@ -54,7 +54,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.native.js index e820e8a25e9e..e95104f7f2e9 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dstdevyc = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dstdevyc instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { @@ -63,7 +59,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/c/benchmark.length.c index 1ee95938acd6..6552916b0bf8 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dstdevyc( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dstdevyc_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/repl.txt index d7dba08e1253..9252f8467087 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -43,25 +43,22 @@ -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); - > {{alias}}( x.length, 1, x, 1 ) + > {{alias}}( x.length, 1.0, x, 1 ) ~2.0817 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1.0, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1.0, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -105,13 +102,12 @@ -------- // Standard Usage: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); - > {{alias}}.ndarray( x.length, 1, x, 1, 0 ) + > {{alias}}.ndarray( x.length, 1.0, x, 1, 0 ) ~2.0817 // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1.0, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/index.d.ts index be789ff684cf..6df16ce43a7d 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -36,10 +36,10 @@ interface Routine { * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * - * var v = dstdevyc( x.length, 1, x, 1 ); + * var v = dstdevyc( x.length, 1.0, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -56,10 +56,10 @@ interface Routine { * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * - * var v = dstdevyc.ndarray( x.length, 1, x, 1, 0 ); + * var v = dstdevyc.ndarray( x.length, 1.0, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example @@ -76,7 +76,7 @@ interface Routine { * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * -* var v = dstdevyc( x.length, 1, x, 1 ); +* var v = dstdevyc( x.length, 1.0, x, 1 ); * // returns ~2.0817 * * @example @@ -84,7 +84,7 @@ interface Routine { * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * -* var v = dstdevyc.ndarray( x.length, 1, x, 1, 0 ); +* var v = dstdevyc.ndarray( x.length, 1.0, x, 1, 0 ); * // returns ~2.0817 */ declare var dstdevyc: Routine; diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/test.ts index bdb011468b50..781bc13d5c1d 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/test.ts +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/docs/types/test.ts @@ -25,21 +25,21 @@ import dstdevyc = require( './index' ); { const x = new Float64Array( 10 ); - dstdevyc( x.length, 1, x, 1 ); // $ExpectType number + dstdevyc( x.length, 1.0, x, 1 ); // $ExpectType number } // The compiler throws an error if the function is provided a first argument which is not a number... { const x = new Float64Array( 10 ); - dstdevyc( '10', 1, x, 1 ); // $ExpectError - dstdevyc( true, 1, x, 1 ); // $ExpectError - dstdevyc( false, 1, x, 1 ); // $ExpectError - dstdevyc( null, 1, x, 1 ); // $ExpectError - dstdevyc( undefined, 1, x, 1 ); // $ExpectError - dstdevyc( [], 1, x, 1 ); // $ExpectError - dstdevyc( {}, 1, x, 1 ); // $ExpectError - dstdevyc( ( x: number ): number => x, 1, x, 1 ); // $ExpectError + dstdevyc( '10', 1.0, x, 1 ); // $ExpectError + dstdevyc( true, 1.0, x, 1 ); // $ExpectError + dstdevyc( false, 1.0, x, 1 ); // $ExpectError + dstdevyc( null, 1.0, x, 1 ); // $ExpectError + dstdevyc( undefined, 1.0, x, 1 ); // $ExpectError + dstdevyc( [], 1.0, x, 1 ); // $ExpectError + dstdevyc( {}, 1.0, x, 1 ); // $ExpectError + dstdevyc( ( x: number ): number => x, 1.0, x, 1 ); // $ExpectError } // The compiler throws an error if the function is provided a second argument which is not a number... @@ -60,29 +60,29 @@ import dstdevyc = require( './index' ); { const x = new Float64Array( 10 ); - dstdevyc( x.length, 1, 10, 1 ); // $ExpectError - dstdevyc( x.length, 1, '10', 1 ); // $ExpectError - dstdevyc( x.length, 1, true, 1 ); // $ExpectError - dstdevyc( x.length, 1, false, 1 ); // $ExpectError - dstdevyc( x.length, 1, null, 1 ); // $ExpectError - dstdevyc( x.length, 1, undefined, 1 ); // $ExpectError - dstdevyc( x.length, 1, [], 1 ); // $ExpectError - dstdevyc( x.length, 1, {}, 1 ); // $ExpectError - dstdevyc( x.length, 1, ( x: number ): number => x, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, 10, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, '10', 1 ); // $ExpectError + dstdevyc( x.length, 1.0, true, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, false, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, null, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, undefined, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, [], 1 ); // $ExpectError + dstdevyc( x.length, 1.0, {}, 1 ); // $ExpectError + dstdevyc( x.length, 1.0, ( x: number ): number => x, 1 ); // $ExpectError } // The compiler throws an error if the function is provided a fourth argument which is not a number... { const x = new Float64Array( 10 ); - dstdevyc( x.length, 1, x, '10' ); // $ExpectError - dstdevyc( x.length, 1, x, true ); // $ExpectError - dstdevyc( x.length, 1, x, false ); // $ExpectError - dstdevyc( x.length, 1, x, null ); // $ExpectError - dstdevyc( x.length, 1, x, undefined ); // $ExpectError - dstdevyc( x.length, 1, x, [] ); // $ExpectError - dstdevyc( x.length, 1, x, {} ); // $ExpectError - dstdevyc( x.length, 1, x, ( x: number ): number => x ); // $ExpectError + dstdevyc( x.length, 1.0, x, '10' ); // $ExpectError + dstdevyc( x.length, 1.0, x, true ); // $ExpectError + dstdevyc( x.length, 1.0, x, false ); // $ExpectError + dstdevyc( x.length, 1.0, x, null ); // $ExpectError + dstdevyc( x.length, 1.0, x, undefined ); // $ExpectError + dstdevyc( x.length, 1.0, x, [] ); // $ExpectError + dstdevyc( x.length, 1.0, x, {} ); // $ExpectError + dstdevyc( x.length, 1.0, x, ( x: number ): number => x ); // $ExpectError } // The compiler throws an error if the function is provided an unsupported number of arguments... @@ -91,30 +91,30 @@ import dstdevyc = require( './index' ); dstdevyc(); // $ExpectError dstdevyc( x.length ); // $ExpectError - dstdevyc( x.length, 1 ); // $ExpectError - dstdevyc( x.length, 1, x ); // $ExpectError - dstdevyc( x.length, 1, x, 1, 10 ); // $ExpectError + dstdevyc( x.length, 1.0 ); // $ExpectError + dstdevyc( x.length, 1.0, x ); // $ExpectError + dstdevyc( x.length, 1.0, x, 1, 10 ); // $ExpectError } // Attached to main export is an `ndarray` method which returns a number... { const x = new Float64Array( 10 ); - dstdevyc.ndarray( x.length, 1, x, 1, 0 ); // $ExpectType number + dstdevyc.ndarray( x.length, 1.0, x, 1, 0 ); // $ExpectType number } // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... { const x = new Float64Array( 10 ); - dstdevyc.ndarray( '10', 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( true, 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( false, 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( null, 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( undefined, 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( [], 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( {}, 1, x, 1, 0 ); // $ExpectError - dstdevyc.ndarray( ( x: number ): number => x, 1, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( '10', 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( true, 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( false, 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( null, 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( undefined, 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( [], 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( {}, 1.0, x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( ( x: number ): number => x, 1.0, x, 1, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... @@ -135,43 +135,43 @@ import dstdevyc = require( './index' ); { const x = new Float64Array( 10 ); - dstdevyc.ndarray( x.length, 1, 10, 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, '10', 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, true, 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, false, 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, null, 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, undefined, 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, [], 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, {}, 1, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, ( x: number ): number => x, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, 10, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, '10', 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, true, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, false, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, null, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, undefined, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, [], 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, {}, 1, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, ( x: number ): number => x, 1, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... { const x = new Float64Array( 10 ); - dstdevyc.ndarray( x.length, 1, x, '10', 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, true, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, false, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, null, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, undefined, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, [], 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, {}, 0 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, ( x: number ): number => x, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, '10', 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, true, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, false, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, null, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, undefined, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, [], 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, {}, 0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, ( x: number ): number => x, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... { const x = new Float64Array( 10 ); - dstdevyc.ndarray( x.length, 1, x, 1, '10' ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, true ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, false ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, null ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, undefined ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, [] ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, {} ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, ( x: number ): number => x ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, '10' ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, true ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, false ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, null ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, undefined ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, [] ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, {} ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, ( x: number ): number => x ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... @@ -180,8 +180,8 @@ import dstdevyc = require( './index' ); dstdevyc.ndarray(); // $ExpectError dstdevyc.ndarray( x.length ); // $ExpectError - dstdevyc.ndarray( x.length, 1 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1 ); // $ExpectError - dstdevyc.ndarray( x.length, 1, x, 1, 0, 10 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1 ); // $ExpectError + dstdevyc.ndarray( x.length, 1.0, x, 1, 0, 10 ); // $ExpectError } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/c/example.c index cccb616d0749..38867e242dac 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dstdevyc.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard deviation: - double v = stdlib_strided_dstdevyc( N, 1, x, stride ); + double v = stdlib_strided_dstdevyc( N, 1.0, x, strideX ); // Print the result: printf( "sample standard deviation: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/index.js index 8b9a1fb42fcc..b097cd431352 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/examples/index.js @@ -18,19 +18,13 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dstdevyc = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); -var v = dstdevyc( x.length, 1, x, 1 ); +var v = dstdevyc( x.length, 1.0, x, 1 ); console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/include/stdlib/stats/base/dstdevyc.h b/lib/node_modules/@stdlib/stats/base/dstdevyc/include/stdlib/stats/base/dstdevyc.h index c2c7c904c7bd..4aff22a2f126 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/include/stdlib/stats/base/dstdevyc.h +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/include/stdlib/stats/base/dstdevyc.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSTDEVYC_H #define STDLIB_STATS_BASE_DSTDEVYC_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. */ -double stdlib_strided_dstdevyc( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dstdevyc)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dstdevyc_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.js index 2f73390a3c99..3f947f520f86 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.js @@ -20,8 +20,8 @@ // MODULES // -var dvarianceyc = require( '@stdlib/stats/base/dvarianceyc' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -36,20 +36,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevyc( N, 1, x, 1 ); +* var v = dstdevyc( x.length, 1.0, x, 1 ); * // returns ~2.0817 */ -function dstdevyc( N, correction, x, stride ) { - return sqrt( dvarianceyc( N, correction, x, stride ) ); +function dstdevyc( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.native.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.native.js index 1412a9fe066b..922cfa5ad004 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/dstdevyc.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevyc( N, 1, x, 1 ); +* var v = dstdevyc( x.length, 1.0, x, 1 ); * // returns ~2.0817 */ -function dstdevyc( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dstdevyc( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/index.js index b639bfc51b40..dbba359a4626 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/index.js @@ -28,20 +28,17 @@ * var dstdevyc = require( '@stdlib/stats/base/dstdevyc' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dstdevyc( N, 1, x, 1 ); +* var v = dstdevyc( x.length, 1.0, x, 1 ); * // returns ~2.0817 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dstdevyc = require( '@stdlib/stats/base/dstdevyc' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevyc.ndarray( N, 1, x, 2, 1 ); +* var v = dstdevyc.ndarray( 4, 1.0, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.js index f00395d9c3cb..19f36e809f05 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.js @@ -36,22 +36,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevyc( N, 1, x, 2, 1 ); +* var v = dstdevyc( 4, 1.0, x, 2, 1 ); * // returns 2.5 */ -function dstdevyc( N, correction, x, stride, offset ) { - return sqrt( dvarianceyc( N, correction, x, stride, offset ) ); +function dstdevyc( N, correction, x, strideX, offsetX ) { + return sqrt( dvarianceyc( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.native.js index f289426d1e75..ff494e65917d 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dstdevyc.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dstdevyc.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dstdevyc( N, 1, x, 2, 1 ); +* var v = dstdevyc( 4, 1.0, x, 2, 1 ); * // returns 2.5 */ -function dstdevyc( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dstdevyc( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/manifest.json b/lib/node_modules/@stdlib/stats/base/dstdevyc/manifest.json index 11ff85b680fb..db81f65afb3a 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dstdevyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvarianceyc", "@stdlib/napi/export", "@stdlib/napi/argv", @@ -49,33 +52,55 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dstdevyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvarianceyc" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dstdevyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", + "@stdlib/stats/base/dvarianceyc" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrt", "@stdlib/stats/base/dvarianceyc" ] } diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/src/addon.c b/lib/node_modules/@stdlib/stats/base/dstdevyc/src/addon.c index b86395f29211..b3fb8a63b5e5 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dstdevyc.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dstdevyc( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevyc)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dstdevyc_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/src/dstdevyc.c b/lib/node_modules/@stdlib/stats/base/dstdevyc/src/dstdevyc.c deleted file mode 100644 index 6e6535361ee7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/src/dstdevyc.c +++ /dev/null @@ -1,39 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dstdevyc.h" -#include "stdlib/stats/base/dvarianceyc.h" -#include -#include - -/** -* Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. -* -* ## References -* -* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dstdevyc( const int64_t N, const double correction, const double *X, const int64_t stride ) { - return sqrt( stdlib_strided_dvarianceyc( N, correction, X, stride ) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/src/main.c b/lib/node_modules/@stdlib/stats/base/dstdevyc/src/main.c new file mode 100644 index 000000000000..72ea3b7a1ef8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/src/main.c @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dstdevyc.h" +#include "stdlib/stats/base/dvarianceyc.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +* +* ## References +* +* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevyc)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dstdevyc_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard deviation of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dstdevyc_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrt( API_SUFFIX(stdlib_strided_dvarianceyc_ndarray)( N, correction, X, strideX, offsetX ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.js index e3d34d3a7825..477805fd2f06 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -46,15 +45,15 @@ tape( 'the function calculates the population standard deviation of a strided ar var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 0, x, 1 ); + v = dstdevyc( x.length, 0.0, x, 1 ); t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 0, x, 1 ); + v = dstdevyc( x.length, 0.0, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 0, x, 1 ); + v = dstdevyc( x.length, 0.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -65,15 +64,15 @@ tape( 'the function calculates the sample standard deviation of a strided array' var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -85,10 +84,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 0, 1, x, 1 ); + v = dstdevyc( 0, 1.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dstdevyc( -1, 1, x, 1 ); + v = dstdevyc( -1, 1.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -100,7 +99,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a populat x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 1, 0, x, 1 ); + v = dstdevyc( 1, 0.0, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, 2 ); + v = dstdevyc( 4, 1.0, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, -2 ); + v = dstdevyc( 4, 1.0, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -173,7 +168,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 0 ); + v = dstdevyc( x.length, 1.0, x, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevyc( N, 1, x1, 2 ); + v = dstdevyc( 4, 1.0, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.native.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.native.js index 525500025840..81ae8890577e 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.dstdevyc.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -55,15 +54,15 @@ tape( 'the function calculates the population standard deviation of a strided ar var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 0, x, 1 ); + v = dstdevyc( x.length, 0.0, x, 1 ); t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 0, x, 1 ); + v = dstdevyc( x.length, 0.0, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 0, x, 1 ); + v = dstdevyc( x.length, 0.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -74,15 +73,15 @@ tape( 'the function calculates the sample standard deviation of a strided array' var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 1, x, 1 ); + v = dstdevyc( x.length, 1.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -94,10 +93,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 0, 1, x, 1 ); + v = dstdevyc( 0, 1.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dstdevyc( -1, 1, x, 1 ); + v = dstdevyc( -1, 1.0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -109,7 +108,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a populat x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 1, 0, x, 1 ); + v = dstdevyc( 1, 0.0, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, 2 ); + v = dstdevyc( 4, 1.0, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, -2 ); + v = dstdevyc( 4, 1.0, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -182,7 +177,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 0 ); + v = dstdevyc( x.length, 1.0, x, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dstdevyc( N, 1, x1, 2 ); + v = dstdevyc( 4, 1.0, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.js index b3d64390e38a..3f290f7e06e0 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -46,15 +45,15 @@ tape( 'the function calculates the population standard deviation of a strided ar var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 0, x, 1, 0 ); + v = dstdevyc( x.length, 0.0, x, 1, 0 ); t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 0, x, 1, 0 ); + v = dstdevyc( x.length, 0.0, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 0, x, 1, 0 ); + v = dstdevyc( x.length, 0.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -65,15 +64,15 @@ tape( 'the function calculates the sample standard deviation of a strided array' var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -85,10 +84,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 0, 1, x, 1, 0 ); + v = dstdevyc( 0, 1.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dstdevyc( -1, 1, x, 1, 0 ); + v = dstdevyc( -1, 1.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -100,7 +99,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a populat x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 1, 0, x, 1, 0 ); + v = dstdevyc( 1, 0.0, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, 2, 0 ); + v = dstdevyc( 4, 1.0, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, -2, 6 ); + v = dstdevyc( 4, 1.0, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -173,14 +168,13 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 0, 0 ); + v = dstdevyc( x.length, 1.0, x, 0, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, 2, 1 ); + v = dstdevyc( 4, 1.0, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.native.js index e75c9ef0079a..a4e744221b92 100644 --- a/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dstdevyc/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -55,15 +54,15 @@ tape( 'the function calculates the population standard deviation of a strided ar var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 0, x, 1, 0 ); + v = dstdevyc( x.length, 0.0, x, 1, 0 ); t.strictEqual( v, sqrt( 53.5/x.length ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 0, x, 1, 0 ); + v = dstdevyc( x.length, 0.0, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 0, x, 1, 0 ); + v = dstdevyc( x.length, 0.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -74,15 +73,15 @@ tape( 'the function calculates the sample standard deviation of a strided array' var v; x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ NaN, 4.0 ] ); - v = dstdevyc( x.length, 1, x, 1, 0 ); + v = dstdevyc( x.length, 1.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -94,10 +93,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 0, 1, x, 1, 0 ); + v = dstdevyc( 0, 1.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dstdevyc( -1, 1, x, 1, 0 ); + v = dstdevyc( -1, 1.0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -109,7 +108,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a populat x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( 1, 0, x, 1, 0 ); + v = dstdevyc( 1, 0.0, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, 2, 0 ); + v = dstdevyc( 4, 1.0, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, -2, 6 ); + v = dstdevyc( 4, 1.0, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -182,14 +177,13 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ); - v = dstdevyc( x.length, 1, x, 0, 0 ); + v = dstdevyc( x.length, 1.0, x, 0, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); t.end(); }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dstdevyc( N, 1, x, 2, 1 ); + v = dstdevyc( 4, 1.0, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/README.md b/lib/node_modules/@stdlib/stats/base/dvariancech/README.md index 8de7fb0ffa42..e8e74d2667f9 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/README.md +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dvariancech = require( '@stdlib/stats/base/dvariancech' ); ``` -#### dvariancech( N, correction, x, stride ) +#### dvariancech( N, correction, x, strideX ) Computes the [variance][variance] of a double-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -106,9 +106,8 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvariancech( N, 1, x, 1 ); +var v = dvariancech( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dvariancech( N, 1, x, 2 ); +var v = dvariancech( 4, 1, x, 2 ); // returns 6.25 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dvariancech( N, 1, x1, 2 ); +var v = dvariancech( 4, 1, x1, 2 ); // returns 6.25 ``` -#### dvariancech.ndarray( N, correction, x, stride, offset ) +#### dvariancech.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvariancech.ndarray( N, 1, x, 1, 0 ); +var v = dvariancech.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dvariancech.ndarray( N, 1, x, 2, 1 ); +var v = dvariancech.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -203,18 +194,12 @@ var v = dvariancech.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvariancech = require( '@stdlib/stats/base/dvariancech' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvariancech( x.length, 1, x, 1 ); @@ -225,6 +210,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dvariancech.h" +``` + +#### stdlib_strided_dvariancech( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvariancech( 3, 1.0, x, 1 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dvariancech( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dvariancech_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvariancech_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dvariancech_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dvariancech.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dvariancech( N, 1, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.js index 8c94964499db..68481178fe1e 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvariancech = require( './../lib/dvariancech.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvariancech = require( './../lib/dvariancech.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.native.js index 38998beb072d..9ceddc82e7b1 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvariancech = tryRequire( resolve( __dirname, './../lib/dvariancech.native.j var opts = { 'skip': ( dvariancech instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.js index 92e4106ddb76..693f3286c128 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvariancech = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvariancech = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.native.js index 2c316a860600..963be337bde5 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvariancech = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dvariancech instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/c/benchmark.length.c index 0bb519635238..03fafbcf8698 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dvariancech( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dvariancech_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dvariancech/docs/repl.txt index 43f242fac84b..5c7cb150ec99 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -89,10 +86,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -109,8 +106,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dvariancech/docs/types/index.d.ts index 9c130062d17c..8025a470dc2a 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dvariancech( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dvariancech.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dvariancech/examples/c/example.c index 1a1d1c9f37ca..7d6d7a3ceacd 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dvariancech.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - double v = stdlib_strided_dvariancech( N, 1, x, stride ); + double v = stdlib_strided_dvariancech( N, 1, x, strideX ); // Print the result: printf( "sample variance: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/examples/index.js b/lib/node_modules/@stdlib/stats/base/dvariancech/examples/index.js index 84ebbc7026ea..05eea282c667 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvariancech = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvariancech( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/include/stdlib/stats/base/dvariancech.h b/lib/node_modules/@stdlib/stats/base/dvariancech/include/stdlib/stats/base/dvariancech.h index 09fea705a327..495bef2f7f37 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/include/stdlib/stats/base/dvariancech.h +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/include/stdlib/stats/base/dvariancech.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DVARIANCECH_H #define STDLIB_STATS_BASE_DVARIANCECH_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. */ -double stdlib_strided_dvariancech( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dvariancech)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dvariancech_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.js b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.js index 1a0cc187c833..63e8b0c94228 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -37,53 +43,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancech( N, 1, x, 1 ); +* var v = dvariancech( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvariancech( N, correction, x, stride ) { - var mu; - var ix; - var M2; - var M; - var d; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - // Use an estimate for the mean: - mu = x[ ix ]; - ix += stride; - - // Compute the variance... - M2 = 0.0; - M = 0.0; - for ( i = 1; i < N; i++ ) { - d = x[ ix ] - mu; - M2 += d * d; - M += d; - ix += stride; - } - return (M2/n) - ((M/N)*(M/n)); +function dvariancech( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.native.js b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.native.js index beaecd2bd919..2b3a272f7a07 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/dvariancech.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancech( N, 1, x, 1 ); +* var v = dvariancech( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvariancech( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dvariancech( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/index.js b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/index.js index d815a35db3cc..d1d1038370b0 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/index.js @@ -28,20 +28,17 @@ * var dvariancech = require( '@stdlib/stats/base/dvariancech' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancech( N, 1, x, 1 ); +* var v = dvariancech( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dvariancech = require( '@stdlib/stats/base/dvariancech' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancech.ndarray( N, 1, x, 2, 1 ); +* var v = dvariancech.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.js index 32a13515e763..0edf6e118d41 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.js @@ -37,21 +37,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancech( N, 1, x, 2, 1 ); +* var v = dvariancech( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvariancech( N, correction, x, stride, offset ) { +function dvariancech( N, correction, x, strideX, offsetX ) { var mu; var ix; var M2; @@ -64,14 +62,14 @@ function dvariancech( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - ix = offset; + ix = offsetX; // Use an estimate for the mean: mu = x[ ix ]; - ix += stride; + ix += strideX; // Compute the variance... M2 = 0.0; @@ -80,7 +78,7 @@ function dvariancech( N, correction, x, stride, offset ) { d = x[ ix ] - mu; M2 += d * d; M += d; - ix += stride; + ix += strideX; } return (M2/n) - ((M/N)*(M/n)); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.native.js index e7c345eee924..ff16a3d86026 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dvariancech.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dvariancech.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancech( N, 1, x, 2, 1 ); +* var v = dvariancech( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvariancech( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dvariancech( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/manifest.json b/lib/node_modules/@stdlib/stats/base/dvariancech/manifest.json index f7c4971545f4..86308d31795d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dvariancech.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,31 +50,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dvariancech.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dvariancech.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/src/addon.c b/lib/node_modules/@stdlib/stats/base/dvariancech/src/addon.c index 803792a03f9c..2b89f8ad017f 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/src/addon.c @@ -17,12 +17,13 @@ */ #include "stdlib/stats/base/dvariancech.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_double.h" #include "stdlib/napi/argv_strided_float64array.h" #include "stdlib/napi/create_double.h" +#include "stdlib/napi/argv_double.h" #include /** @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dvariancech( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvariancech)( N, correction, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvariancech_ndarray)( N, correction, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/src/dvariancech.c b/lib/node_modules/@stdlib/stats/base/dvariancech/src/dvariancech.c deleted file mode 100644 index 96985256f3e5..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/src/dvariancech.c +++ /dev/null @@ -1,79 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dvariancech.h" -#include - -/** -* Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. -* -* ## Method -* -* - This implementation uses a one-pass trial mean approach, as suggested by Chan et al (1983). -* -* ## References -* -* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). -* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). -* - Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis, Ltd.: 242–47. doi:[10.1080/00031305.1983.10483115](https://doi.org/10.1080/00031305.1983.10483115). -* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dvariancech( const int64_t N, const double correction, const double *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double dN; - double mu; - double M2; - double M; - double n; - double d; - - dN = (double)N; - n = dN - correction; - if ( N <= 0 || n <= 0.0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - // Use an estimate for the mean: - mu = X[ ix ]; - ix += stride; - - // Compute the variance... - M2 = 0.0; - M = 0.0; - for ( i = 1; i < N; i++ ) { - d = X[ ix ] - mu; - M2 += d * d; - M += d; - ix += stride; - } - return (M2/n) - ((M/dN)*(M/n)); -} diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/src/main.c b/lib/node_modules/@stdlib/stats/base/dvariancech/src/main.c new file mode 100644 index 000000000000..5af8b762169c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dvariancech.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm. +* +* ## Method +* +* - This implementation uses a one-pass trial mean approach, as suggested by Chan et al (1983). +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). +* - Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis, Ltd.: 242–47. doi:[10.1080/00031305.1983.10483115](https://doi.org/10.1080/00031305.1983.10483115). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvariancech)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dvariancech_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvariancech_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double dN; + double mu; + double M2; + double M; + double n; + double d; + + dN = (double)N; + n = dN - correction; + if ( N <= 0 || n <= 0.0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0; + } + ix = offsetX; + // Use an estimate for the mean: + mu = X[ ix ]; + ix += strideX; + + // Compute the variance... + M2 = 0.0; + M = 0.0; + for ( i = 1; i < N; i++ ) { + d = X[ ix ] - mu; + M2 += d * d; + M += d; + ix += strideX; + } + return (M2/n) - ((M/dN)*(M/n)); +} diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.js b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.js index 052d25c282cd..b4e14cdc2a79 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvariancech = require( './../lib/dvariancech.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, 2 ); + v = dvariancech( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, -2 ); + v = dvariancech( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -181,7 +176,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -197,9 +191,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvariancech( N, 1, x1, 2 ); + v = dvariancech( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.native.js b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.native.js index ad8c98810b2d..37955ab18d31 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.dvariancech.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, 2 ); + v = dvariancech( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, -2 ); + v = dvariancech( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -206,9 +200,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvariancech( N, 1, x1, 2 ); + v = dvariancech( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.js index d400dbef578a..0f84382a5d7b 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvariancech = require( './../lib/ndarray.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, 2, 0 ); + v = dvariancech( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, -2, 6 ); + v = dvariancech( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -179,7 +174,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -193,9 +187,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, 2, 1 ); + v = dvariancech( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.native.js index 1bf1c941612d..8e72d0ed47a6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancech/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, 2, 0 ); + v = dvariancech( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, -2, 6 ); + v = dvariancech( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -188,7 +183,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -202,9 +196,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvariancech( N, 1, x, 2, 1 ); + v = dvariancech( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/README.md b/lib/node_modules/@stdlib/stats/base/dvariancetk/README.md index 548089be3223..3128ccbb0a06 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/README.md +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/README.md @@ -128,7 +128,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dvariancetk = require( '@stdlib/stats/base/dvariancetk' ); ``` -#### dvariancetk( N, correction, x, stride ) +#### dvariancetk( N, correction, x, strideX ) Computes the [variance][variance] of a double-precision floating-point strided array `x` using a one-pass textbook algorithm. @@ -136,9 +136,8 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvariancetk( N, 1, x, 1 ); +var v = dvariancetk( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -147,18 +146,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dvariancetk( N, 1, x, 2 ); +var v = dvariancetk( 4, 1, x, 2 ); // returns 6.25 ``` @@ -168,18 +165,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dvariancetk( N, 1, x1, 2 ); +var v = dvariancetk( 4, 1, x1, 2 ); // returns 6.25 ``` -#### dvariancetk.ndarray( N, correction, x, stride, offset ) +#### dvariancetk.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -187,26 +181,23 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvariancetk.ndarray( N, 1, x, 1, 0 ); +var v = dvariancetk.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in the strided array starting from the second value ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dvariancetk.ndarray( N, 1, x, 2, 1 ); +var v = dvariancetk.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -233,18 +224,12 @@ var v = dvariancetk.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvariancetk = require( '@stdlib/stats/base/dvariancetk' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvariancetk( x.length, 1, x, 1 ); @@ -255,6 +240,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dvariancetk.h" +``` + +#### stdlib_strided_dvariancetk( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass textbook algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvariancetk( 3, 1.0, x, 1 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dvariancetk( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dvariancetk_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvariancetk_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dvariancetk_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dvariancetk.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dvariancetk( N, 1, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.js index 295336c9f89e..99dcf9039510 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvariancetk = require( './../lib/dvariancetk.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvariancetk = require( './../lib/dvariancetk.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.native.js index e23a1e9d9fe1..54fede9a4b51 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvariancetk = tryRequire( resolve( __dirname, './../lib/dvariancetk.native.j var opts = { 'skip': ( dvariancetk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.js index 7722baec16a1..39cbf0d13bd6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvariancetk = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvariancetk = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.native.js index a3f7a8437f82..78ae0396b46d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvariancetk = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dvariancetk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/c/benchmark.length.c index bd44a2b00c5d..6bde367ec742 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dvariancetk( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dvariancetk_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/repl.txt index d2f8d8ca3687..ee1018955e7f 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -89,10 +86,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -109,8 +106,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/types/index.d.ts index 94bbaaeea820..a7fb647373c6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dvariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dvariancetk.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/c/example.c index d471bb58fa2b..f6e98c48c379 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dvariancetk.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - double v = stdlib_strided_dvariancetk( N, 1, x, stride ); + double v = stdlib_strided_dvariancetk( N, 1, x, strideX ); // Print the result: printf( "sample variance: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/index.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/index.js index 20f27a659094..80170888e231 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvariancetk = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvariancetk( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/include/stdlib/stats/base/dvariancetk.h b/lib/node_modules/@stdlib/stats/base/dvariancetk/include/stdlib/stats/base/dvariancetk.h index bd8a8026309d..4fcc5d7bc8f2 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/include/stdlib/stats/base/dvariancetk.h +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/include/stdlib/stats/base/dvariancetk.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DVARIANCETK_H #define STDLIB_STATS_BASE_DVARIANCETK_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. */ -double stdlib_strided_dvariancetk( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dvariancetk)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dvariancetk_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.js index 2588c9736d78..33c20b35b2c0 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -26,47 +32,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancetk( N, 1, x, 1 ); +* var v = dvariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvariancetk( N, correction, x, stride ) { - var S2; - var ix; - var S; - var v; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - S2 = 0.0; - S = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - S2 += v * v; - S += v; - ix += stride; - } - return (S2 - ((S/N)*S)) / n; +function dvariancetk( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.native.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.native.js index 4485bbddef49..b53cfe0e7eaf 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/dvariancetk.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancetk( N, 1, x, 1 ); +* var v = dvariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvariancetk( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dvariancetk( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/index.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/index.js index 6ba421bfcbca..e7e9fc0672a4 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/index.js @@ -28,20 +28,17 @@ * var dvariancetk = require( '@stdlib/stats/base/dvariancetk' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancetk( N, 1, x, 1 ); +* var v = dvariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dvariancetk = require( '@stdlib/stats/base/dvariancetk' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancetk.ndarray( N, 1, x, 2, 1 ); +* var v = dvariancetk.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.js index c75d5f483307..69c7c464db1b 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.js @@ -26,21 +26,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancetk( N, 1, x, 2, 1 ); +* var v = dvariancetk( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvariancetk( N, correction, x, stride, offset ) { +function dvariancetk( N, correction, x, strideX, offsetX ) { var S2; var ix; var S; @@ -52,17 +50,17 @@ function dvariancetk( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - ix = offset; + ix = offsetX; S2 = 0.0; S = 0.0; for ( i = 0; i < N; i++ ) { v = x[ ix ]; S2 += v * v; S += v; - ix += stride; + ix += strideX; } return (S2 - ((S/N)*S)) / n; } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.native.js index b5465e5a2f5e..01dacde3cb85 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dvariancetk.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dvariancetk.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancetk( N, 1, x, 2, 1 ); +* var v = dvariancetk( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvariancetk( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dvariancetk( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/manifest.json b/lib/node_modules/@stdlib/stats/base/dvariancetk/manifest.json index 45074c2c9287..86308d31795d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dvariancetk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,31 +50,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dvariancetk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dvariancetk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/src/addon.c b/lib/node_modules/@stdlib/stats/base/dvariancetk/src/addon.c index ffdb298bfa17..b915b8e8a342 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/src/addon.c @@ -17,12 +17,13 @@ */ #include "stdlib/stats/base/dvariancetk.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_double.h" #include "stdlib/napi/argv_strided_float64array.h" #include "stdlib/napi/create_double.h" +#include "stdlib/napi/argv_double.h" #include /** @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dvariancetk( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvariancetk)( N, correction, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvariancetk_ndarray)( N, correction, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/src/dvariancetk.c b/lib/node_modules/@stdlib/stats/base/dvariancetk/src/dvariancetk.c deleted file mode 100644 index 788876381d55..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/src/dvariancetk.c +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dvariancetk.h" -#include - -/** -* Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dvariancetk( const int64_t N, const double correction, const double *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double dN; - double S2; - double S; - double n; - double v; - - dN = (double)N; - n = dN - correction; - if ( N <= 0 || n <= 0.0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - S2 = 0.0; - S = 0.0; - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - S2 += v * v; - S += v; - ix += stride; - } - return (S2 - ((S/dN)*S)) / n; -} diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/src/main.c b/lib/node_modules/@stdlib/stats/base/dvariancetk/src/main.c new file mode 100644 index 000000000000..c85b9d125742 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/src/main.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dvariancetk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvariancetk)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dvariancetk_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvariancetk_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double dN; + double S2; + double S; + double n; + double v; + + dN = (double)N; + n = dN - correction; + if ( N <= 0 || n <= 0.0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0; + } + ix = offsetX; + S2 = 0.0; + S = 0.0; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + S2 += v * v; + S += v; + ix += strideX; + } + return (S2 - ((S/dN)*S)) / n; +} diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.js index a9d76f228232..ba5348da279d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvariancetk = require( './../lib/dvariancetk.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, 2 ); + v = dvariancetk( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, -2 ); + v = dvariancetk( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -181,7 +176,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -197,9 +191,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvariancetk( N, 1, x1, 2 ); + v = dvariancetk( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.native.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.native.js index 992072037bf6..1a97b4fae201 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.dvariancetk.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, 2 ); + v = dvariancetk( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, -2 ); + v = dvariancetk( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -206,9 +200,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvariancetk( N, 1, x1, 2 ); + v = dvariancetk( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.js index 79b59b853163..39c8aa006676 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvariancetk = require( './../lib/ndarray.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, 2, 0 ); + v = dvariancetk( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, -2, 6 ); + v = dvariancetk( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -179,7 +174,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -193,9 +187,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, 2, 1 ); + v = dvariancetk( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.native.js index bc4c84a6f9d1..c5eace23715f 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancetk/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, 2, 0 ); + v = dvariancetk( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, -2, 6 ); + v = dvariancetk( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -188,7 +183,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -202,9 +196,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvariancetk( N, 1, x, 2, 1 ); + v = dvariancetk( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/README.md b/lib/node_modules/@stdlib/stats/base/dvariancewd/README.md index 9e11e1a8c15f..095f62e75201 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dvariancewd = require( '@stdlib/stats/base/dvariancewd' ); ``` -#### dvariancewd( N, correction, x, stride ) +#### dvariancewd( N, correction, x, strideX ) Computes the [variance][variance] of a double-precision floating-point strided array `x` using Welford's algorithm. @@ -106,9 +106,8 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvariancewd( N, 1, x, 1 ); +var v = dvariancewd( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dvariancewd( N, 1, x, 2 ); +var v = dvariancewd( 4, 1, x, 2 ); // returns 6.25 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dvariancewd( N, 1, x1, 2 ); +var v = dvariancewd( 4, 1, x1, 2 ); // returns 6.25 ``` -#### dvariancewd.ndarray( N, correction, x, stride, offset ) +#### dvariancewd.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvariancewd.ndarray( N, 1, x, 1, 0 ); +var v = dvariancewd.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dvariancewd.ndarray( N, 1, x, 2, 1 ); +var v = dvariancewd.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -202,18 +193,12 @@ var v = dvariancewd.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvariancewd = require( '@stdlib/stats/base/dvariancewd' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvariancewd( x.length, 1, x, 1 ); @@ -224,6 +209,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dvariancewd.h" +``` + +#### stdlib_strided_dvariancewd( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using Welford's algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvariancewd( 3, 1.0, x, 1 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dvariancewd( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dvariancewd_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvariancewd_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dvariancewd_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dvariancewd.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dvariancewd( N, 1, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.js index be28678b6447..01b1faf962d5 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvariancewd = require( './../lib/dvariancewd.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvariancewd = require( './../lib/dvariancewd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.native.js index 4ef289b16216..3074888bc88a 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvariancewd = tryRequire( resolve( __dirname, './../lib/dvariancewd.native.j var opts = { 'skip': ( dvariancewd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.js index eb2d99e3330a..9c93f60fb280 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvariancewd = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvariancewd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.native.js index 44812a228ef1..4694e7de9c5f 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvariancewd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dvariancewd instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/c/benchmark.length.c index 986d3edca940..25661cc7bac1 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dvariancewd( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dvariancewd_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/repl.txt index 147cd77e66fc..ec1f6ad472d7 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a double-precision floating-point strided array using Welford's algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -89,10 +86,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -109,8 +106,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/types/index.d.ts index a37477f05447..11a709310ce6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dvariancewd( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the variance of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dvariancewd.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/c/example.c index 489140280f6a..e137c62990c2 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dvariancewd.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - double v = stdlib_strided_dvariancewd( N, 1, x, stride ); + double v = stdlib_strided_dvariancewd( N, 1, x, strideX ); // Print the result: printf( "sample variance: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/index.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/index.js index 1bc5a243ce5e..b17b80c6c284 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvariancewd = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvariancewd( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/include/stdlib/stats/base/dvariancewd.h b/lib/node_modules/@stdlib/stats/base/dvariancewd/include/stdlib/stats/base/dvariancewd.h index 3077f8abe607..fa51f9f0972c 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/include/stdlib/stats/base/dvariancewd.h +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/include/stdlib/stats/base/dvariancewd.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DVARIANCEWD_H #define STDLIB_STATS_BASE_DVARIANCEWD_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a double-precision floating-point strided array using Welford's algorithm. */ -double stdlib_strided_dvariancewd( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dvariancewd)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dvariancewd_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.js index c89b1bf23f74..2c45bf91eaa3 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -65,49 +71,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancewd( N, 1, x, 1 ); +* var v = dvariancewd( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvariancewd( N, correction, x, stride ) { - var delta; - var mu; - var M2; - var ix; - var v; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - M2 = 0.0; - mu = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - delta = v - mu; - mu += delta / (i+1); - M2 += delta * ( v - mu ); - ix += stride; - } - return M2 / n; +function dvariancewd( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.native.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.native.js index b33206232c82..68a27da43587 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/dvariancewd.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancewd( N, 1, x, 1 ); +* var v = dvariancewd( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvariancewd( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dvariancewd( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/index.js index 9bdffe84e307..cbe5ac50522d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/index.js @@ -28,20 +28,17 @@ * var dvariancewd = require( '@stdlib/stats/base/dvariancewd' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvariancewd( N, 1, x, 1 ); +* var v = dvariancewd( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dvariancewd = require( '@stdlib/stats/base/dvariancewd' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancewd.ndarray( N, 1, x, 2, 1 ); +* var v = dvariancewd.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.js index 6a8bf38c6f8e..73e6a6ead015 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.js @@ -65,21 +65,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancewd( N, 1, x, 2, 1 ); +* var v = dvariancewd( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvariancewd( N, correction, x, stride, offset ) { +function dvariancewd( N, correction, x, strideX, offsetX ) { var delta; var mu; var M2; @@ -92,10 +90,10 @@ function dvariancewd( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - ix = offset; + ix = offsetX; M2 = 0.0; mu = 0.0; for ( i = 0; i < N; i++ ) { @@ -103,7 +101,7 @@ function dvariancewd( N, correction, x, stride, offset ) { delta = v - mu; mu += delta / (i+1); M2 += delta * ( v - mu ); - ix += stride; + ix += strideX; } return M2 / n; } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.native.js index a9eef17e4fab..97a4b7a3a56a 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dvariancewd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dvariancewd.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvariancewd( N, 1, x, 2, 1 ); +* var v = dvariancewd( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvariancewd( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dvariancewd( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/manifest.json b/lib/node_modules/@stdlib/stats/base/dvariancewd/manifest.json index a57661e74320..86308d31795d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dvariancewd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,31 +50,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dvariancewd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dvariancewd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dvariancewd/src/addon.c index c5ed41ec9918..69d6ea22c871 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/src/addon.c @@ -17,12 +17,13 @@ */ #include "stdlib/stats/base/dvariancewd.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_double.h" #include "stdlib/napi/argv_strided_float64array.h" #include "stdlib/napi/create_double.h" +#include "stdlib/napi/argv_double.h" #include /** @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dvariancewd( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvariancewd)( N, correction, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvariancewd_ndarray)( N, correction, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/src/dvariancewd.c b/lib/node_modules/@stdlib/stats/base/dvariancewd/src/dvariancewd.c deleted file mode 100644 index 148ac77e7bb0..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/src/dvariancewd.c +++ /dev/null @@ -1,101 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dvariancewd.h" -#include - -/** -* Computes the variance of a double-precision floating-point strided array using Welford's algorithm. -* -* ## Method -* -* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows. Let -* -* ```tex -* \begin{align*} -* S_n &= n \sigma_n^2 \\ -* &= \sum_{i=1}^{n} (x_i - \mu_n)^2 \\ -* &= \biggl(\sum_{i=1}^{n} x_i^2 \biggr) - n\mu_n^2 -* \end{align*} -* ``` -* -* Accordingly, -* -* ```tex -* \begin{align*} -* S_n - S_{n-1} &= \sum_{i=1}^{n} x_i^2 - n\mu_n^2 - \sum_{i=1}^{n-1} x_i^2 + (n-1)\mu_{n-1}^2 \\ -* &= x_n^2 - n\mu_n^2 + (n-1)\mu_{n-1}^2 \\ -* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1}^2 - \mu_n^2) \\ -* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1} - \mu_n)(\mu_{n-1} + \mu_n) \\ -* &= x_n^2 - \mu_{n-1}^2 + (\mu_{n-1} - x_n)(\mu_{n-1} + \mu_n) \\ -* &= x_n^2 - \mu_{n-1}^2 + \mu_{n-1}^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ -* &= x_n^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ -* &= (x_n - \mu_{n-1})(x_n - \mu_n) \\ -* &= S_{n-1} + (x_n - \mu_{n-1})(x_n - \mu_n) -* \end{align*} -* ``` -* -* where we use the identity -* -* ```tex -* x_n - \mu_{n-1} = n (\mu_n - \mu_{n-1}) -* ``` -* -* ## References -* -* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). -* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dvariancewd( const int64_t N, const double correction, const double *X, const int64_t stride ) { - double delta; - int64_t ix; - int64_t i; - double mu; - double M2; - double n; - double v; - - n = (double)N - correction; - if ( N <= 0 || n <= 0.0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - M2 = 0.0; - mu = 0.0; - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - delta = v - mu; - mu += delta / (double)(i+1); - M2 += delta * ( v - mu ); - ix += stride; - } - return M2 / n; -} diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/src/main.c b/lib/node_modules/@stdlib/stats/base/dvariancewd/src/main.c new file mode 100644 index 000000000000..61d55409fa45 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/src/main.c @@ -0,0 +1,113 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dvariancewd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a double-precision floating-point strided array using Welford's algorithm. +* +* ## Method +* +* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows. Let +* +* ```tex +* \begin{align*} +* S_n &= n \sigma_n^2 \\ +* &= \sum_{i=1}^{n} (x_i - \mu_n)^2 \\ +* &= \biggl(\sum_{i=1}^{n} x_i^2 \biggr) - n\mu_n^2 +* \end{align*} +* ``` +* +* Accordingly, +* +* ```tex +* \begin{align*} +* S_n - S_{n-1} &= \sum_{i=1}^{n} x_i^2 - n\mu_n^2 - \sum_{i=1}^{n-1} x_i^2 + (n-1)\mu_{n-1}^2 \\ +* &= x_n^2 - n\mu_n^2 + (n-1)\mu_{n-1}^2 \\ +* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1}^2 - \mu_n^2) \\ +* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1} - \mu_n)(\mu_{n-1} + \mu_n) \\ +* &= x_n^2 - \mu_{n-1}^2 + (\mu_{n-1} - x_n)(\mu_{n-1} + \mu_n) \\ +* &= x_n^2 - \mu_{n-1}^2 + \mu_{n-1}^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ +* &= x_n^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ +* &= (x_n - \mu_{n-1})(x_n - \mu_n) \\ +* &= S_{n-1} + (x_n - \mu_{n-1})(x_n - \mu_n) +* \end{align*} +* ``` +* +* where we use the identity +* +* ```tex +* x_n - \mu_{n-1} = n (\mu_n - \mu_{n-1}) +* ``` +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvariancewd)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dvariancewd_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvariancewd_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + double delta; + CBLAS_INT ix; + CBLAS_INT i; + double mu; + double M2; + double n; + double v; + + n = (double)N - correction; + if ( N <= 0 || n <= 0.0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0; + } + ix = offsetX; + M2 = 0.0; + mu = 0.0; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + delta = v - mu; + mu += delta / (double)(i+1); + M2 += delta * ( v - mu ); + ix += strideX; + } + return M2 / n; +} diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.js index 8bbae408e2e3..e9ea5e1d0676 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvariancewd = require( './../lib/dvariancewd.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, 2 ); + v = dvariancewd( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, -2 ); + v = dvariancewd( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -181,7 +176,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -197,9 +191,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvariancewd( N, 1, x1, 2 ); + v = dvariancewd( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.native.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.native.js index b6a079bbbaa8..614eb77aa97b 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.dvariancewd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, 2 ); + v = dvariancewd( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, -2 ); + v = dvariancewd( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -206,9 +200,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvariancewd( N, 1, x1, 2 ); + v = dvariancewd( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.js index 2480b0dc5de1..f574fbe64807 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvariancewd = require( './../lib/ndarray.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, 2, 0 ); + v = dvariancewd( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, -2, 6 ); + v = dvariancewd( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -179,7 +174,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -193,9 +187,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, 2, 1 ); + v = dvariancewd( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.native.js index 2c35d085398d..828b3a69178b 100644 --- a/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvariancewd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, 2, 0 ); + v = dvariancewd( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, -2, 6 ); + v = dvariancewd( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -188,7 +183,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -202,9 +196,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvariancewd( N, 1, x, 2, 1 ); + v = dvariancewd( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/README.md b/lib/node_modules/@stdlib/stats/base/dvarianceyc/README.md index ba7635b8d142..9f79f8b49dfe 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/README.md +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dvarianceyc = require( '@stdlib/stats/base/dvarianceyc' ); ``` -#### dvarianceyc( N, correction, x, stride ) +#### dvarianceyc( N, correction, x, strideX ) Computes the [variance][variance] of a double-precision floating-point strided array `x` using a one-pass algorithm proposed by Youngs and Cramer. @@ -106,9 +106,8 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvarianceyc( N, 1, x, 1 ); +var v = dvarianceyc( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dvarianceyc( N, 1, x, 2 ); +var v = dvarianceyc( 4, 1, x, 2 ); // returns 6.25 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dvarianceyc( N, 1, x1, 2 ); +var v = dvarianceyc( 4, 1, x1, 2 ); // returns 6.25 ``` -#### dvarianceyc.ndarray( N, correction, x, stride, offset ) +#### dvarianceyc.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [variance][variance] of a double-precision floating-point strided a var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = dvarianceyc.ndarray( N, 1, x, 1, 0 ); +var v = dvarianceyc.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dvarianceyc.ndarray( N, 1, x, 2, 1 ); +var v = dvarianceyc.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -202,18 +193,12 @@ var v = dvarianceyc.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvarianceyc = require( '@stdlib/stats/base/dvarianceyc' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvarianceyc( x.length, 1, x, 1 ); @@ -224,6 +209,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dvarianceyc.h" +``` + +#### stdlib_strided_dvarianceyc( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvarianceyc( 3, 1.0, x, 1 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dvarianceyc( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dvarianceyc_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvarianceyc_ndarray( 3, 1.0, x, 1, 0 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dvarianceyc_ndarray( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dvarianceyc.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dvarianceyc( N, 1, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.js index b54c56dea28f..470d8d26b207 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvarianceyc = require( './../lib/dvarianceyc.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvarianceyc = require( './../lib/dvarianceyc.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.native.js index 766f11790923..8ae25a7ab31d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvarianceyc = tryRequire( resolve( __dirname, './../lib/dvarianceyc.native.j var opts = { 'skip': ( dvarianceyc instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.js index 5f03d57392e0..0bb722cc980d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvarianceyc = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvarianceyc = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.native.js index 70026bc3363f..d57fbad48a97 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvarianceyc = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( dvarianceyc instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/c/benchmark.length.c index 9fd04b2942de..96da50370957 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dvarianceyc( len, 1.0, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dvarianceyc_ndarray( len, 1.0, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/repl.txt index 13e416059d54..0d459232934b 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/types/index.d.ts index d6c181e4855a..01dfc782a622 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = dvarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = dvarianceyc.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/c/example.c index 5057c582ae99..5cfa15d9faf0 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dvarianceyc.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - double v = stdlib_strided_dvarianceyc( N, 1, x, stride ); + double v = stdlib_strided_dvarianceyc( N, 1, x, strideX ); // Print the result: printf( "sample variance: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/index.js index c6ac20b81713..9a412716dac3 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvarianceyc = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvarianceyc( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/include/stdlib/stats/base/dvarianceyc.h b/lib/node_modules/@stdlib/stats/base/dvarianceyc/include/stdlib/stats/base/dvarianceyc.h index 6a78e9124efc..8e46400adeb1 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/include/stdlib/stats/base/dvarianceyc.h +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/include/stdlib/stats/base/dvarianceyc.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DVARIANCEYC_H #define STDLIB_STATS_BASE_DVARIANCEYC_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. */ -double stdlib_strided_dvarianceyc( const int64_t N, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dvarianceyc)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dvarianceyc_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.js index 1e5612d8a65a..c8895bd95db6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -34,50 +40,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvarianceyc( N, 1, x, 1 ); +* var v = dvarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvarianceyc( N, correction, x, stride ) { - var sum; - var ix; - var S; - var v; - var d; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = x[ ix ]; - ix += stride; - S = 0.0; - for ( i = 2; i <= N; i++ ) { - v = x[ ix ]; - sum += v; - d = (i*v) - sum; - S += (1.0/(i*(i-1))) * d * d; - ix += stride; - } - return S / n; +function dvarianceyc( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.native.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.native.js index cc006bf4059e..528d2e7a834a 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/dvarianceyc.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvarianceyc( N, 1, x, 1 ); +* var v = dvarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function dvarianceyc( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function dvarianceyc( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/index.js index a13977a30538..4e877ff357aa 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/index.js @@ -28,20 +28,17 @@ * var dvarianceyc = require( '@stdlib/stats/base/dvarianceyc' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = dvarianceyc( N, 1, x, 1 ); +* var v = dvarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dvarianceyc = require( '@stdlib/stats/base/dvarianceyc' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvarianceyc.ndarray( N, 1, x, 2, 1 ); +* var v = dvarianceyc.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.js index 68cebc9719e6..3dad935d833c 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.js @@ -34,21 +34,19 @@ * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvarianceyc( N, 1, x, 2, 1 ); +* var v = dvarianceyc( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvarianceyc( N, correction, x, stride, offset ) { +function dvarianceyc( N, correction, x, strideX, offsetX ) { var sum; var ix; var S; @@ -61,18 +59,18 @@ function dvarianceyc( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - sum = x[ offset ]; - ix = offset + stride; + sum = x[ offsetX ]; + ix = offsetX + strideX; S = 0.0; for ( i = 2; i <= N; i++ ) { v = x[ ix ]; sum += v; d = (i*v) - sum; S += (1.0/(i*(i-1))) * d * d; - ix += stride; + ix += strideX; } return S / n; } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.native.js index 6a91178dae41..56df3eb22e57 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dvarianceyc.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './dvarianceyc.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvarianceyc( N, 1, x, 2, 1 ); +* var v = dvarianceyc( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function dvarianceyc( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function dvarianceyc( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/manifest.json b/lib/node_modules/@stdlib/stats/base/dvarianceyc/manifest.json index 8e508090b8c2..86308d31795d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dvarianceyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,31 +50,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dvarianceyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dvarianceyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/addon.c b/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/addon.c index f4902bb475e1..4fee08a907c2 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/dvarianceyc.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dvarianceyc( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvarianceyc)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvarianceyc_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/dvarianceyc.c b/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/dvarianceyc.c deleted file mode 100644 index a65f6a63662d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/dvarianceyc.c +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dvarianceyc.h" -#include - -/** -* Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. -* -* ## Method -* -* - This implementation uses a one-pass algorithm, as proposed by Youngs and Cramer (1971). -* -* ## References -* -* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dvarianceyc( const int64_t N, const double correction, const double *X, const int64_t stride ) { - double sum; - int64_t ix; - int64_t i; - double di; - double S; - double v; - double n; - double d; - - n = (double)N - correction; - if ( N <= 0 || n <= 0.0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = X[ ix ]; - ix += stride; - S = 0.0; - for ( i = 2; i <= N; i++ ) { - di = (double)i; - v = X[ ix ]; - sum += v; - d = (di*v) - sum; - S += (1.0/(di*(di-1.0))) * d * d; - ix += stride; - } - return S / n; -} diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/main.c b/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/main.c new file mode 100644 index 000000000000..2336144c61eb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/src/main.c @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dvarianceyc.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +* +* ## Method +* +* - This implementation uses a one-pass algorithm, as proposed by Youngs and Cramer (1971). +* +* ## References +* +* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvarianceyc)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dvarianceyc_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a double-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvarianceyc_ndarray)( const CBLAS_INT N, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double sum; + double di; + double S; + double v; + double n; + double d; + + n = (double)N - correction; + if ( N <= 0 || n <= 0.0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0; + } + ix = offsetX; + sum = X[ ix ]; + ix += strideX; + S = 0.0; + for ( i = 2; i <= N; i++ ) { + di = (double)i; + v = X[ ix ]; + sum += v; + d = (di*v) - sum; + S += (1.0/(di*(di-1.0))) * d * d; + ix += strideX; + } + return S / n; +} diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.js index 142b3cbfc1ec..8d17ca5d2e75 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvarianceyc = require( './../lib/dvarianceyc.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, 2 ); + v = dvarianceyc( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, -2 ); + v = dvarianceyc( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -181,7 +176,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -197,9 +191,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvarianceyc( N, 1, x1, 2 ); + v = dvarianceyc( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.native.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.native.js index 25072750c664..596300d4e4cb 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.dvarianceyc.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, 2 ); + v = dvarianceyc( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, -2 ); + v = dvarianceyc( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -206,9 +200,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvarianceyc( N, 1, x1, 2 ); + v = dvarianceyc( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.js index b6de2c690f6c..1e59205d3589 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvarianceyc = require( './../lib/ndarray.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, 2, 0 ); + v = dvarianceyc( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, -2, 6 ); + v = dvarianceyc( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -179,7 +174,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -193,9 +187,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, 2, 1 ); + v = dvarianceyc( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.native.js index 612cc6f84168..b807dff5f972 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarianceyc/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, 2, 0 ); + v = dvarianceyc( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, -2, 6 ); + v = dvarianceyc( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -188,7 +183,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -202,9 +196,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvarianceyc( N, 1, x, 2, 1 ); + v = dvarianceyc( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/README.md b/lib/node_modules/@stdlib/stats/base/dvarmtk/README.md index 0e5c661833ee..d8ff6a24e216 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var dvarmtk = require( '@stdlib/stats/base/dvarmtk' ); ``` -#### dvarmtk( N, mean, correction, x, stride ) +#### dvarmtk( N, mean, correction, x, strideX ) Computes the [variance][variance] of a double-precision floating-point strided array `x` provided a known `mean` and using a one-pass textbook algorithm. @@ -117,18 +117,16 @@ The function has the following parameters: - **mean**: mean. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float64Array`][@stdlib/array/float64]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = dvarmtk( N, 1.25, 1, x, 2 ); +var v = dvarmtk( 4, 1.25, 1, x, 2 ); // returns 6.25 ``` @@ -138,18 +136,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dvarmtk( N, 1.25, 1, x1, 2 ); +var v = dvarmtk( 4, 1.25, 1, x1, 2 ); // returns 6.25 ``` -#### dvarmtk.ndarray( N, mean, correction, x, stride, offset ) +#### dvarmtk.ndarray( N, mean, correction, x, strideX, offsetX ) Computes the [variance][variance] of a double-precision floating-point strided array provided a known `mean` and using a one-pass textbook algorithm and alternative indexing semantics. @@ -164,18 +159,16 @@ var v = dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = dvarmtk.ndarray( N, 1.25, 1, x, 2, 1 ); +var v = dvarmtk.ndarray( 4, 1.25, 1, x, 2, 1 ); // returns 6.25 ``` @@ -201,18 +194,12 @@ var v = dvarmtk.ndarray( N, 1.25, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvarmtk = require( '@stdlib/stats/base/dvarmtk' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvarmtk( x.length, 0.0, 1, x, 1 ); @@ -223,6 +210,127 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dvarmtk.h" +``` + +#### stdlib_strided_dvarmtk( N, mean, correction, \*X, strideX ) + +Computes the [variance][variance] of a double-precision floating-point strided array provided a known `mean` and using a one-pass textbook algorithm. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvarmtk( 3, 1.0/3.0, 1.0, x, 1 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **mean**: `[in] double` mean. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dvarmtk( const CBLAS_INT N, const double mean, const double correction, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dvarmtk_ndarray( N, mean, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a double-precision floating-point strided array provided a known `mean` and using a one-pass textbook algorithm and alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 2.0 }; + +double v = stdlib_strided_dvarmtk_ndarray( 3, 1.0/3.0, 1.0, x, 1, 0 ); +// returns ~4.3333 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **mean**: `[in] double` mean. +- **correction**: `[in] double` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dvarmtk_ndarray( const CBLAS_INT N, const double mean, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dvarmtk.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + double v = stdlib_strided_dvarmtk( N, 4.5, 1, x, strideX ); + + // Print the result: + printf( "sample variance: %lf\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.js index a545772d33e7..3d20f78923a8 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvarmtk = require( './../lib/dvarmtk.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvarmtk = require( './../lib/dvarmtk.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.native.js index 1f87165604de..e7b8f4fe4d6f 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvarmtk = tryRequire( resolve( __dirname, './../lib/dvarmtk.native.js' ) ); var opts = { 'skip': ( dvarmtk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.js index 7a76f094d3c4..a0035b477c79 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var pkg = require( './../package.json' ).name; var dvarmtk = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var dvarmtk = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.native.js index 44638abcb51b..8bdec6de5b71 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var dvarmtk = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( dvarmtk instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/c/benchmark.length.c index c388a5baf643..9693b11e65ec 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; double x[ len ]; double v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dvarmtk( len, 0.0, 1, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dvarmtk_ndarray( len, 0.0, 1, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/repl.txt index a56658e6c2ef..0232de9ae8f6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, mean, correction, x, stride ) +{{alias}}( N, mean, correction, x, strideX ) Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -34,8 +34,8 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -49,20 +49,19 @@ > {{alias}}( x.length, 1.0/3.0, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 1.0/3.0, 1, x, 2 ) + > {{alias}}( 3, 1.0/3.0, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 1.0/3.0, 1, x1, 2 ) + > {{alias}}( 3, 1.0/3.0, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, mean, correction, x, stride, offset ) + +{{alias}}.ndarray( N, mean, correction, x, strideX, offsetX ) Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm and alternative indexing semantics. @@ -94,10 +93,10 @@ x: Float64Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -114,8 +113,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1.0/3.0, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1.0/3.0, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/types/index.d.ts index 3ffcf3f009a4..67b843567f96 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/docs/types/index.d.ts @@ -29,7 +29,7 @@ interface Routine { * @param mean - mean * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -40,7 +40,7 @@ interface Routine { * var v = dvarmtk( x.length, 1.0/3.0, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, mean: number, correction: number, x: Float64Array, stride: number ): number; + ( N: number, mean: number, correction: number, x: Float64Array, strideX: number ): number; /** * Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm and alternative indexing semantics. @@ -49,8 +49,8 @@ interface Routine { * @param mean - mean * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -61,7 +61,7 @@ interface Routine { * var v = dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, mean: number, correction: number, x: Float64Array, stride: number, offset: number ): number; + ndarray( N: number, mean: number, correction: number, x: Float64Array, strideX: number, offsetX: number ): number; } /** @@ -71,7 +71,7 @@ interface Routine { * @param mean - mean * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/c/example.c index 90fb728032bb..29e398d579eb 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dvarmtk.h" -#include #include int main( void ) { // Create a strided array: - double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - double v = stdlib_strided_dvarmtk( N, 4.5, 1, x, stride ); + double v = stdlib_strided_dvarmtk( N, 4.5, 1, x, strideX ); // Print the result: printf( "sample variance: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/index.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/index.js index 7930c818ba56..0c779aaeff6b 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var dvarmtk = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); console.log( x ); var v = dvarmtk( x.length, 0.0, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/include/stdlib/stats/base/dvarmtk.h b/lib/node_modules/@stdlib/stats/base/dvarmtk/include/stdlib/stats/base/dvarmtk.h index 37d3c1fbef4a..6bf37a80bba3 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/include/stdlib/stats/base/dvarmtk.h +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/include/stdlib/stats/base/dvarmtk.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DVARMTK_H #define STDLIB_STATS_BASE_DVARMTK_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. */ -double stdlib_strided_dvarmtk( const int64_t N, const double mean, const double correction, const double *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dvarmtk)( const CBLAS_INT N, const double mean, const double correction, const double *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dvarmtk_ndarray)( const CBLAS_INT N, const double mean, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.js index d0acc799b0fc..a5f08a386bba 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -27,7 +33,7 @@ * @param {number} mean - mean * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example @@ -38,32 +44,8 @@ * var v = dvarmtk( x.length, 1.0/3.0, 1, x, 1 ); * // returns ~4.3333 */ -function dvarmtk( N, mean, correction, x, stride ) { - var ix; - var M2; - var d; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - M2 = 0.0; - for ( i = 0; i < N; i++ ) { - d = x[ ix ] - mean; - M2 += d * d; - ix += stride; - } - return M2 / n; +function dvarmtk( N, mean, correction, x, strideX ) { + return ndarray( N, mean, correction, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.native.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.native.js index ecd7c7cae8f4..383d13095ea6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/dvarmtk.native.js @@ -32,7 +32,7 @@ var addon = require( './../src/addon.node' ); * @param {number} mean - mean * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example @@ -43,8 +43,8 @@ var addon = require( './../src/addon.node' ); * var v = dvarmtk( x.length, 1.0/3.0, 1, x, 1 ); * // returns ~4.3333 */ -function dvarmtk( N, mean, correction, x, stride ) { - return addon( N, mean, correction, x, stride ); +function dvarmtk( N, mean, correction, x, strideX ) { + return addon( N, mean, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/index.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/index.js index 0c9e81a7aba2..2cc878b71104 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/index.js @@ -34,13 +34,11 @@ * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dvarmtk = require( '@stdlib/stats/base/dvarmtk' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvarmtk.ndarray( N, 1.25, 1, x, 2, 1 ); +* var v = dvarmtk.ndarray( 4, 1.25, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.js index e94c7bc92446..8f3bf6aa262f 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.js @@ -27,21 +27,19 @@ * @param {number} mean - mean * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvarmtk( N, 1.25, 1, x, 2, 1 ); +* var v = dvarmtk( 4, 1.25, 1, x, 2, 1 ); * // returns 6.25 */ -function dvarmtk( N, mean, correction, x, stride, offset ) { +function dvarmtk( N, mean, correction, x, strideX, offsetX ) { var ix; var M2; var d; @@ -52,15 +50,15 @@ function dvarmtk( N, mean, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - ix = offset; + ix = offsetX; M2 = 0.0; for ( i = 0; i < N; i++ ) { d = x[ ix ] - mean; M2 += d * d; - ix += stride; + ix += strideX; } return M2 / n; } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.native.js index 36f05e6d54b9..83156ff2197d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float64Array = require( '@stdlib/array/float64' ); -var addon = require( './dvarmtk.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -33,27 +32,20 @@ var addon = require( './dvarmtk.native.js' ); * @param {number} mean - mean * @param {number} correction - degrees of freedom adjustment * @param {Float64Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = dvarmtk( N, 1.25, 1, x, 2, 1 ); +* var v = dvarmtk( 4, 1.25, 1, x, 2, 1 ); * // returns 6.25 */ -function dvarmtk( N, mean, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, mean, correction, view, stride ); +function dvarmtk( N, mean, correction, x, strideX, offsetX ) { + return addon.ndarray( N, mean, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/manifest.json b/lib/node_modules/@stdlib/stats/base/dvarmtk/manifest.json index 9ed8de013695..86308d31795d 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dvarmtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,31 +50,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dvarmtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dvarmtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/dvarmtk/src/addon.c index a862aed77eaa..889bb6f237a6 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/src/addon.c @@ -17,12 +17,13 @@ */ #include "stdlib/stats/base/dvarmtk.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" -#include "stdlib/napi/argv_double.h" #include "stdlib/napi/argv_strided_float64array.h" #include "stdlib/napi/create_double.h" +#include "stdlib/napi/argv_double.h" #include /** @@ -35,12 +36,31 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 4 ); STDLIB_NAPI_ARGV_DOUBLE( env, mean, argv, 1 ); STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 3 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dvarmtk( N, mean, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ) + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvarmtk)( N, mean, correction, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, correction, argv, 2 ); + STDLIB_NAPI_ARGV_DOUBLE( env, mean, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 5 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dvarmtk_ndarray)( N, mean, correction, X, strideX, offsetX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/src/dvarmtk.c b/lib/node_modules/@stdlib/stats/base/dvarmtk/src/dvarmtk.c deleted file mode 100644 index 371f7071d8ab..000000000000 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/src/dvarmtk.c +++ /dev/null @@ -1,58 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/dvarmtk.h" -#include - -/** -* Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. -* -* @param N number of indexed elements -* @param mean mean -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -double stdlib_strided_dvarmtk( const int64_t N, const double mean, const double correction, const double *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double M2; - double n; - double d; - - n = (double)N - correction; - if ( N <= 0 || n <= 0.0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - M2 = 0.0; - for ( i = 0; i < N; i++ ) { - d = X[ ix ] - mean; - M2 += d * d; - ix += stride; - } - return M2 / n; -} diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/src/main.c b/lib/node_modules/@stdlib/stats/base/dvarmtk/src/main.c new file mode 100644 index 000000000000..42673e608b73 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/src/main.c @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dvarmtk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm. +* +* @param N number of indexed elements +* @param mean mean +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvarmtk)( const CBLAS_INT N, const double mean, const double correction, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dvarmtk_ndarray)( N, mean, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a double-precision floating-point strided array provided a known mean and using a one-pass textbook algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param mean mean +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dvarmtk_ndarray)( const CBLAS_INT N, const double mean, const double correction, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double M2; + double n; + double d; + + n = (double)N - correction; + if ( N <= 0 || n <= 0.0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0; + } + ix = offsetX; + M2 = 0.0; + for ( i = 0; i < N; i++ ) { + d = X[ ix ] - mean; + M2 += d * d; + ix += strideX; + } + return M2 / n; +} diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.js index 2dcadb58d23a..65b5793cbabf 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvarmtk = require( './../lib/dvarmtk.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, 2 ); + v = dvarmtk( 4, 1.25, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, -2 ); + v = dvarmtk( 4, 1.25, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -181,7 +176,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -197,9 +191,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvarmtk( N, 1.25, 1, x1, 2 ); + v = dvarmtk( 4, 1.25, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.native.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.native.js index 5a5a9e78ff19..0f3607d9a275 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.dvarmtk.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, 2 ); + v = dvarmtk( 4, 1.25, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, -2 ); + v = dvarmtk( 4, 1.25, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -206,9 +200,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dvarmtk( N, 1.25, 1, x1, 2 ); + v = dvarmtk( 4, 1.25, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.js index bf17949ff60a..38024555ab27 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var dvarmtk = require( './../lib/ndarray.js' ); @@ -121,7 +120,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -136,15 +134,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, 2, 0 ); + v = dvarmtk( 4, 1.25, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -159,8 +155,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, -2, 6 ); + v = dvarmtk( 4, 1.25, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -179,7 +174,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -193,9 +187,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, 2, 1 ); + v = dvarmtk( 4, 1.25, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.native.js index ed8e56cce9b6..a78a7830c1e5 100644 --- a/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dvarmtk/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -130,7 +129,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -145,15 +143,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, 2, 0 ); + v = dvarmtk( 4, 1.25, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,8 +164,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, -2, 6 ); + v = dvarmtk( 4, 1.25, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -188,7 +183,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -202,9 +196,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = dvarmtk( N, 1.25, 1, x, 2, 1 ); + v = dvarmtk( 4, 1.25, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/lib/index.js b/lib/node_modules/@stdlib/stats/base/lib/index.js index 4ed422eeeebf..01a3d58b5968 100644 --- a/lib/node_modules/@stdlib/stats/base/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/lib/index.js @@ -72,24 +72,6 @@ setReadOnly( ns, 'cumin', require( '@stdlib/stats/base/cumin' ) ); */ setReadOnly( ns, 'cuminabs', require( '@stdlib/stats/base/cuminabs' ) ); -/** -* @name dcumax -* @memberof ns -* @readonly -* @type {Function} -* @see {@link module:@stdlib/stats/base/dcumax} -*/ -setReadOnly( ns, 'dcumax', require( '@stdlib/stats/base/dcumax' ) ); - -/** -* @name dcumaxabs -* @memberof ns -* @readonly -* @type {Function} -* @see {@link module:@stdlib/stats/base/dcumaxabs} -*/ -setReadOnly( ns, 'dcumaxabs', require( '@stdlib/stats/base/dcumaxabs' ) ); - /** * @name dcumin * @memberof ns @@ -117,15 +99,6 @@ setReadOnly( ns, 'dcuminabs', require( '@stdlib/stats/base/dcuminabs' ) ); */ setReadOnly( ns, 'dists', require( '@stdlib/stats/base/dists' ) ); -/** -* @name dmax -* @memberof ns -* @readonly -* @type {Function} -* @see {@link module:@stdlib/stats/base/dmax} -*/ -setReadOnly( ns, 'dmax', require( '@stdlib/stats/base/dmax' ) ); - /** * @name dmaxabs * @memberof ns diff --git a/lib/node_modules/@stdlib/stats/base/max-by/README.md b/lib/node_modules/@stdlib/stats/base/max-by/README.md index 0cfd4a68734b..96c7229df2f2 100644 --- a/lib/node_modules/@stdlib/stats/base/max-by/README.md +++ b/lib/node_modules/@stdlib/stats/base/max-by/README.md @@ -48,7 +48,7 @@ var v = maxBy( x.length, x, 1, accessor ); The function has the following parameters: - **N**: number of indexed elements. -- **x**: input [`Array`][mdn-array], [`typed array`][mdn-typed-array], or an array-like object (excluding strings and functions). +- **x**: input [`Array`][mdn-array], [`typed array`][mdn-typed-array], or an array-like object (excluding strings and functions). - **stride**: index increment. - **clbk**: callback function. - **thisArg**: execution context (_optional_). @@ -162,7 +162,7 @@ var v = maxBy.ndarray( 3, x, 1, x.length-3, accessor ); - If `N <= 0`, both functions return `NaN`. - A provided callback function should return a numeric value. - If a provided callback function does not return any value (or equivalently, explicitly returns `undefined`), the value is **ignored**. -- When possible, prefer using [`dmax`][@stdlib/stats/base/dmax], [`smax`][@stdlib/stats/base/smax], and/or [`max`][@stdlib/stats/base/max], as, depending on the environment, these interfaces are likely to be significantly more performant. +- When possible, prefer using [`dmax`][@stdlib/stats/strided/dmax], [`smax`][@stdlib/stats/base/smax], and/or [`max`][@stdlib/stats/base/max], as, depending on the environment, these interfaces are likely to be significantly more performant.
@@ -202,7 +202,7 @@ console.log( v ); ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/max`][@stdlib/stats/base/max]: calculate the maximum value of a strided array. - [`@stdlib/stats/base/min-by`][@stdlib/stats/base/min-by]: calculate the minimum value of a strided array via a callback function. - [`@stdlib/stats/base/nanmax-by`][@stdlib/stats/base/nanmax-by]: calculate the maximum value of a strided array via a callback function, ignoring NaN values. @@ -222,7 +222,7 @@ console.log( v ); -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/max diff --git a/lib/node_modules/@stdlib/stats/base/max/README.md b/lib/node_modules/@stdlib/stats/base/max/README.md index 363dbdf9372a..b40881e618d3 100644 --- a/lib/node_modules/@stdlib/stats/base/max/README.md +++ b/lib/node_modules/@stdlib/stats/base/max/README.md @@ -120,7 +120,7 @@ var v = max.ndarray( N, x, 2, 1 ); ## Notes - If `N <= 0`, both functions return `NaN`. -- Depending on the environment, the typed versions ([`dmax`][@stdlib/stats/base/dmax], [`smax`][@stdlib/stats/base/smax], etc.) are likely to be significantly more performant. +- Depending on the environment, the typed versions ([`dmax`][@stdlib/stats/strided/dmax], [`smax`][@stdlib/stats/base/smax], etc.) are likely to be significantly more performant.
@@ -163,7 +163,7 @@ console.log( v ); ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/min`][@stdlib/stats/base/min]: calculate the minimum value of a strided array. - [`@stdlib/stats/base/nanmax`][@stdlib/stats/base/nanmax]: calculate the maximum value of a strided array, ignoring NaN values. - [`@stdlib/stats/base/smax`][@stdlib/stats/base/smax]: calculate the maximum value of a single-precision floating-point strided array. @@ -182,7 +182,7 @@ console.log( v ); -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/min]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/min diff --git a/lib/node_modules/@stdlib/stats/base/scumax/README.md b/lib/node_modules/@stdlib/stats/base/scumax/README.md index eb5b8c3c6687..4aaa627674f4 100644 --- a/lib/node_modules/@stdlib/stats/base/scumax/README.md +++ b/lib/node_modules/@stdlib/stats/base/scumax/README.md @@ -18,6 +18,8 @@ limitations under the License. --> + + # scumax > Calculate the cumulative maximum of single-precision floating-point strided array elements. @@ -108,7 +110,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative maximum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -210,7 +212,7 @@ The function accepts the following arguments: void stdlib_strided_scumax( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); ``` -#### stdlib_strided_scumax_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY) +#### stdlib_strided_scumax_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) Computes the cumulative maximum of single-precision floating-point strided array elements using alternative indexing semantics. @@ -302,7 +304,7 @@ int main( void ) { ## See Also - [`@stdlib/stats/base/cumax`][@stdlib/stats/base/cumax]: calculate the cumulative maximum of a strided array. -- [`@stdlib/stats/base/dcumax`][@stdlib/stats/base/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. +- [`@stdlib/stats/strided/dcumax`][@stdlib/stats/strided/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. - [`@stdlib/stats/base/scumin`][@stdlib/stats/base/scumin]: calculate the cumulative minimum of single-precision floating-point strided array elements.
@@ -321,7 +323,7 @@ int main( void ) { [@stdlib/stats/base/cumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumax -[@stdlib/stats/base/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumax +[@stdlib/stats/strided/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumax [@stdlib/stats/base/scumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumin diff --git a/lib/node_modules/@stdlib/stats/base/scumax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/scumax/docs/repl.txt index d9c3e2737913..addf98ae0640 100644 --- a/lib/node_modules/@stdlib/stats/base/scumax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/scumax/docs/repl.txt @@ -20,13 +20,13 @@ Input array. strideX: integer - Stride Length for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Stride Length for `y`. + Stride length for `y`. Returns ------- @@ -75,7 +75,7 @@ Input array. strideX: integer - Stride Length for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -84,7 +84,7 @@ Output array. strideY: integer - Stride Length for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. diff --git a/lib/node_modules/@stdlib/stats/base/scumax/src/addon.c b/lib/node_modules/@stdlib/stats/base/scumax/src/addon.c index b3215c3e57b9..7bf3289ebbda 100644 --- a/lib/node_modules/@stdlib/stats/base/scumax/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/scumax/src/addon.c @@ -20,6 +20,7 @@ #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/argv_strided_float32array.h" #include @@ -37,7 +38,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); - stdlib_strided_scumax( N, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_scumax)( N, X, strideX, Y, strideY ); return NULL; } @@ -57,7 +58,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); - stdlib_strided_scumax_ndarray( N, X, strideX, offsetX, Y, strideY, offsetY ); + API_SUFFIX(stdlib_strided_scumax_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); return NULL; } diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/scumaxabs/README.md index 7ade5f2c90e2..4a9d10786823 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/README.md +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/README.md @@ -54,11 +54,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -108,7 +108,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum absolute value of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative maximum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -141,20 +141,14 @@ scumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var scumaxabs = require( '@stdlib/stats/base/scumaxabs' ); -var y; -var x; -var i; - -x = new Float32Array( 10 ); -y = new Float32Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); +var y = new Float32Array( x.length ); console.log( x ); console.log( y ); @@ -166,6 +160,132 @@ console.log( y ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/scumaxabs.h" +``` + +#### stdlib_strided_scumaxabs( N, \*X, strideX, \*Y, strideY ) + +Computes the cumulative maximum absolute value of single-precision floating-point strided array elements. + +```c +const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scumaxabs( 4, x, 2, y, -2 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scumaxabs( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_scumaxabs_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + +Computes the cumulative maximum absolute value of single-precision floating-point strided array elements using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scumaxabs_ndarray( 4, x, 2, 0, y, -2, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scumaxabs_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/scumaxabs.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative maximum absolute value: + stdlib_strided_scumaxabs( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
@@ -181,7 +301,7 @@ console.log( y ); ## See Also - [`@stdlib/stats/base/cumaxabs`][@stdlib/stats/base/cumaxabs]: calculate the cumulative maximum absolute value of a strided array. -- [`@stdlib/stats/base/dcumaxabs`][@stdlib/stats/base/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. +- [`@stdlib/stats/strided/dcumaxabs`][@stdlib/stats/strided/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. - [`@stdlib/stats/base/scumax`][@stdlib/stats/base/scumax]: calculate the cumulative maximum of single-precision floating-point strided array elements. - [`@stdlib/stats/base/scuminabs`][@stdlib/stats/base/scuminabs]: calculate the cumulative minimum absolute value of single-precision floating-point strided array elements. @@ -201,7 +321,7 @@ console.log( y ); [@stdlib/stats/base/cumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumaxabs -[@stdlib/stats/base/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumaxabs +[@stdlib/stats/strided/dcumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumaxabs [@stdlib/stats/base/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumax diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.js index 82398dc1f0e7..b6f45a54ba58 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var scumaxabs = require( './../lib/scumaxabs.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var scumaxabs = require( './../lib/scumaxabs.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.native.js index 32e449882464..1afedec83a0b 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -36,6 +36,9 @@ var scumaxabs = tryRequire( resolve( __dirname, './../lib/scumaxabs.native.js' ) var opts = { 'skip': ( scumaxabs instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.js index fb37fb74fd29..990341f028c2 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var scumaxabs = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var scumaxabs = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.native.js index 94455ec12af2..14c4755c7f62 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/benchmark.ndarray.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -36,6 +36,9 @@ var scumaxabs = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( scumaxabs instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/c/benchmark.length.c index ed32e9bdf31f..1d0cb614f0cf 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scumaxabs_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/scumaxabs/docs/repl.txt index 859cd438cbb3..593c55554ddf 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative maximum absolute value of single-precision floating- point strided array elements. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,13 +20,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -41,11 +41,10 @@ > {{alias}}( x.length, x, 1, y, 1 ) [ 1.0, 2.0, 2.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, y, 2 ) + > {{alias}}( 3, x, 2, y, 2 ) [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ] // Using view offsets: @@ -53,12 +52,12 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, y1, 1 ) + > {{alias}}( 3, x1, 2, y1, 1 ) [ 2.0, 2.0, 2.0 ] > y0 [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] + {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative maximum absolute value of single-precision floating- point strided array elements using alternative indexing semantics. @@ -76,7 +75,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -85,7 +84,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -106,8 +105,7 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 ) + > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] See Also diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/c/example.c index b0c3db4c3732..6c14e2b446a6 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/stats/base/scumaxabs.h" -#include #include -#include int main( void ) { // Create strided arrays: - float x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify stride lengths: - int64_t strideX = 2; - int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative maximum absolute value: stdlib_strided_scumaxabs( N, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/index.js index bbe24bdcbbd4..8744b695ba7a 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var scumaxabs = require( './../lib' ); -var y; -var x; -var i; - -x = new Float32Array( 10 ); -y = new Float32Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); +var y = new Float32Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/include/stdlib/stats/base/scumaxabs.h b/lib/node_modules/@stdlib/stats/base/scumaxabs/include/stdlib/stats/base/scumaxabs.h index e321b0e8f82b..b9702bd53f92 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/include/stdlib/stats/base/scumaxabs.h +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/include/stdlib/stats/base/scumaxabs.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SCUMAXABS_H #define STDLIB_STATS_BASE_SCUMAXABS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative maximum absolute value of single-precision floating-point strided array elements. */ -void stdlib_strided_scumaxabs( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scumaxabs)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative maximum absolute value of single-precision floating-point strided array elements using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scumaxabs_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/index.js index 1aa9570e16e8..23c87266898f 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scumaxabs( N, x, 1, y, 1 ); +* scumaxabs( x.length, x, 1, y, 1 ); * // y => [ 1.0, 2.0, 2.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var scumaxabs = require( '@stdlib/stats/base/scumaxabs' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* scumaxabs.ndarray( N, x, 2, 1, y, 1, 0 ); +* scumaxabs.ndarray( 4, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.js index 61cad0018816..6643194c63ba 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var absf = require( '@stdlib/math/base/special/absf' ); // MAIN // @@ -40,13 +40,11 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scumaxabs( N, x, 2, 1, y, 1, 0 ); +* var v = scumaxabs( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] */ function scumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { @@ -62,7 +60,7 @@ function scumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { ix = offsetX; iy = offsetY; - max = abs( x[ ix ] ); + max = absf( x[ ix ] ); y[ iy ] = max; iy += strideY; @@ -70,7 +68,7 @@ function scumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { if ( isnanf( max ) === false ) { for ( i; i < N; i++ ) { ix += strideX; - v = abs( x[ ix ] ); + v = absf( x[ ix ] ); if ( isnanf( v ) ) { max = v; break; diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.native.js index 14943adb206f..c3cf1859ccaf 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './scumaxabs.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -40,27 +39,15 @@ var addon = require( './scumaxabs.native.js' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scumaxabs( N, x, 2, 1, y, 1, 0 ); +* var v = scumaxabs( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] */ function scumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideY < 0 ) { - offsetY += (N-1) * strideY; - } - viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewY = new Float32Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len - addon( N, viewX, strideX, viewY, strideY ); + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.js index 196f202b882a..85444f7847e3 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -41,58 +41,14 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scumaxabs( N, x, 1, y, 1 ); +* var v = scumaxabs( x.length, x, 1, y, 1 ); * // returns [ 1.0, 2.0, 2.0 ] */ function scumaxabs( N, x, strideX, y, strideY ) { - var max; - var ix; - var iy; - var v; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - max = abs( x[ ix ] ); - y[ iy ] = max; - - iy += strideY; - i = 1; - if ( isnanf( max ) === false ) { - for ( i; i < N; i++ ) { - ix += strideX; - v = abs( x[ ix ] ); - if ( isnanf( v ) ) { - max = v; - break; - } - if ( v > max ) { - max = v; - } - y[ iy ] = max; - iy += strideY; - } - } - if ( isnanf( max ) ) { - for ( i; i < N; i++ ) { - y[ iy ] = max; - iy += strideY; - } - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.native.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.native.js index 82500500ee19..388a7551e979 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/lib/scumaxabs.native.js @@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scumaxabs( N, x, 1, y, 1 ); +* var v = scumaxabs( x.length, x, 1, y, 1 ); * // returns [ 1.0, 2.0, 2.0 ] */ function scumaxabs( N, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/manifest.json b/lib/node_modules/@stdlib/stats/base/scumaxabs/manifest.json index e5e7c12f76fe..890d09728a73 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,18 +28,20 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/scumaxabs.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nanf", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/absf", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -47,34 +50,56 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/scumaxabs.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nanf" + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf" ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/scumaxabs.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nanf" + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/scumaxabs/src/addon.c index b76a3a4c6380..3e55634c1dea 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/scumaxabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -37,8 +38,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); - stdlib_strided_scumaxabs( N, X, strideX, Y, strideY ); + API_SUFFIX(stdlib_strided_scumaxabs)( N, X, strideX, Y, strideY ); return NULL; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_scumaxabs_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/src/main.c b/lib/node_modules/@stdlib/stats/base/scumaxabs/src/main.c new file mode 100644 index 000000000000..f8875d80ac18 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/scumaxabs.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/special/absf.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative maximum absolute value of single-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void API_SUFFIX(stdlib_strided_scumaxabs)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scumaxabs_ndarray)( N, X, strideX, ox, Y, strideY, oy ); + return; +} + +/** +* Computes the cumulative maximum absolute value of single-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Y output array +* @param strideY Y stride length +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scumaxabs_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + float max; + float v; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + max = stdlib_base_absf( X[ ix ] ); + Y[ iy ] = max; + + iy += strideY; + i = 1; + if ( !stdlib_base_is_nanf( max ) ) { + for (; i < N; i++ ) { + ix += strideX; + v = stdlib_base_absf( X[ ix ] ); + if ( stdlib_base_is_nanf( v ) ) { + max = v; + break; + } + if ( v > max ) { + max = v; + } + Y[ iy ] = max; + iy += strideY; + } + } + if ( stdlib_base_is_nanf( max ) ) { + for (; i < N; i++ ) { + Y[ iy ] = max; + iy += strideY; + } + } + return; +} diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/src/scumaxabs.c b/lib/node_modules/@stdlib/stats/base/scumaxabs/src/scumaxabs.c deleted file mode 100644 index 58c94e0a4099..000000000000 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/src/scumaxabs.c +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/scumaxabs.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include -#include - -/** -* Computes the cumulative maximum absolute value of single-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scumaxabs( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - int64_t ix; - int64_t iy; - int64_t i; - float max; - float v; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - max = fabsf( X[ ix ] ); - Y[ iy ] = max; - - iy += strideY; - i = 1; - if ( !stdlib_base_is_nanf( max ) ) { - for (; i < N; i++ ) { - ix += strideX; - v = fabsf( X[ ix ] ); - if ( stdlib_base_is_nanf( v ) ) { - max = v; - break; - } - if ( v > max ) { - max = v; - } - Y[ iy ] = max; - iy += strideY; - } - } - if ( stdlib_base_is_nanf( max ) ) { - for (; i < N; i++ ) { - Y[ iy ] = max; - iy += strideY; - } - } - return; -} diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.js index f20609abed47..98e8cb46d663 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, 0, y, 1, 0 ); + scumaxabs( 3, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumaxabs( N, x, 1, 0, y, 2, 0 ); + scumaxabs( 3, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, -2, x.length-1, y, -1, 2 ); + scumaxabs( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -238,7 +231,6 @@ tape( 'the function supports negative strides', function test( t ) { tape( 'the function supports an `x` offset', function test( t ) { var expected; - var N; var x; var y; @@ -262,9 +254,8 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - scumaxabs( N, x, 2, 1, y, 1, 0 ); + scumaxabs( 4, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports an `x` offset', function test( t ) { tape( 'the function supports a `y` offset', function test( t ) { var expected; - var N; var x; var y; @@ -298,9 +288,8 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - scumaxabs( N, x, 1, 0, y, 2, 1 ); + scumaxabs( 4, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -312,7 +301,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -330,9 +318,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, 0, y, -1, 2 ); + scumaxabs( 3, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.native.js index ab9906f3764f..1a8132d813a3 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, 0, y, 1, 0 ); + scumaxabs( 3, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumaxabs( N, x, 1, 0, y, 2, 0 ); + scumaxabs( 3, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, -2, x.length-1, y, -1, 2 ); + scumaxabs( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - scumaxabs( N, x, 2, 1, y, 1, 0 ); + scumaxabs( 4, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - scumaxabs( N, x, 1, 0, y, 2, 1 ); + scumaxabs( 4, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -321,7 +310,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -339,9 +327,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, 0, y, -1, 2 ); + scumaxabs( 3, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.js index 81b849b45b5f..5981bd871fc3 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, y, 1 ); + scumaxabs( 3, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumaxabs( N, x, 1, y, 2 ); + scumaxabs( 3, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, -2, y, -1 ); + scumaxabs( 3, x, -2, y, -1 ); expected = new Float32Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, y, -1 ); + scumaxabs( 3, x, 2, y, -1 ); expected = new Float32Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float32Array([ @@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - scumaxabs( N, x1, -2, y1, 1 ); + scumaxabs( 3, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 6.0, 6.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.native.js b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.native.js index 44af1d08f49c..5ed692dba4d8 100644 --- a/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumaxabs/test/test.scumaxabs.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, y, 1 ); + scumaxabs( 3, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumaxabs( N, x, 1, y, 2 ); + scumaxabs( 3, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, -2, y, -1 ); + scumaxabs( 3, x, -2, y, -1 ); expected = new Float32Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - scumaxabs( N, x, 2, y, -1 ); + scumaxabs( 3, x, 2, y, -1 ); expected = new Float32Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float32Array([ @@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - scumaxabs( N, x1, -2, y1, 1 ); + scumaxabs( 3, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 6.0, 6.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumin/README.md b/lib/node_modules/@stdlib/stats/base/scumin/README.md index fa46b155be22..a9395cd5cd79 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/README.md +++ b/lib/node_modules/@stdlib/stats/base/scumin/README.md @@ -54,11 +54,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -108,7 +108,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative minimum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -141,20 +141,14 @@ scumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var scumin = require( '@stdlib/stats/base/scumin' ); -var y; -var x; -var i; - -x = new Float32Array( 10 ); -y = new Float32Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); +var y = new Float32Array( x.length ); console.log( x ); console.log( y ); @@ -166,6 +160,132 @@ console.log( y ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/scumin.h" +``` + +#### stdlib_strided_scumin( N, \*X, strideX, \*Y, strideY ) + +Computes the cumulative minimum of single-precision floating-point strided array elements. + +```c +const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scumin( 4, x, 2, y, -2 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scumin( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_scumin_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + +Computes the cumulative minimum of single-precision floating-point strided array elements using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scumin_ndarray( 4, x, 2, 0, y, -2, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scumin_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/scumin.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative minimum: + stdlib_strided_scumin( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.js index 209f95db0015..82a95b5f5a00 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var scumin = require( './../lib/scumin.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var scumin = require( './../lib/scumin.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.native.js index 8e8b9eb7f742..a26023e2361f 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -36,6 +36,9 @@ var scumin = tryRequire( resolve( __dirname, './../lib/scumin.native.js' ) ); var opts = { 'skip': ( scumin instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.js index cbbd1e623e65..7f37ec681910 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var scumin = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var scumin = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.native.js index 86438854966d..cff33c47f5b8 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/benchmark.ndarray.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -36,6 +36,9 @@ var scumin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( scumin instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/c/benchmark.length.c index 075ff95496d9..22a4d0e1c61e 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/scumin/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scumin_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/scumin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/scumin/docs/repl.txt index 1689c56d26ff..69e90e484a67 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/scumin/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative minimum of single-precision floating-point strided array elements. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,13 +20,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -41,11 +41,10 @@ > {{alias}}( x.length, x, 1, y, 1 ) [ 1.0, -2.0, -2.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, y, 2 ) + > {{alias}}( 3, x, 2, y, 2 ) [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ] // Using view offsets: @@ -53,12 +52,12 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, y1, 1 ) + > {{alias}}( 3, x1, 2, y1, 1 ) [ -2.0, -2.0, -2.0 ] > y0 [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ] + {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative minimum of single-precision floating-point strided array elements using alternative indexing semantics. @@ -76,7 +75,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -85,7 +84,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -106,8 +105,7 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 ) + > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ] See Also diff --git a/lib/node_modules/@stdlib/stats/base/scumin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/scumin/examples/c/example.c index 38c2f9642b39..5591ee482a68 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/scumin/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/stats/base/scumin.h" -#include #include -#include int main( void ) { // Create strided arrays: - float x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify stride lengths: - int64_t strideX = 2; - int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative minimum: stdlib_strided_scumin( N, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/stats/base/scumin/examples/index.js b/lib/node_modules/@stdlib/stats/base/scumin/examples/index.js index cb0647a6d30c..f5f24e86f65c 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var scumin = require( './../lib' ); -var y; -var x; -var i; - -x = new Float32Array( 10 ); -y = new Float32Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( randu()*100.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); +var y = new Float32Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/stats/base/scumin/include.gypi b/lib/node_modules/@stdlib/stats/base/scumin/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/scumin/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative minimum of single-precision floating-point strided array elements. */ -void stdlib_strided_scumin( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scumin)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative minimum of single-precision floating-point strided array elements using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scumin_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/scumin/lib/index.js b/lib/node_modules/@stdlib/stats/base/scumin/lib/index.js index 5586e56d769a..061b684d1ddb 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scumin( N, x, 1, y, 1 ); +* scumin( x.length, x, 1, y, 1 ); * // y => [ 1.0, -2.0, -2.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var scumin = require( '@stdlib/stats/base/scumin' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* scumin.ndarray( N, x, 2, 1, y, 1, 0 ); +* scumin.ndarray( 4, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.js index ca104af2e9b1..bfc52052310b 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.js @@ -40,13 +40,11 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scumin( N, x, 2, 1, y, 1, 0 ); +* var v = scumin( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] */ function scumin( N, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.native.js index fbe4aca2c82c..c014219f089e 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './scumin.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -40,27 +39,15 @@ var addon = require( './scumin.native.js' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scumin( N, x, 2, 1, y, 1, 0 ); +* var v = scumin( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] */ function scumin( N, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideY < 0 ) { - offsetY += (N-1) * strideY; - } - viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewY = new Float32Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len - addon( N, viewX, strideX, viewY, strideY ); + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.js b/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.js index 9345c3089792..a56aaa050385 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -41,58 +41,14 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scumin( N, x, 1, y, 1 ); +* var v = scumin( x.length, x, 1, y, 1 ); * // returns [ 1.0, -2.0, -2.0 ] */ function scumin( N, x, strideX, y, strideY ) { - var min; - var ix; - var iy; - var v; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - min = x[ ix ]; - y[ iy ] = min; - - iy += strideY; - i = 1; - if ( isnanf( min ) === false ) { - for ( i; i < N; i++ ) { - ix += strideX; - v = x[ ix ]; - if ( isnanf( v ) ) { - min = v; - break; - } - if ( v < min || ( v === min && isNegativeZerof( v ) ) ) { - min = v; - } - y[ iy ] = min; - iy += strideY; - } - } - if ( isnanf( min ) ) { - for ( i; i < N; i++ ) { - y[ iy ] = min; - iy += strideY; - } - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.native.js b/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.native.js index eb64296a84e9..b48a97aba623 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/lib/scumin.native.js @@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scumin( N, x, 1, y, 1 ); +* var v = scumin( x.length, x, 1, y, 1 ); * // returns [ 1.0, -2.0, -2.0 ] */ function scumin( N, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/stats/base/scumin/manifest.json b/lib/node_modules/@stdlib/stats/base/scumin/manifest.json index 552ac3b19354..ec1f8510708f 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/scumin/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,77 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/scumin.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/math/base/assert/is-nanf" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-negative-zerof" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nanf", "@stdlib/math/base/assert/is-negative-zerof" ] diff --git a/lib/node_modules/@stdlib/stats/base/scumin/src/addon.c b/lib/node_modules/@stdlib/stats/base/scumin/src/addon.c new file mode 100644 index 000000000000..bcab8f099a35 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/scumin/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/scumin.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_scumin)( N, X, strideX, Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_scumin_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/scumin/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/scumin/src/addon.cpp deleted file mode 100644 index 7f669ce07271..000000000000 --- a/lib/node_modules/@stdlib/stats/base/scumin/src/addon.cpp +++ /dev/null @@ -1,151 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/scumin.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_blas_ext_base_scumin { - - /** - * Computes the cumulative minimum of single-precision floating-point strided array elements. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Y`: output array - * - `strideY`: `Y` stride length - */ - napi_value node_scumin( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideY; - status = napi_get_value_int64( env, argv[ 4 ], &strideY ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t ylen; - void *Y; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &ylen, &Y, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - stdlib_strided_scumin( N, (float *)X, strideX, (float *)Y, strideY ); - - return nullptr; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scumin, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_blas_ext_base_scumin diff --git a/lib/node_modules/@stdlib/stats/base/scumin/src/main.c b/lib/node_modules/@stdlib/stats/base/scumin/src/main.c new file mode 100644 index 000000000000..f94f3a11b494 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/scumin/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/scumin.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/assert/is_negative_zerof.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative minimum of single-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void API_SUFFIX(stdlib_strided_scumin)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scumin_ndarray)( N, X, strideX, ox, Y, strideY, oy ); + return; +} + +/** +* Computes the cumulative minimum of single-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Y output array +* @param strideY Y stride length +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scumin_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + float min; + float v; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + min = X[ ix ]; + Y[ iy ] = min; + + iy += strideY; + i = 1; + if ( !stdlib_base_is_nanf( min ) ) { + for (; i < N; i++ ) { + ix += strideX; + v = X[ ix ]; + if ( stdlib_base_is_nanf( v ) ) { + min = v; + break; + } + if ( v < min || ( v == min && stdlib_base_is_negative_zerof( v ) ) ) { + min = v; + } + Y[ iy ] = min; + iy += strideY; + } + } + if ( stdlib_base_is_nanf( min ) ) { + for (; i < N; i++ ) { + Y[ iy ] = min; + iy += strideY; + } + } + return; +} diff --git a/lib/node_modules/@stdlib/stats/base/scumin/src/scumin.c b/lib/node_modules/@stdlib/stats/base/scumin/src/scumin.c deleted file mode 100644 index 070081b0b63f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/scumin/src/scumin.c +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/scumin.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include "stdlib/math/base/assert/is_negative_zerof.h" -#include - -/** -* Computes the cumulative minimum of single-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scumin( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - int64_t ix; - int64_t iy; - int64_t i; - float min; - float v; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - min = X[ ix ]; - Y[ iy ] = min; - - iy += strideY; - i = 1; - if ( !stdlib_base_is_nanf( min ) ) { - for (; i < N; i++ ) { - ix += strideX; - v = X[ ix ]; - if ( stdlib_base_is_nanf( v ) ) { - min = v; - break; - } - if ( v < min || ( v == min && stdlib_base_is_negative_zerof( v ) ) ) { - min = v; - } - Y[ iy ] = min; - iy += strideY; - } - } - if ( stdlib_base_is_nanf( min ) ) { - for (; i < N; i++ ) { - Y[ iy ] = min; - iy += strideY; - } - } - return; -} diff --git a/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.js index 8274e7a83c04..e9133373df5f 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, 0, y, 1, 0 ); + scumin( 3, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumin( N, x, 1, 0, y, 2, 0 ); + scumin( 3, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, -2, x.length-1, y, -1, 2 ); + scumin( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -238,7 +231,6 @@ tape( 'the function supports negative strides', function test( t ) { tape( 'the function supports an `x` offset', function test( t ) { var expected; - var N; var x; var y; @@ -262,9 +254,8 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - scumin( N, x, 2, 1, y, 1, 0 ); + scumin( 4, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] ); // eslint-disable-line max-len t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports an `x` offset', function test( t ) { tape( 'the function supports a `y` offset', function test( t ) { var expected; - var N; var x; var y; @@ -298,9 +288,8 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - scumin( N, x, 1, 0, y, 2, 1 ); + scumin( 4, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -312,7 +301,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -330,9 +318,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, 0, y, -1, 2 ); + scumin( 3, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.native.js index 3c851e7a52c2..742332948926 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, 0, y, 1, 0 ); + scumin( 3, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumin( N, x, 1, 0, y, 2, 0 ); + scumin( 3, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, -2, x.length-1, y, -1, 2 ); + scumin( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - scumin( N, x, 2, 1, y, 1, 0 ); + scumin( 4, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] ); // eslint-disable-line max-len t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - scumin( N, x, 1, 0, y, 2, 1 ); + scumin( 4, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -321,7 +310,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -339,9 +327,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, 0, y, -1, 2 ); + scumin( 3, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.js b/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.js index 5a3ca492e335..0941a75ed2b8 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, y, 1 ); + scumin( 3, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumin( N, x, 1, y, 2 ); + scumin( 3, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, -2, y, -1 ); + scumin( 3, x, -2, y, -1 ); expected = new Float32Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, y, -1 ); + scumin( 3, x, 2, y, -1 ); expected = new Float32Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float32Array([ @@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - scumin( N, x1, -2, y1, 1 ); + scumin( 3, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.native.js b/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.native.js index 557ad15bd368..bfc15cf5de16 100644 --- a/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.native.js +++ b/lib/node_modules/@stdlib/stats/base/scumin/test/test.scumin.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, y, 1 ); + scumin( 3, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scumin( N, x, 1, y, 2 ); + scumin( 3, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scumin( N, x, -2, y, -1 ); + scumin( 3, x, -2, y, -1 ); expected = new Float32Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - scumin( N, x, 2, y, -1 ); + scumin( 3, x, 2, y, -1 ); expected = new Float32Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float32Array([ @@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - scumin( N, x1, -2, y1, 1 ); + scumin( 3, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/README.md b/lib/node_modules/@stdlib/stats/base/scuminabs/README.md index 6c08a6d35ca9..835d95b79ca9 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/README.md +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/README.md @@ -54,11 +54,11 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. -- **strideY**: index increment for `y`. +- **strideY**: stride length for `y`. -The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative minimum absolute value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative minimum absolute value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -108,7 +108,7 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum absolute value of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative minimum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -141,20 +141,14 @@ scuminabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var scuminabs = require( '@stdlib/stats/base/scuminabs' ); -var y; -var x; -var i; - -x = new Float32Array( 10 ); -y = new Float32Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); +var y = new Float32Array( x.length ); console.log( x ); console.log( y ); @@ -166,6 +160,133 @@ console.log( y ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/scuminabs.h" +``` + +#### stdlib_strided_scuminabs( N, \*X, strideX, \*Y, strideY ) + +Computes the cumulative minumum absolute value of single-precision floating-point strided array elements. + +```c +const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scuminabs( 4, x, 2, y, -2 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_scuminabs( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_scuminabs_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY) + +Computes the cumulative minumum absolute value of single-precision floating-point strided array elements using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; +float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_scuminabs_ndarray( 4, x, 2, 0, y, -2, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_scuminabs_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/scuminabs.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative minumum absolute value: + stdlib_strided_scuminabs( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.js index 7fae59e43ad1..fa0eea7d43d6 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var scuminabs = require( './../lib/scuminabs.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var scuminabs = require( './../lib/scuminabs.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var y; - var x; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.native.js index 53588610f0a3..69554253f4cc 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -36,6 +36,9 @@ var scuminabs = tryRequire( resolve( __dirname, './../lib/scuminabs.native.js' ) var opts = { 'skip': ( scuminabs instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.js index 298e574aa2de..5ae76af75328 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name; var scuminabs = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,15 +46,8 @@ var scuminabs = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.native.js index c30783a52b33..d2b9725c47a6 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/benchmark.ndarray.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -36,6 +36,9 @@ var scuminabs = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( scuminabs instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float32Array( len ); - y = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float32Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/c/benchmark.length.c index 17c665a5545b..d18c9efcd6c8 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float y[ len ]; @@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + y[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_scuminabs_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -143,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/scuminabs/docs/repl.txt index b079282df8a9..a26002517d0a 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/docs/repl.txt @@ -3,8 +3,8 @@ Computes the cumulative minimum absolute value of single-precision floating- point strided array elements. - The `N` and `stride` parameters determine which elements in `x` and `y` are - accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -20,13 +20,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. y: Float32Array Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. Returns ------- @@ -41,11 +41,10 @@ > {{alias}}( x.length, x, 1, y, 1 ) [ 1.0, 1.0, 1.0 ] - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, y, 2 ) + > {{alias}}( 3, x, 2, y, 2 ) [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ] // Using view offsets: @@ -53,12 +52,12 @@ > var y0 = new {{alias:@stdlib/array/float32}}( x0.length ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, y1, 1 ) + > {{alias}}( 3, x1, 2, y1, 1 ) [ 2.0, 2.0, 1.0 ] > y0 [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ] + {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative minimum absolute value of single-precision floating- point strided array elements using alternative indexing semantics. @@ -76,7 +75,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -85,7 +84,7 @@ Output array. strideY: integer - Index increment for `y`. + Stride length for `y`. offsetY: integer Starting index for `y`. @@ -106,8 +105,7 @@ // Advanced indexing: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > y = new {{alias:@stdlib/array/float32}}( x.length ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 ) + > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ] See Also diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/scuminabs/examples/c/example.c index 39b213aeadc6..77bc33633950 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/examples/c/example.c @@ -17,27 +17,25 @@ */ #include "stdlib/stats/base/scuminabs.h" -#include #include -#include int main( void ) { // Create strided arrays: - float x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; - float y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + const float x[] = { 1.0f, 2.0f, -3.0f, 4.0f, -5.0f, 6.0f, 7.0f, 8.0f }; + float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify stride lengths: - int64_t strideX = 2; - int64_t strideY = -2; + const int strideX = 2; + const int strideY = -2; // Compute the cumulative minimum absolute value: stdlib_strided_scuminabs( N, x, strideX, y, strideY ); // Print the result: - for ( int64_t i = 0; i < 8; i++ ) { - printf( "y[ %"PRId64" ] = %f\n", i, y[ i ] ); + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %f\n", i, y[ i ] ); } } diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/scuminabs/examples/index.js index beecfea76164..f49a8c9d160e 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/examples/index.js @@ -18,20 +18,14 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var Float32Array = require( '@stdlib/array/float32' ); var scuminabs = require( './../lib' ); -var y; -var x; -var i; - -x = new Float32Array( 10 ); -y = new Float32Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); +var y = new Float32Array( x.length ); console.log( x ); console.log( y ); diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/include/stdlib/stats/base/scuminabs.h b/lib/node_modules/@stdlib/stats/base/scuminabs/include/stdlib/stats/base/scuminabs.h index 220b28d922a8..aad0ff74bac0 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/include/stdlib/stats/base/scuminabs.h +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/include/stdlib/stats/base/scuminabs.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SCUMINABS_H #define STDLIB_STATS_BASE_SCUMINABS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the cumulative minimum absolute value of single-precision floating-point strided array elements. */ -void stdlib_strided_scuminabs( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY ); +void API_SUFFIX(stdlib_strided_scuminabs)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative minimum absolute value of single-precision floating-point strided array elements using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_scuminabs_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/index.js index 927b1933216e..3071e225384a 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/index.js @@ -29,21 +29,18 @@ * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* scuminabs( N, x, 1, y, 1 ); +* scuminabs( x.length, x, 1, y, 1 ); * // y => [ 1.0, 1.0, 1.0 ] * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var scuminabs = require( '@stdlib/stats/base/scuminabs' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* scuminabs.ndarray( N, x, 2, 1, y, 1, 0 ); +* scuminabs.ndarray( 4, x, 2, 1, y, 1, 0 ); * // y => [ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] */ diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.js index ef419862ac64..948e2536a7c4 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var absf = require( '@stdlib/math/base/special/absf' ); // MAIN // @@ -40,13 +40,11 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scuminabs( N, x, 2, 1, y, 1, 0 ); +* var v = scuminabs( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] */ function scuminabs( N, x, strideX, offsetX, y, strideY, offsetY ) { @@ -62,7 +60,7 @@ function scuminabs( N, x, strideX, offsetX, y, strideY, offsetY ) { ix = offsetX; iy = offsetY; - min = abs( x[ ix ] ); + min = absf( x[ ix ] ); y[ iy ] = min; iy += strideY; @@ -70,7 +68,7 @@ function scuminabs( N, x, strideX, offsetX, y, strideY, offsetY ) { if ( isnanf( min ) === false ) { for ( i; i < N; i++ ) { ix += strideX; - v = abs( x[ ix ] ); + v = absf( x[ ix ] ); if ( isnanf( v ) ) { min = v; break; diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.native.js index 22fa6aa51f31..60dc69aaf2f3 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './scuminabs.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -40,27 +39,15 @@ var addon = require( './scuminabs.native.js' ); * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * var y = new Float32Array( x.length ); -* var N = floor( x.length / 2 ); * -* var v = scuminabs( N, x, 2, 1, y, 1, 0 ); +* var v = scuminabs( 4, x, 2, 1, y, 1, 0 ); * // returns [ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] */ function scuminabs( N, x, strideX, offsetX, y, strideY, offsetY ) { - var viewX; - var viewY; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideY < 0 ) { - offsetY += (N-1) * strideY; - } - viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewY = new Float32Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len - addon( N, viewX, strideX, viewY, strideY ); + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); return y; } diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.js b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.js index c810e436cced..979fa1e5c98f 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -41,58 +41,14 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scuminabs( N, x, 1, y, 1 ); +* var v = scuminabs( x.length, x, 1, y, 1 ); * // returns [ 1.0, 1.0, 1.0 ] */ function scuminabs( N, x, strideX, y, strideY ) { - var min; - var ix; - var iy; - var v; - var i; - - if ( N <= 0 ) { - return y; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - min = abs( x[ ix ] ); - y[ iy ] = min; - - iy += strideY; - i = 1; - if ( isnanf( min ) === false ) { - for ( i; i < N; i++ ) { - ix += strideX; - v = abs( x[ ix ] ); - if ( isnanf( v ) ) { - min = v; - break; - } - if ( v < min ) { - min = v; - } - y[ iy ] = min; - iy += strideY; - } - } - if ( isnanf( min ) ) { - for ( i; i < N; i++ ) { - y[ iy ] = min; - iy += strideY; - } - } - return y; + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, x, strideX, ox, y, strideY, oy ); } diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.native.js b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.native.js index af658e0f5833..3f77171edc3e 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.native.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/lib/scuminabs.native.js @@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float32Array( x.length ); -* var N = x.length; * -* var v = scuminabs( N, x, 1, y, 1 ); +* var v = scuminabs( x.length, x, 1, y, 1 ); * // returns [ 1.0, 1.0, 1.0 ] */ function scuminabs( N, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/manifest.json b/lib/node_modules/@stdlib/stats/base/scuminabs/manifest.json index ab1d56169a3b..af15e5d2624a 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,18 +27,79 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/scuminabs.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nanf" + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/scuminabs/src/addon.c new file mode 100644 index 000000000000..80604c48e58f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/scuminabs.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_scuminabs)( N, X, strideX, Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_scuminabs_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/scuminabs/src/addon.cpp deleted file mode 100644 index d45aa2d13b77..000000000000 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/src/addon.cpp +++ /dev/null @@ -1,151 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/scuminabs.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_blas_ext_base_scuminabs { - - /** - * Computes the cumulative minimum absolute value of single-precision floating-point strided array elements. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Y`: output array - * - `strideY`: `Y` stride length - */ - napi_value node_scuminabs( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideY; - status = napi_get_value_int64( env, argv[ 4 ], &strideY ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t ylen; - void *Y; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &ylen, &Y, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideY) >= (int64_t)ylen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - stdlib_strided_scuminabs( N, (float *)X, strideX, (float *)Y, strideY ); - - return nullptr; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_scuminabs, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_blas_ext_base_scuminabs diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/src/main.c b/lib/node_modules/@stdlib/stats/base/scuminabs/src/main.c new file mode 100644 index 000000000000..5e791f9e1beb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/scuminabs.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/special/absf.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative minimum absolute value of single-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void stdlib_strided_scuminabs( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_scuminabs_ndarray)( N, X, strideX, ox, Y, strideY, oy ); + return; +} + +/** +* Computes the cumulative minimum absolute value of single-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Y output array +* @param strideY Y stride length +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_scuminabs_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + float min; + float v; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + min = stdlib_base_absf( X[ ix ] ); + Y[ iy ] = min; + + iy += strideY; + i = 1; + if ( !stdlib_base_is_nanf( min ) ) { + for (; i < N; i++ ) { + ix += strideX; + v = stdlib_base_absf( X[ ix ] ); + if ( stdlib_base_is_nanf( v ) ) { + min = v; + break; + } + if ( v < min ) { + min = v; + } + Y[ iy ] = min; + iy += strideY; + } + } + if ( stdlib_base_is_nanf( min ) ) { + for (; i < N; i++ ) { + Y[ iy ] = min; + iy += strideY; + } + } + return; +} diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/src/scuminabs.c b/lib/node_modules/@stdlib/stats/base/scuminabs/src/scuminabs.c deleted file mode 100644 index c49d3eb6d776..000000000000 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/src/scuminabs.c +++ /dev/null @@ -1,80 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/scuminabs.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include -#include - -/** -* Computes the cumulative minimum absolute value of single-precision floating-point strided array elements. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Y output array -* @param strideY Y stride length -*/ -void stdlib_strided_scuminabs( const int64_t N, const float *X, const int64_t strideX, float *Y, const int64_t strideY ) { - int64_t ix; - int64_t iy; - int64_t i; - float min; - float v; - - if ( N <= 0 ) { - return; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideY < 0 ) { - iy = (1-N) * strideY; - } else { - iy = 0; - } - min = fabsf( X[ ix ] ); - Y[ iy ] = min; - - iy += strideY; - i = 1; - if ( !stdlib_base_is_nanf( min ) ) { - for (; i < N; i++ ) { - ix += strideX; - v = fabsf( X[ ix ] ); - if ( stdlib_base_is_nanf( v ) ) { - min = v; - break; - } - if ( v < min ) { - min = v; - } - Y[ iy ] = min; - iy += strideY; - } - } - if ( stdlib_base_is_nanf( min ) ) { - for (; i < N; i++ ) { - Y[ iy ] = min; - iy += strideY; - } - } - return; -} diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.js index df4d398225ad..e739da5141cd 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, 0, y, 1, 0 ); + scuminabs( 3, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scuminabs( N, x, 1, 0, y, 2, 0 ); + scuminabs( 3, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 1.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, -2, x.length-1, y, -1, 2 ); + scuminabs( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -238,7 +231,6 @@ tape( 'the function supports negative strides', function test( t ) { tape( 'the function supports an `x` offset', function test( t ) { var expected; - var N; var x; var y; @@ -262,9 +254,8 @@ tape( 'the function supports an `x` offset', function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - scuminabs( N, x, 2, 1, y, 1, 0 ); + scuminabs( 4, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports an `x` offset', function test( t ) { tape( 'the function supports a `y` offset', function test( t ) { var expected; - var N; var x; var y; @@ -298,9 +288,8 @@ tape( 'the function supports a `y` offset', function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - scuminabs( N, x, 1, 0, y, 2, 1 ); + scuminabs( 4, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -312,7 +301,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -330,9 +318,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, 0, y, -1, 2 ); + scuminabs( 3, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.native.js index b43f172484e6..4a343d7a7643 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, 0, y, 1, 0 ); + scuminabs( 3, x, 2, 0, y, 1, 0 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scuminabs( N, x, 1, 0, y, 2, 0 ); + scuminabs( 3, x, 1, 0, y, 2, 0 ); expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 1.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, -2, x.length-1, y, -1, 2 ); + scuminabs( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - scuminabs( N, x, 2, 1, y, 1, 0 ); + scuminabs( 4, x, 2, 1, y, 1, 0 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - scuminabs( N, x, 1, 0, y, 2, 1 ); + scuminabs( 4, x, 1, 0, y, 2, 1 ); expected = new Float32Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -321,7 +310,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -339,9 +327,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, 0, y, -1, 2 ); + scuminabs( 3, x, 2, 0, y, -1, 2 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.js b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.js index 8990e619233f..86f5222e2922 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, y, 1 ); + scuminabs( 3, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scuminabs( N, x, 1, y, 2 ); + scuminabs( 3, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 1.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, -2, y, -1 ); + scuminabs( 3, x, -2, y, -1 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, y, -1 ); + scuminabs( 3, x, 2, y, -1 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float32Array([ @@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - scuminabs( N, x1, -2, y1, 1 ); + scuminabs( 3, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.native.js b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.native.js index a3f464bc026c..8c41a4ce71d7 100644 --- a/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.native.js +++ b/lib/node_modules/@stdlib/stats/base/scuminabs/test/test.scuminabs.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, y, 1 ); + scuminabs( 3, x, 2, y, 1 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - scuminabs( N, x, 1, y, 2 ); + scuminabs( 3, x, 1, y, 2 ); expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 1.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, -2, y, -1 ); + scuminabs( 3, x, -2, y, -1 ); expected = new Float32Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float32Array([ 1.0, // 0 @@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - scuminabs( N, x, 2, y, -1 ); + scuminabs( 3, x, 2, y, -1 ); expected = new Float32Array( [ 1.0, 1.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float32Array([ @@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - scuminabs( N, x1, -2, y1, 1 ); + scuminabs( 3, x1, -2, y1, 1 ); expected = new Float32Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/README.md b/lib/node_modules/@stdlib/stats/base/sdsmeanors/README.md index b6735cf153ed..6deff1aff6f0 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/README.md +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var sdsmeanors = require( '@stdlib/stats/base/sdsmeanors' ); ``` -#### sdsmeanors( N, x, stride ) +#### sdsmeanors( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using ordinary recursive summation with extended accumulation. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sdsmeanors( N, x, 1 ); +var v = sdsmeanors( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = sdsmeanors( N, x, 2 ); +var v = sdsmeanors( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = sdsmeanors( N, x1, 2 ); +var v = sdsmeanors( 4, x1, 2 ); // returns 1.25 ``` -#### sdsmeanors.ndarray( N, x, stride, offset ) +#### sdsmeanors.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sdsmeanors.ndarray( N, x, 1, 0 ); +var v = sdsmeanors.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = sdsmeanors.ndarray( N, x, 2, 1 ); +var v = sdsmeanors.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -141,7 +132,7 @@ var v = sdsmeanors.ndarray( N, x, 2, 1 ); ## Notes - If `N <= 0`, both functions return `NaN`. -- Accumulated intermediate values are stored as double-precision floating-point numbers. +- Accumulated intermediate values are stored as double-precision floating-point numbers.
@@ -154,18 +145,12 @@ var v = sdsmeanors.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sdsmeanors = require( '@stdlib/stats/base/sdsmeanors' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = sdsmeanors( x.length, x, 1 ); @@ -176,6 +161,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/sdsmeanors.h" +``` + +#### stdlib_strided_sdsmeanors( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_sdsmeanors( 3, x, 1 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_sdsmeanors( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sdsmeanors_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_sdsmeanors_ndarray( 3, x, 1, 0 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_sdsmeanors_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/sdsmeanors.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + float v = stdlib_strided_sdsmeanors( N, x, strideX ); + + // Print the result: + printf( "mean: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.js index a3f5b93f46ff..39dbe2bcbea5 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sdsmeanors = require( './../lib/sdsmeanors.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var sdsmeanors = require( './../lib/sdsmeanors.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.native.js index 0fa9e3d76c8c..f7465ec74cbc 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var sdsmeanors = tryRequire( resolve( __dirname, './../lib/sdsmeanors.native.js' var opts = { 'skip': ( sdsmeanors instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.js index 36cdc219a591..3b5b803f982d 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sdsmeanors = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var sdsmeanors = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.native.js index 1135efb4f96b..5026b01d91c8 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var sdsmeanors = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sdsmeanors instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/c/benchmark.length.c index deb83fdf24c3..9ac69fff6c27 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sdsmeanors( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sdsmeanors_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/repl.txt index ed5adb0eafb5..6966b18f0ae3 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics. @@ -66,10 +63,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/types/index.d.ts index 111cf3c65b46..ede43b1f2ef9 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = sdsmeanors( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = sdsmeanors.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/c/example.c index b991da7c510b..de7d5f7d0607 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/sdsmeanors.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - float v = stdlib_strided_sdsmeanors( N, x, stride ); + float v = stdlib_strided_sdsmeanors( N, x, strideX ); // Print the result: printf( "mean: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/index.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/index.js index b215eb7442f4..75f620a0d0c8 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sdsmeanors = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = sdsmeanors( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/include/stdlib/stats/base/sdsmeanors.h b/lib/node_modules/@stdlib/stats/base/sdsmeanors/include/stdlib/stats/base/sdsmeanors.h index 21f64d838f45..60f91e7920f6 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/include/stdlib/stats/base/sdsmeanors.h +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/include/stdlib/stats/base/sdsmeanors.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SDSMEANORS_H #define STDLIB_STATS_BASE_SDSMEANORS_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. */ -float stdlib_strided_sdsmeanors( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sdsmeanors)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sdsmeanors_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/index.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/index.js index 21732c3598f1..3dc60c9f855b 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/index.js @@ -28,20 +28,17 @@ * var sdsmeanors = require( '@stdlib/stats/base/sdsmeanors' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sdsmeanors( N, x, 1 ); +* var v = sdsmeanors( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var sdsmeanors = require( '@stdlib/stats/base/sdsmeanors' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sdsmeanors.ndarray( N, x, 2, 1 ); +* var v = sdsmeanors.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.js index 1f1804c5f74c..2799997a7d76 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.js @@ -30,21 +30,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sdsmeanors( N, x, 2, 1 ); +* var v = sdsmeanors( 4, x, 2, 1 ); * // returns 1.25 */ -function sdsmeanors( N, x, stride, offset ) { +function sdsmeanors( N, x, strideX, offsetX ) { var sum; var ix; var i; @@ -52,14 +50,14 @@ function sdsmeanors( N, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; sum = 0.0; for ( i = 0; i < N; i++ ) { sum += x[ ix ]; - ix += stride; + ix += strideX; } return float64ToFloat32( sum / N ); } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.native.js index 87b3f66f2186..3f6da4b60419 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './sdsmeanors.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './sdsmeanors.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sdsmeanors( N, x, 2, 1 ); +* var v = sdsmeanors( 4, x, 2, 1 ); * // returns 1.25 */ -function sdsmeanors( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function sdsmeanors( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.js index a7093412036e..0d9cdd13c47f 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.js @@ -20,7 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -30,40 +31,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sdsmeanors( N, x, 1 ); +* var v = sdsmeanors( x.length, x, 1 ); * // returns ~0.3333 */ -function sdsmeanors( N, x, stride ) { - var sum; - var ix; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - for ( i = 0; i < N; i++ ) { - sum += x[ ix ]; - ix += stride; - } - return float64ToFloat32( sum / N ); +function sdsmeanors( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.native.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.native.js index 40d1e5c6e49c..3a464ad6cb4d 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.native.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/lib/sdsmeanors.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sdsmeanors( N, x, 1 ); +* var v = sdsmeanors( x.length, x, 1 ); * // returns ~0.3333 */ -function sdsmeanors( N, x, stride ) { - return addon( N, x, stride ); +function sdsmeanors( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/manifest.json b/lib/node_modules/@stdlib/stats/base/sdsmeanors/manifest.json index 75d6d0ccefb7..7a0fdb1d890b 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/sdsmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -47,31 +49,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/sdsmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/sdsmeanors.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/addon.c b/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/addon.c index c75bb935ad79..29e621c11a50 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/addon.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2025 The Stdlib Authors. +* Copyright (c) 2024 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/sdsmeanors.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sdsmeanors( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sdsmeanors)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sdsmeanors_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/main.c b/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/main.c new file mode 100644 index 000000000000..1a6c40e5bcbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/main.c @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sdsmeanors.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sdsmeanors)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sdsmeanors_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sdsmeanors_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double sum; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + ix = offsetX; + sum = 0.0; + for ( i = 0; i < N; i++ ) { + sum += (double)X[ ix ]; + ix += strideX; + } + return sum / (double)N; +} diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/sdsmeanors.c b/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/sdsmeanors.c deleted file mode 100644 index 2aa66825fc9f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/src/sdsmeanors.c +++ /dev/null @@ -1,52 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sdsmeanors.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation with extended accumulation. -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sdsmeanors( const int64_t N, const float *X, const int64_t stride ) { - double sum; - int64_t ix; - int64_t i; - - if ( N <= 0 ) { - return 0.0 / 0.0; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = 0.0; - for ( i = 0; i < N; i++ ) { - sum += (double)X[ ix ]; - ix += stride; - } - return sum / (double)N; -} diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.js index 55f06147d1e3..566b9a3bf7ea 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sdsmeanors = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, 2, 0 ); + v = sdsmeanors( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, -2, 6 ); + v = sdsmeanors( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, 2, 1 ); + v = sdsmeanors( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.native.js index a2a0450e14a0..5dde55cd38b8 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, 2, 0 ); + v = sdsmeanors( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, -2, 6 ); + v = sdsmeanors( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, 2, 1 ); + v = sdsmeanors( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.js index d6f973e34b25..f1c474ef2e83 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var sdsmeanors = require( './../lib/sdsmeanors.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, 2 ); + v = sdsmeanors( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, -2 ); + v = sdsmeanors( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sdsmeanors( N, x1, 2 ); + v = sdsmeanors( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.native.js b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.native.js index 059ffc76fb00..3265d338914e 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.native.js +++ b/lib/node_modules/@stdlib/stats/base/sdsmeanors/test/test.sdsmeanors.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, 2 ); + v = sdsmeanors( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sdsmeanors( N, x, -2 ); + v = sdsmeanors( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sdsmeanors( N, x1, 2 ); + v = sdsmeanors( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi b/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sdsnanmean( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp deleted file mode 100644 index d4114ff4f966..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sdsnanmean.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sdsnanmean { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_sdsnanmean( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sdsnanmean( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sdsnanmean, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sdsnanmean diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sdsnanmeanors( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp deleted file mode 100644 index e0608f28d7dd..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sdsnanmeanors.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sdsnanmeanors { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_sdsnanmeanors( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sdsnanmeanors( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sdsnanmeanors, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sdsnanmeanors diff --git a/lib/node_modules/@stdlib/stats/base/smax/README.md b/lib/node_modules/@stdlib/stats/base/smax/README.md index 36d2b8a16e2f..76c07a485228 100644 --- a/lib/node_modules/@stdlib/stats/base/smax/README.md +++ b/lib/node_modules/@stdlib/stats/base/smax/README.md @@ -270,7 +270,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/base/dmax`][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmax`][@stdlib/stats/strided/dmax]: calculate the maximum value of a double-precision floating-point strided array. - [`@stdlib/stats/base/max`][@stdlib/stats/base/max]: calculate the maximum value of a strided array. - [`@stdlib/stats/base/smin`][@stdlib/stats/base/smin]: calculate the minimum value of a single-precision floating-point strided array. - [`@stdlib/stats/base/snanmax`][@stdlib/stats/base/snanmax]: calculate the maximum value of a single-precision floating-point strided array, ignoring NaN values. @@ -289,7 +289,7 @@ int main( void ) { -[@stdlib/stats/base/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmax +[@stdlib/stats/strided/dmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmax [@stdlib/stats/base/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/max diff --git a/lib/node_modules/@stdlib/stats/base/smax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smax/docs/repl.txt index 447df52534d7..d2347e727493 100644 --- a/lib/node_modules/@stdlib/stats/base/smax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smax/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/smax/src/addon.c b/lib/node_modules/@stdlib/stats/base/smax/src/addon.c index efe83f11e005..32ba0d4bc8e6 100644 --- a/lib/node_modules/@stdlib/stats/base/smax/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/smax/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/smax.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smax( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smax)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smax_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smax_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smaxabs/docs/repl.txt index 9a100e107961..4527d2ec53e1 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smaxabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/smaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/smaxabs/src/addon.c index fa15e9dd1b47..4cdfa243f80f 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/smaxabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/smaxabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smaxabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smaxabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smaxabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smaxabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md b/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md index 2d3b6fa7e7b6..7f59ecdb503e 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' ); ``` -#### smaxabssorted( N, x, stride ) +#### smaxabssorted( N, x, strideX ) Computes the maximum absolute value of a sorted single-precision floating-point strided array `x`. @@ -56,18 +56,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: index increment for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = smaxabssorted( N, x, 2 ); +var v = smaxabssorted( 4, x, 2 ); // returns 4.0 ``` @@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smaxabssorted( N, x1, 2 ); +var v = smaxabssorted( 4, x1, 2 ); // returns 4.0 ``` -#### smaxabssorted.ndarray( N, x, stride, offset ) +#### smaxabssorted.ndarray( N, x, strideX, offsetX ) Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -102,18 +97,16 @@ var v = smaxabssorted.ndarray( x.length, x, 1, 0 ); The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = smaxabssorted.ndarray( N, x, 2, 1 ); +var v = smaxabssorted.ndarray( 4, x, 2, 1 ); // returns 4.0 ``` @@ -139,16 +132,13 @@ var v = smaxabssorted.ndarray( N, x, 2, 1 ); ```javascript -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = smaxabssorted( x.length, x, 1 ); @@ -159,6 +149,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smaxabssorted.h" +``` + +#### stdlib_strided_smaxabssorted( N, \*X, strideX ) + +Computes the maximum absolute value of a sorted single-precision floating-point strided array. + +```c +const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; + +float v = stdlib_strided_smaxabssorted( 4, x, 2 ); +// returns 7.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_smaxabssorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_smaxabssorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; + +float v = stdlib_strided_smaxabssorted_ndarray( 4, x, 2, 0 ); +// returns 7.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_smaxabssorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smaxabssorted.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the maximum absolute value: + float v = stdlib_strided_smaxabssorted( N, x, strideX ); + + // Print the result: + printf( "maxabs: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js index 2ac183eec251..de2b563e9575 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smaxabssorted = require( './../lib/smaxabssorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var smaxabssorted = require( './../lib/smaxabssorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js index e078637b4a9f..5eb7b502b0eb 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var smaxabssorted = tryRequire( resolve( __dirname, './../lib/smaxabssorted.nati var opts = { 'skip': ( smaxabssorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js index da66e78de0f3..16c697f6cb4f 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smaxabssorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var smaxabssorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js index 50677703e5d6..021d542282dc 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var smaxabssorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' var opts = { 'skip': ( smaxabssorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - (len/2); - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c index 4adecd1ce942..22f0fed7d4de 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smaxabssorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i - (len/2); + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smaxabssorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS; + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt index d8eb24b2245d..3b51ef2a5888 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the maximum absolute value of a sorted single-precision floating- point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,8 +22,8 @@ x: Float32Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,22 +37,19 @@ > {{alias}}( x.length, x, 1 ) 3.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 2.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) 3.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the maximum absolute value of a sorted single-precision floating- point strided array using alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float32Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 3.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts index 20111c7d9230..bebe407fc252 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum absolute value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = smaxabssorted( x.length, x, 1 ); * // returns 3.0 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns maximum absolute value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = smaxabssorted.ndarray( x.length, x, 1, 0 ); * // returns 3.0 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c index abbe77270ced..5defd829bff7 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/smaxabssorted.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 }; + const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the maximum absolute value: - float v = stdlib_strided_smaxabssorted( N, x, stride ); + float v = stdlib_strided_smaxabssorted( N, x, strideX ); // Print the result: printf( "maxabs: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js index 36fc67912ee4..7907b227a919 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var smaxabssorted = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - x.length; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = smaxabssorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi b/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the maximum absolute value of a sorted single-precision floating-point strided array. */ -float stdlib_strided_smaxabssorted( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_smaxabssorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js index 6c2bf70858db..2d0a5fe8bfdf 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js @@ -28,20 +28,17 @@ * var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' ); * * var x = new Float32Array( [ -1.0, -2.0, -3.0 ] ); -* var N = x.length; * -* var v = smaxabssorted( N, x, 1 ); +* var v = smaxabssorted( x.length, x, 1 ); * // returns 3.0 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smaxabssorted.ndarray( N, x, 2, 1 ); +* var v = smaxabssorted.ndarray( 4, x, 2, 1 ); * // returns 4.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js index f75720ed3aeb..ac460c8c0a06 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var absf = require( '@stdlib/math/base/special/absf' ); // MAIN // @@ -31,37 +31,35 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum absolute value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smaxabssorted( N, x, 2, 1 ); +* var v = smaxabssorted( 4, x, 2, 1 ); * // returns 4.0 */ -function smaxabssorted( N, x, stride, offset ) { +function smaxabssorted( N, x, strideX, offsetX ) { var v1; var v2; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return x[ 0 ]; } - v1 = x[ offset ]; - v2 = x[ offset + ((N-1)*stride) ]; + v1 = x[ offsetX ]; + v2 = x[ offsetX + ((N-1)*strideX) ]; if ( isnanf( v1 ) || isnanf( v2 ) ) { return NaN; } - v1 = abs( v1 ); - v2 = abs( v2 ); + v1 = absf( v1 ); + v2 = absf( v2 ); if ( v1 > v2 ) { return v1; } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js index 6c118eb57a89..70fb049038b9 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './smaxabssorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './smaxabssorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum absolute value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smaxabssorted( N, x, 2, 1 ); +* var v = smaxabssorted( 4, x, 2, 1 ); * // returns 4.0 */ -function smaxabssorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function smaxabssorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js index 601547599380..58d223b34851 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,44 +31,19 @@ var abs = require( '@stdlib/math/base/special/abs' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum absolute value * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ -1.0, -2.0, -3.0 ] ); -* var N = x.length; * -* var v = smaxabssorted( N, x, 1 ); +* var v = smaxabssorted( x.length, x, 1 ); * // returns 3.0 */ -function smaxabssorted( N, x, stride ) { - var v1; - var v2; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - v1 = x[ (1-N) * stride ]; - v2 = x[ 0 ]; - } else { - v1 = x[ 0 ]; - v2 = x[ (N-1) * stride ]; - } - if ( isnanf( v1 ) || isnanf( v2 ) ) { - return NaN; - } - v1 = abs( v1 ); - v2 = abs( v2 ); - if ( v1 > v2 ) { - return v1; - } - return v2; +function smaxabssorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js index f9a71bc2c9c7..ac6d9b262d87 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum absolute value * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ -1.0, -2.0, -3.0 ] ); -* var N = x.length; * -* var v = smaxabssorted( N, x, 1 ); +* var v = smaxabssorted( x.length, x, 1 ); * // returns 3.0 */ -function smaxabssorted( N, x, stride ) { - return addon( N, x, stride ); +function smaxabssorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json b/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json index 70db545e29cd..c5f79a39adbb 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,18 +27,80 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smaxabssorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nanf" + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/special/absf", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c new file mode 100644 index 000000000000..c0833a4989d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smaxabssorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smaxabssorted)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp deleted file mode 100644 index 247ca07d6599..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smaxabssorted.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smaxabssorted { - - /** - * Computes the maximum absolute value of a sorted single-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: sorted input array - * - `stride`: stride length - */ - napi_value node_smaxabssorted( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smaxabssorted( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smaxabssorted, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smaxabssorted diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c new file mode 100644 index 000000000000..64a899661429 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smaxabssorted.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/special/absf.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the maximum absolute value of a sorted single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smaxabssorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + float v1; + float v2; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + v1 = X[ offsetX ]; + v2 = X[ ( ( N - 1 ) * strideX ) + offsetX ]; + if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) { + return 0.0f / 0.0f; // NaN + } + v1 = stdlib_base_absf( v1 ); + v2 = stdlib_base_absf( v2 ); + if ( v1 > v2 ) { + return v1; + } + return v2; +} diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c deleted file mode 100644 index d91eccfab7f7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c +++ /dev/null @@ -1,58 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smaxabssorted.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include -#include - -/** -* Computes the maximum absolute value of a sorted single-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_smaxabssorted( const int64_t N, const float *X, const int64_t stride ) { - float v1; - float v2; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - v1 = X[ (1-N) * stride ]; - v2 = X[ 0 ]; - } else { - v1 = X[ 0 ]; - v2 = X[ (N-1) * stride ]; - } - if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) { - return 0.0f / 0.0f; // NaN - } - v1 = fabsf( v1 ); - v2 = fabsf( v2 ); - if ( v1 > v2 ) { - return v1; - } - return v2; -} diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js index 3222cdfd1981..c2f5e9a961e7 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, 2, 0 ); + v = smaxabssorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, -2, 6 ); + v = smaxabssorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, 2, 1 ); + v = smaxabssorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js index 8e0a25335ab7..c3379e3993de 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, 2, 0 ); + v = smaxabssorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, -2, 6 ); + v = smaxabssorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, 2, 1 ); + v = smaxabssorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js index f654ff6f9525..e8f32a828003 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, 2 ); + v = smaxabssorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, -2 ); + v = smaxabssorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smaxabssorted( N, x1, 2 ); + v = smaxabssorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js index a7203cfdd25e..8b3a74a94dde 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, 2 ); + v = smaxabssorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smaxabssorted( N, x, -2 ); + v = smaxabssorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smaxabssorted( N, x1, 2 ); + v = smaxabssorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md b/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md index de8c418d00a0..f20f04d3a85d 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md @@ -44,15 +44,13 @@ Computes the maximum value of a sorted single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = smaxsorted( N, x, 1 ); +var v = smaxsorted( x.length, x, 1 ); // returns 3.0 x = new Float32Array( [ 3.0, 2.0, 1.0 ] ); -N = x.length; -v = smaxsorted( N, x, 1 ); +v = smaxsorted( x.length, x, 1 ); // returns 3.0 ``` @@ -60,18 +58,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = smaxsorted( N, x, 2 ); +var v = smaxsorted( 4, x, 2 ); // returns 4.0 ``` @@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smaxsorted( N, x1, 2 ); +var v = smaxsorted( 4, x1, 2 ); // returns 4.0 ``` -#### smaxsorted.ndarray( N, x, stride, offset ) +#### smaxsorted.ndarray( N, x, strideX, offsetX ) Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -100,26 +93,23 @@ Computes the maximum value of a sorted single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = smaxsorted.ndarray( N, x, 1, 0 ); +var v = smaxsorted.ndarray( x.length, x, 1, 0 ); // returns 3.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = smaxsorted.ndarray( N, x, 2, 1 ); +var v = smaxsorted.ndarray( 4, x, 2, 1 ); // returns 4.0 ``` @@ -145,16 +135,13 @@ var v = smaxsorted.ndarray( N, x, 2, 1 ); ```javascript -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var smaxsorted = require( '@stdlib/stats/base/smaxsorted' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = smaxsorted( x.length, x, 1 ); @@ -165,6 +152,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smaxsorted.h" +``` + +#### stdlib_strided_smaxsorted( N, \*X, strideX ) + +Computes the maximum value of a sorted single-precision floating-point strided array. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smaxsorted( 3, x, 1 ); +// returns 3.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_smaxsorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_smaxsorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smaxsorted_ndarray( 3, x, 1, 0 ); +// returns 3.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_smaxsorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smaxsorted.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the maximum value: + float v = stdlib_strided_smaxsorted( N, x, strideX ); + + // Print the result: + printf( "max: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js index 3dca715f1b1d..c32e45d8a078 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smaxsorted = require( './../lib/smaxsorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var smaxsorted = require( './../lib/smaxsorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js index 0bed96875d2b..55f8e8fbab28 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var smaxsorted = tryRequire( resolve( __dirname, './../lib/smaxsorted.native.js' var opts = { 'skip': ( smaxsorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js index 29673890359b..5fc048214ead 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smaxsorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var smaxsorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js index a75a00fa15e7..6d9dd607368b 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var smaxsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( smaxsorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c index 705880dd25c5..1252ee68d5fc 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smaxsorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smaxsorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS; + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt index 26df328ced96..44fd804f1c02 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the maximum value of a sorted single-precision floating-point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,8 +22,8 @@ x: Float32Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,22 +37,19 @@ > {{alias}}( x.length, x, 1 ) 3.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) 2.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) 3.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float32Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 3.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts index 1defad939e3f..f9aef7b6f035 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns maximum value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = smaxsorted( x.length, x, 1 ); * // returns 3.0 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns maximum value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = smaxsorted.ndarray( x.length, x, 1, 0 ); * // returns 3.0 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns maximum value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c index f793a54a9fec..1874db46dd28 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/smaxsorted.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the maximum value: - float v = stdlib_strided_smaxsorted( N, x, stride ); + float v = stdlib_strided_smaxsorted( N, x, strideX ); // Print the result: printf( "max: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js index 4dc04539dfeb..7c8da27dbea5 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var smaxsorted = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = smaxsorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the maximum value of a sorted single-precision floating-point strided array. */ -float stdlib_strided_smaxsorted( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_smaxsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js index 844e74130978..3ece51392ad3 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js @@ -28,20 +28,17 @@ * var smaxsorted = require( '@stdlib/stats/base/smaxsorted' ); * * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = smaxsorted( N, x, 1 ); +* var v = smaxsorted( x.length, x, 1 ); * // returns 3.0 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smaxsorted = require( '@stdlib/stats/base/smaxsorted' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smaxsorted.ndarray( N, x, 2, 1 ); +* var v = smaxsorted.ndarray( 4, x, 2, 1 ); * // returns 4.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js index 3c97d9993abf..3e8759112cd7 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js @@ -31,32 +31,30 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smaxsorted( N, x, 2, 1 ); +* var v = smaxsorted( 4, x, 2, 1 ); * // returns 4.0 */ -function smaxsorted( N, x, stride, offset ) { +function smaxsorted( N, x, strideX, offsetX ) { var v1; var v2; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return x[ 0 ]; } - v1 = x[ offset ]; - v2 = x[ offset + ((N-1)*stride) ]; + v1 = x[ offsetX ]; + v2 = x[ offsetX + ((N-1)*strideX) ]; if ( isnanf( v1 ) || isnanf( v2 ) ) { return NaN; } diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js index e9b33c63c0e3..b332e2ba874d 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './smaxsorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './smaxsorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} maximum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smaxsorted( N, x, 2, 1 ); +* var v = smaxsorted( 4, x, 2, 1 ); * // returns 4.0 */ -function smaxsorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function smaxsorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js index 9ada465ae2d1..2f2dbcacea2d 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,48 +31,19 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = smaxsorted( N, x, 1 ); +* var v = smaxsorted( x.length, x, 1 ); * // returns 3.0 */ -function smaxsorted( N, x, stride ) { - var v1; - var v2; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - v1 = x[ (1-N) * stride ]; - v2 = x[ 0 ]; - } else { - v1 = x[ 0 ]; - v2 = x[ (N-1) * stride ]; - } - if ( isnanf( v1 ) || isnanf( v2 ) ) { - return NaN; - } - if ( v1 === v2 ) { - if ( isPositiveZerof( v1 ) || isPositiveZerof( v2 ) ) { - return 0.0; - } - return v1; - } - if ( v1 > v2 ) { - return v1; - } - return v2; +function smaxsorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js index 3d3aa222d40c..ed41c91b40f2 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} maximum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = smaxsorted( N, x, 1 ); +* var v = smaxsorted( x.length, x, 1 ); * // returns 3.0 */ -function smaxsorted( N, x, stride ) { - return addon( N, x, stride ); +function smaxsorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json index 0584a64076ec..da756d76a756 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,19 +27,80 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smaxsorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nanf", - "@stdlib/math/base/assert/is-positive-zerof" + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c new file mode 100644 index 000000000000..10d7a996faf8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smaxsorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smaxsorted)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp deleted file mode 100644 index 0fa5695cafe5..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smaxsorted.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smaxsorted { - - /** - * Computes the maximum value of a sorted single-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: sorted input array - * - `stride`: stride length - */ - napi_value node_smaxsorted( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smaxsorted( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smaxsorted, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smaxsorted diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/main.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/main.c new file mode 100644 index 000000000000..40c85be416fc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/main.c @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smaxsorted.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/assert/is_positive_zerof.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the maximum value of a sorted single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smaxsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + float v1; + float v2; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + v1 = X[ offsetX ]; + v2 = X[ ( ( N - 1 ) * strideX ) + offsetX ]; + if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) { + return 0.0f / 0.0f; // NaN + } + if ( v1 == v2 ) { + if ( stdlib_base_is_positive_zerof( v1 ) || stdlib_base_is_positive_zerof( v2 ) ) { + return 0.0f; + } + return v1; + } + if ( v1 > v2 ) { + return v1; + } + return v2; +} diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/smaxsorted.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/smaxsorted.c deleted file mode 100644 index 10fc5f943862..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/smaxsorted.c +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smaxsorted.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include "stdlib/math/base/assert/is_positive_zerof.h" -#include - -/** -* Computes the maximum value of a sorted single-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_smaxsorted( const int64_t N, const float *X, const int64_t stride ) { - float v1; - float v2; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - v1 = X[ (1-N) * stride ]; - v2 = X[ 0 ]; - } else { - v1 = X[ 0 ]; - v2 = X[ (N-1) * stride ]; - } - if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) { - return 0.0f / 0.0f; // NaN - } - if ( v1 == v2 ) { - if ( stdlib_base_is_positive_zerof( v1 ) || stdlib_base_is_positive_zerof( v2 ) ) { - return 0.0f; - } - return v1; - } - if ( v1 > v2 ) { - return v1; - } - return v2; -} diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js index 68347035884d..73712bd07b51 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, 2, 0 ); + v = smaxsorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -148,14 +144,13 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0, 2.0, // 2 -7.0, - 3.0, // 1 + 3.0, // 1 3.0, 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, -2, 6 ); + v = smaxsorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, 2, 1 ); + v = smaxsorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js index ade40cf702c1..a4cb3681fe00 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, 2, 0 ); + v = smaxsorted( 4, x, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -157,14 +153,13 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0, 2.0, // 2 -7.0, - 3.0, // 1 + 3.0, // 1 3.0, 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, -2, 6 ); + v = smaxsorted( 4, x, -2, 6 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, 2, 1 ); + v = smaxsorted( 4, x, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js index 73d5cfac8e45..646a72f5da66 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, 2 ); + v = smaxsorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, -2 ); + v = smaxsorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smaxsorted( N, x1, 2 ); + v = smaxsorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js index 0749b49ced0c..6a74d1f6f012 100644 --- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, 2 ); + v = smaxsorted( 4, x, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smaxsorted( N, x, -2 ); + v = smaxsorted( 4, x, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smaxsorted( N, x1, 2 ); + v = smaxsorted( 4, x1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smean/include.gypi b/lib/node_modules/@stdlib/stats/base/smean/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smean/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smean/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smean( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp deleted file mode 100644 index f6e2a81d05e3..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smean.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smean { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smean( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smean( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smean, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smean diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi b/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeankbn( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp deleted file mode 100644 index f81f6b55202d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeankbn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeankbn { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeankbn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeankbn( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeankbn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeankbn diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi b/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeankbn2( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp deleted file mode 100644 index b3137e597900..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeankbn2.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeankbn2 { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeankbn2( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeankbn2( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeankbn2, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeankbn2 diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/README.md b/lib/node_modules/@stdlib/stats/base/smeanli/README.md index a784871351ac..51f6a8137a95 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/README.md +++ b/lib/node_modules/@stdlib/stats/base/smeanli/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var smeanli = require( '@stdlib/stats/base/smeanli' ); ``` -#### smeanli( N, x, stride ) +#### smeanli( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = smeanli( N, x, 1 ); +var v = smeanli( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: index increment for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = smeanli( N, x, 2 ); +var v = smeanli( 4, x, 2 ); // returns 1.25 ``` @@ -90,14 +87,11 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smeanli( N, x1, 2 ); +var v = smeanli( 4, x1, 2 ); // returns 1.25 ``` @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = smeanli.ndarray( N, x, 1, 0 ); +var v = smeanli.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = smeanli.ndarray( N, x, 2, 1 ); +var v = smeanli.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -154,18 +145,12 @@ var v = smeanli.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var smeanli = require( '@stdlib/stats/base/smeanli' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = smeanli( x.length, x, 1 ); @@ -176,6 +161,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smeanli.h" +``` + +#### stdlib_strided_smeanli( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smeanli( 3, x, 1 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +float stdlib_strided_smeanli( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_smeanli_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smeanli_ndarray( 3, x, 1, 0 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +float stdlib_strided_smeanli_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smeanli.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + float v = stdlib_strided_smeanli( N, x, strideX ); + + // Print the result: + printf( "mean: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.js index 82ea402f0fe1..f9d6b3963df3 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smeanli = require( './../lib/smeanli.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var smeanli = require( './../lib/smeanli.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.native.js index f31daf51b5d9..f3f435366a91 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var smeanli = tryRequire( resolve( __dirname, './../lib/smeanli.native.js' ) ); var opts = { 'skip': ( smeanli instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.js index 8e7ce1e955a1..bdaede6170e6 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smeanli = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var smeanli = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.native.js index 794f5df24271..b3f16bb4a33a 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var smeanli = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( smeanli instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/c/benchmark.length.c index 95a0dc98d7ba..c00ab4a64401 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smeanli/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smeanli( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smeanli_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smeanli/docs/repl.txt index c20cf76b699c..6b57b3d7beab 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smeanli/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -66,10 +63,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +83,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smeanli/docs/types/index.d.ts index 399f993a564e..008043d91af7 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/smeanli/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = smeanli( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = smeanli.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smeanli/examples/c/example.c index d7f78d9ca8e4..45acd36d4c4d 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smeanli/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/smeanli.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - float v = stdlib_strided_smeanli( N, x, stride ); + float v = stdlib_strided_smeanli( N, x, strideX ); // Print the result: printf( "mean: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/examples/index.js b/lib/node_modules/@stdlib/stats/base/smeanli/examples/index.js index 667b5463db50..4b9b34faafaf 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var smeanli = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = smeanli( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. */ -float stdlib_strided_smeanli( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_smeanli)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smeanli_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/lib/index.js b/lib/node_modules/@stdlib/stats/base/smeanli/lib/index.js index 83366624a2e2..bdb7c2c15fca 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/lib/index.js @@ -28,20 +28,17 @@ * var smeanli = require( '@stdlib/stats/base/smeanli' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = smeanli( N, x, 1 ); +* var v = smeanli( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smeanli = require( '@stdlib/stats/base/smeanli' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smeanli.ndarray( N, x, 2, 1 ); +* var v = smeanli.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.js index 72c18def5624..fa97bcfdb1aa 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.js @@ -35,28 +35,26 @@ var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smeanli( N, x, 2, 1 ); +* var v = smeanli( 4, x, 2, 1 ); * // returns 1.25 */ -function smeanli( N, x, stride, offset ) { +function smeanli( N, x, strideX, offsetX ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - return float64ToFloat32( x[ offset ] + float64ToFloat32( sapxsum( N-1, -x[ offset ], x, stride, offset+stride ) / N ) ); // eslint-disable-line max-len + return float64ToFloat32( x[ offsetX ] + float64ToFloat32( sapxsum( N-1, -x[ offsetX ], x, strideX, offsetX+strideX ) / N ) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.native.js index 5692fbffa955..18753f91a41a 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './smeanli.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './smeanli.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smeanli( N, x, 2, 1 ); +* var v = smeanli( 4, x, 2, 1 ); * // returns 1.25 */ -function smeanli( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function smeanli( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.js b/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.js index 0a1bd0083b61..4b028379f227 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.js @@ -20,8 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ).ndarray; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -35,33 +35,19 @@ var sapxsum = require( '@stdlib/blas/ext/base/sapxsum' ).ndarray; * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = smeanli( N, x, 1 ); +* var v = smeanli( x.length, x, 1 ); * // returns ~0.3333 */ -function smeanli( N, x, stride ) { - var ix; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - return float64ToFloat32( x[ ix ] + float64ToFloat32( sapxsum( N-1, -x[ ix ], x, stride, ix+stride ) / N ) ); // eslint-disable-line max-len +function smeanli( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.native.js b/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.native.js index 265a4ffdd74a..4bca6d9d9e49 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/lib/smeanli.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = smeanli( N, x, 1 ); +* var v = smeanli( x.length, x, 1 ); * // returns ~0.3333 */ -function smeanli( N, x, stride ) { - return addon( N, x, stride ); +function smeanli( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json b/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json index 30f69fc760e7..a9644a577d38 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,75 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smeanli.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/sapxsum", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/sapxsum" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/ext/base/sapxsum" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/blas/ext/base/sapxsum" ] } diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c b/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c new file mode 100644 index 000000000000..7b5aa205204d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smeanli.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smeanli)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smeanli_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp deleted file mode 100644 index f7869e9451aa..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanli.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeanli { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeanli( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeanli( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanli, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeanli diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/src/main.c b/lib/node_modules/@stdlib/stats/base/smeanli/src/main.c new file mode 100644 index 000000000000..b9baf6f0afbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smeanli/src/main.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smeanli.h" +#include "stdlib/blas/ext/base/sapxsum.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. +* +* ## References +* +* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smeanli)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_smeanli_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smeanli_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + return X[ offsetX ] + (float)( (double)API_SUFFIX(stdlib_strided_sapxsum_ndarray)( N-1, -X[ offsetX ], X, strideX, offsetX + strideX ) / (double)N ); +} diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/src/smeanli.c b/lib/node_modules/@stdlib/stats/base/smeanli/src/smeanli.c deleted file mode 100644 index d7b5a46c90d6..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanli/src/smeanli.c +++ /dev/null @@ -1,50 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanli.h" -#include "stdlib/blas/ext/base/sapxsum.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm. -* -* ## References -* -* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_smeanli( const int64_t N, const float *X, const int64_t stride ) { - int64_t ix; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - return X[ ix ] + (float)( (double)stdlib_strided_sapxsum( N-1, -X[ ix ], X+( (stride > 0) ? stride : 0 ), stride ) / (double)N ); -} diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.js index 21268132720d..0edc8cd82a20 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var smeanli = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, 2, 0 ); + v = smeanli( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, -2, 6 ); + v = smeanli( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, 2, 1 ); + v = smeanli( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.native.js index 777a11887889..5f8317f4fce7 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, 2, 0 ); + v = smeanli( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, -2, 6 ); + v = smeanli( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, 2, 1 ); + v = smeanli( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.js b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.js index 024f09cbcbf8..8b1541b30126 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var smeanli = require( './../lib/smeanli.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, 2 ); + v = smeanli( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, -2 ); + v = smeanli( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smeanli( N, x1, 2 ); + v = smeanli( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.native.js b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.native.js index 3b50586d1f83..65f2d5d0fa90 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanli/test/test.smeanli.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, 2 ); + v = smeanli( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smeanli( N, x, -2 ); + v = smeanli( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smeanli( N, x1, 2 ); + v = smeanli( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanlipw/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanlipw/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanlipw/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeanlipw/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeanlipw( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smeanlipw/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanlipw/src/addon.cpp deleted file mode 100644 index 9b7ea8c7e7d0..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanlipw/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanlipw.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeanlipw { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeanlipw( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeanlipw( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanlipw, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeanlipw diff --git a/lib/node_modules/@stdlib/stats/base/smeanors/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanors/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanors/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeanors/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeanors( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smeanors/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanors/src/addon.cpp deleted file mode 100644 index c221f7917990..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanors/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanors.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeanors { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeanors( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeanors( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanors, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeanors diff --git a/lib/node_modules/@stdlib/stats/base/smeanpn/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeanpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeanpn( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smeanpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanpn/src/addon.cpp deleted file mode 100644 index 440d93ce763a..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanpn/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeanpn { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeanpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeanpn( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeanpn diff --git a/lib/node_modules/@stdlib/stats/base/smeanpw/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanpw/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanpw/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeanpw/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeanpw( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/smeanpw/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanpw/src/addon.cpp deleted file mode 100644 index 9d09f2c22d44..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanpw/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanpw.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeanpw { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using pairwise summation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeanpw( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeanpw( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanpw, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeanpw diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/README.md b/lib/node_modules/@stdlib/stats/base/smeanwd/README.md index a66534f117e4..696d84967439 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var smeanwd = require( '@stdlib/stats/base/smeanwd' ); ``` -#### smeanwd( N, x, stride ) +#### smeanwd( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x` using Welford's algorithm. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = smeanwd( N, x, 1 ); +var v = smeanwd( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,18 +68,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = smeanwd( N, x, 2 ); +var v = smeanwd( 4, x, 2 ); // returns 1.25 ``` @@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smeanwd( N, x1, 2 ); +var v = smeanwd( 4, x1, 2 ); // returns 1.25 ``` -#### smeanwd.ndarray( N, x, stride, offset ) +#### smeanwd.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = smeanwd.ndarray( N, x, 1, 0 ); +var v = smeanwd.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = smeanwd.ndarray( N, x, 2, 1 ); +var v = smeanwd.ndarray( 4, x, 2, 1 ); // returns 1.25 ``` @@ -153,18 +144,12 @@ var v = smeanwd.ndarray( N, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var smeanwd = require( '@stdlib/stats/base/smeanwd' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = smeanwd( x.length, x, 1 ); @@ -175,6 +160,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smeanwd.h" +``` + +#### stdlib_strided_smeanwd( N, \*X, strideX ) + +Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using Welford's algorithm. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smeanwd( 3, x, 1 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_smeanwd( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_smeanwd_ndarray( N, \*X, strideX, offsetX ) + +Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smeanwd_ndarray( 3, x, 1, 0 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_smeanwd_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smeanwd.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + float v = stdlib_strided_smeanwd( N, x, strideX ); + + // Print the result: + printf( "mean: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.js index d9206df197f9..bb9d2d77d680 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smeanwd = require( './../lib/smeanwd.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var smeanwd = require( './../lib/smeanwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.native.js index 881334062237..09ef58c28643 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var smeanwd = tryRequire( resolve( __dirname, './../lib/smeanwd.native.js' ) ); var opts = { 'skip': ( smeanwd instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.js index c53ea0098868..b8bd01f99da1 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smeanwd = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var smeanwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.native.js index 49dcf3766579..a0b464371587 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var smeanwd = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( smeanwd instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/c/benchmark.length.c index 607fc32c5f45..7f072692ed11 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smeanwd( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smeanwd_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smeanwd/docs/repl.txt index 037c827c324d..2f3bc8242a48 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -19,8 +19,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -34,22 +34,19 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) ~0.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -65,10 +62,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -85,8 +82,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smeanwd/docs/types/index.d.ts index 26517e524e91..1cf73d256828 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns arithmetic mean * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = smeanwd( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = smeanwd.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smeanwd/examples/c/example.c index 61cb5d5a5bc1..af14356b3334 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/smeanwd.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - float v = stdlib_strided_smeanwd( N, x, stride ); + float v = stdlib_strided_smeanwd( N, x, strideX ); // Print the result: printf( "mean: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/examples/index.js b/lib/node_modules/@stdlib/stats/base/smeanwd/examples/index.js index a360973b5b59..633d80da5f2a 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var smeanwd = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = smeanwd( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanwd/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. */ -float stdlib_strided_smeanwd( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_smeanwd)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smeanwd_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/index.js index b4a25b0ff2cd..26ec8852ee6a 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/index.js @@ -28,20 +28,17 @@ * var smeanwd = require( '@stdlib/stats/base/smeanwd' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = smeanwd( N, x, 1 ); +* var v = smeanwd( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smeanwd = require( '@stdlib/stats/base/smeanwd' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smeanwd.ndarray( N, x, 2, 1 ); +* var v = smeanwd.ndarray( 4, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.js index 945f1ede1e9e..c56c11b16db0 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.js @@ -48,21 +48,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smeanwd( N, x, 2, 1 ); +* var v = smeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function smeanwd( N, x, stride, offset ) { +function smeanwd( N, x, strideX, offsetX ) { var mu; var ix; var n; @@ -71,16 +69,16 @@ function smeanwd( N, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; mu = 0.0; n = 0; for ( i = 0; i < N; i++ ) { n += 1; mu = float64ToFloat32( mu + float64ToFloat32( float64ToFloat32( x[ix]-mu ) / n ) ); // eslint-disable-line max-len - ix += stride; + ix += strideX; } return mu; } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.native.js index 2c7379c4b846..e99079f5cd46 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './smeanwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './smeanwd.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smeanwd( N, x, 2, 1 ); +* var v = smeanwd( 4, x, 2, 1 ); * // returns 1.25 */ -function smeanwd( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function smeanwd( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.js b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.js index 64f30aa3c6e5..2300d2c16c15 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.js @@ -20,7 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -48,43 +49,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = smeanwd( N, x, 1 ); +* var v = smeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function smeanwd( N, x, stride ) { - var mu; - var ix; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - n += 1; - mu = float64ToFloat32( mu + float64ToFloat32( float64ToFloat32( x[ix]-mu ) / n ) ); // eslint-disable-line max-len - ix += stride; - } - return mu; +function smeanwd( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.native.js b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.native.js index 981c5c70ce17..845ee7ab4c24 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/lib/smeanwd.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = smeanwd( N, x, 1 ); +* var v = smeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function smeanwd( N, x, stride ) { - return addon( N, x, stride ); +function smeanwd( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/manifest.json b/lib/node_modules/@stdlib/stats/base/smeanwd/manifest.json index aff3a2ae9465..7a0fdb1d890b 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,73 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/smeanwd/src/addon.c new file mode 100644 index 000000000000..877a7d47c989 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smeanwd)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smeanwd_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanwd/src/addon.cpp deleted file mode 100644 index 792407bbfdfe..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanwd.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smeanwd { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_smeanwd( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smeanwd( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanwd, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smeanwd diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/src/main.c b/lib/node_modules/@stdlib/stats/base/smeanwd/src/main.c new file mode 100644 index 000000000000..7e5b149c51b2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/src/main.c @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smeanwd.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. +* +* ## Method +* +* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows +* +* ```tex +* \begin{align*} +* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ +* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ +* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ +* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) +* \end{align*} +* ``` +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smeanwd)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_smeanwd_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smeanwd_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double n; + float mu; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; + } + ix = offsetX; + mu = 0.0f; + n = 0.0; + for ( i = 0; i < N; i++ ) { + n += 1.0; + mu += (float)((double)( X[ix]-mu ) / n); + ix += strideX; + } + return mu; +} diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/src/smeanwd.c b/lib/node_modules/@stdlib/stats/base/smeanwd/src/smeanwd.c deleted file mode 100644 index 167054958246..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/src/smeanwd.c +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smeanwd.h" -#include - -/** -* Computes the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm. -* -* ## Method -* -* - This implementation uses Welford's algorithm for efficient computation, which can be derived as follows -* -* ```tex -* \begin{align*} -* \mu_n &= \frac{1}{n} \sum_{i=0}^{n-1} x_i \\ -* &= \frac{1}{n} \biggl(x_{n-1} + \sum_{i=0}^{n-2} x_i \biggr) \\ -* &= \frac{1}{n} (x_{n-1} + (n-1)\mu_{n-1}) \\ -* &= \mu_{n-1} + \frac{1}{n} (x_{n-1} - \mu_{n-1}) -* \end{align*} -* ``` -* -* ## References -* -* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). -* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). -* -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_smeanwd( const int64_t N, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double n; - float mu; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0f; - n = 0.0; - for ( i = 0; i < N; i++ ) { - n += 1.0; - mu += (float)((double)( X[ix]-mu ) / n); - ix += stride; - } - return mu; -} diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.js index a0695a52435a..02f254fa5de6 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var smeanwd = require( './../lib/ndarray.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, 2, 0 ); + v = smeanwd( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, -2, 6 ); + v = smeanwd( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -145,7 +140,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -159,9 +153,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, 2, 1 ); + v = smeanwd( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.native.js index ed44da26cea1..a69734233ae1 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -96,7 +95,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -111,15 +109,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, 2, 0 ); + v = smeanwd( 4, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,8 +130,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, -2, 6 ); + v = smeanwd( 4, x, -2, 6 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -154,7 +149,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -168,9 +162,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, 2, 1 ); + v = smeanwd( 4, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.js b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.js index 61efea27aa1c..e4dedcdd4dc5 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var smeanwd = require( './../lib/smeanwd.js' ); @@ -87,7 +86,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -102,15 +100,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, 2 ); + v = smeanwd( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,8 +121,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, -2 ); + v = smeanwd( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -147,7 +142,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -163,9 +157,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smeanwd( N, x1, 2 ); + v = smeanwd( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.native.js b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.native.js index 8834a26f3a24..1bbf9c6ce113 100644 --- a/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/smeanwd/test/test.smeanwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -178,7 +177,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -193,15 +191,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, 2 ); + v = smeanwd( 4, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -216,8 +212,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smeanwd( N, x, -2 ); + v = smeanwd( 4, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -238,7 +233,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -254,9 +248,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smeanwd( N, x1, 2 ); + v = smeanwd( 4, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/README.md b/lib/node_modules/@stdlib/stats/base/smediansorted/README.md index a1445f4a465a..dcae19495563 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var smediansorted = require( '@stdlib/stats/base/smediansorted' ); ``` -#### smediansorted( N, x, stride ) +#### smediansorted( N, x, strideX ) Computes the median value of a sorted single-precision floating-point strided array `x`. @@ -56,18 +56,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the median value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the median value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = smediansorted( N, x, 2 ); +var v = smediansorted( 4, x, 2 ); // returns 2.5 ``` @@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smediansorted( N, x1, 2 ); +var v = smediansorted( 4, x1, 2 ); // returns 2.0 ``` -#### smediansorted.ndarray( N, x, stride, offset ) +#### smediansorted.ndarray( N, x, strideX, offsetX ) Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -96,9 +91,8 @@ Computes the median value of a sorted single-precision floating-point strided ar var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = smediansorted.ndarray( N, x, 1, 0 ); +var v = smediansorted.ndarray( x.length, x, 1, 0 ); // returns 2.0 ``` @@ -106,16 +100,14 @@ The function has the following additional parameters: - **offset**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the median value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the median value for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = smediansorted.ndarray( N, x, 2, 1 ); +var v = smediansorted.ndarray( 4, x, 2, 1 ); // returns 2.0 ``` @@ -141,16 +133,13 @@ var v = smediansorted.ndarray( N, x, 2, 1 ); ```javascript -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var smediansorted = require( '@stdlib/stats/base/smediansorted' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = smediansorted( x.length, x, 1 ); @@ -161,6 +150,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smediansorted.h" +``` + +#### stdlib_strided_smediansorted( N, \*X, strideX ) + +Computes the median value of a sorted single-precision floating-point strided array. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smediansorted( 3, x, 1 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_smediansorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_smediansorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_smediansorted_ndarray( 3, x, 1, 0 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_smediansorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smediansorted.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the median value: + float v = stdlib_strided_smediansorted( N, x, strideX ); + + // Print the result: + printf( "median: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js index aa0d2b00e3dc..49eb9f882fe4 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smediansorted = require( './../lib/smediansorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var smediansorted = require( './../lib/smediansorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js index 44e26264be5b..44f95e1af499 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var smediansorted = tryRequire( resolve( __dirname, './../lib/smediansorted.nati var opts = { 'skip': ( smediansorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js index d0dec1cbc22e..12620874edb7 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var smediansorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var smediansorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js index 9e992b40939f..1c75037ae063 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var smediansorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' var opts = { 'skip': ( smediansorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c index e0b375995782..c7c02d5582b7 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c @@ -82,9 +82,9 @@ static double tic( void ) { * * @return random number */ -static double rand_double( void ) { +static float rand_float( void ) { int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); + return (float)r / ( (float)RAND_MAX + 1.0f ); } /** @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smediansorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smediansorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS; + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt index 3f60345acbca..2ac1f6be73a4 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the median value of a sorted single-precision floating-point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,7 +22,7 @@ x: Float32Array Sorted input array. - stride: integer + strideX: integer Index increment. Returns @@ -37,20 +37,19 @@ > {{alias}}( x.length, x, 1 ) 2.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2 ) + > {{alias}}( 3, x, 2 ) 1.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2 ) + > {{alias}}( 3, x1, 2 ) 2.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -66,10 +65,10 @@ x: Float32Array Sorted input array. - stride: integer + strideX: integer Index increment. - offset: integer + offsetX: integer Starting index. Returns @@ -86,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) 2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts index 948b796c94c9..e1ec1dd684eb 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns median value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = smediansorted( x.length, x, 1 ); * // returns 2.0 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns median value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = smediansorted.ndarray( x.length, x, 1, 0 ); * // returns 2.0 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns median value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c index 727a623326a9..52975dfde647 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/smediansorted.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the median value: - float v = stdlib_strided_smediansorted( N, x, stride ); + float v = stdlib_strided_smediansorted( N, x, strideX ); // Print the result: printf( "median: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js index f2e77652484e..c463db67f1c7 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var smediansorted = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = smediansorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi b/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the median value of a sorted single-precision floating-point strided array. */ -float stdlib_strided_smediansorted( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_smediansorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smediansorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js index c3c940d36aec..b72bc656d954 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js @@ -34,13 +34,11 @@ * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smediansorted = require( '@stdlib/stats/base/smediansorted' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smediansorted.ndarray( N, x, 2, 1 ); +* var v = smediansorted.ndarray( 4, x, 2, 1 ); * // returns 0.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js index 6afedb060092..ea4df53a4263 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js @@ -31,21 +31,19 @@ var floor = require( '@stdlib/math/base/special/floor' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} median value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smediansorted( N, x, 2, 1 ); +* var v = smediansorted( 4, x, 2, 1 ); * // returns 0.0 */ -function smediansorted( N, x, stride, offset ) { +function smediansorted( N, x, strideX, offsetX ) { var n; var m; @@ -56,10 +54,10 @@ function smediansorted( N, x, stride, offset ) { m = floor( n ); if ( n === m ) { // Even number of elements... - return float64ToFloat32( float64ToFloat32( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0 ); // eslint-disable-line max-len + return float64ToFloat32( float64ToFloat32( x[ offsetX+(m*strideX) ] + x[ offsetX+((m-1)*strideX) ] ) / 2.0 ); // eslint-disable-line max-len } // Odd number of elements... - return x[ offset+(m*stride) ]; + return x[ offsetX+(m*strideX) ]; } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js index da59286ed6e6..1e1454676234 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './smediansorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './smediansorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} median value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = smediansorted( N, x, 2, 1 ); +* var v = smediansorted( 4, x, 2, 1 ); * // returns 0.0 */ -function smediansorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function smediansorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js index c484afcbf35d..ae926ae41a23 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js @@ -20,8 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,7 +31,7 @@ var floor = require( '@stdlib/math/base/special/floor' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} median value * * @example @@ -42,27 +42,8 @@ var floor = require( '@stdlib/math/base/special/floor' ); * var v = smediansorted( x.length, x, 1 ); * // returns 2.0 */ -function smediansorted( N, x, stride ) { - var offset; - var n; - var m; - - if ( N <= 0 ) { - return NaN; - } - if ( stride < 0 ) { - offset = (1-N) * stride; - } else { - offset = 0; - } - n = N / 2; - m = floor( n ); - if ( n === m ) { - // Even number of elements... - return float64ToFloat32( float64ToFloat32( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0 ); // eslint-disable-line max-len - } - // Odd number of elements... - return x[ offset+(m*stride) ]; +function smediansorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js index b378fc6d03d3..de6698ed0efe 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js @@ -30,7 +30,7 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} median value * * @example @@ -41,8 +41,8 @@ var addon = require( './../src/addon.node' ); * var v = smediansorted( x.length, x, 1 ); * // returns 2.0 */ -function smediansorted( N, x, stride ) { - return addon( N, x, stride ); +function smediansorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json b/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json index d8255d672b93..7a0fdb1d890b 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,73 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smediansorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c new file mode 100644 index 000000000000..8a1db3fb4fbb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smediansorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smediansorted)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smediansorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp deleted file mode 100644 index 47845c16d2b2..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smediansorted.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smediansorted { - - /** - * Computes the median value of a sorted single-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: sorted input array - * - `stride`: stride length - */ - napi_value node_smediansorted( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smediansorted( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smediansorted, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smediansorted diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c b/lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c new file mode 100644 index 000000000000..300fd23956ce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smediansorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the median value of a sorted single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smediansorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_smediansorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smediansorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT n; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + n = N >> 1; + if ( N & 1 ) { + // Odd number of elements... + return X[ offsetX + ( n * strideX ) ]; + } + // Even number of elements... + return ( X[ offsetX + ( n * strideX ) ] + X[ offsetX+( ( n - 1 ) * strideX ) ] ) / 2.0f; +} diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c b/lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c deleted file mode 100644 index aba34b158855..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c +++ /dev/null @@ -1,49 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smediansorted.h" -#include - -/** -* Computes the median value of a sorted single-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_smediansorted( const int64_t N, const float *X, const int64_t stride ) { - int64_t offset; - int64_t n; - - if ( N <= 0 ) { - return 0.0f/0.0f; // NaN - } - if ( stride < 0 ) { - offset = (1-N) * stride; - } else { - offset = 0; - } - n = N >> 1; - if ( N & 1 ) { - // Odd number of elements... - return X[ offset+(n*stride) ]; - } - // Even number of elements... - return ( X[ offset+(n*stride) ] + X[ offset+((n-1)*stride) ] ) / 2.0f; -} diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js index 13c6c2f675f5..23f6d6cf609d 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, 2, 0 ); + v = smediansorted( 4, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, -2, 6 ); + v = smediansorted( 4, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -178,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -192,9 +186,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, 2, 1 ); + v = smediansorted( 4, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js index 23124fe66745..090c33c8fd3b 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, 2, 0 ); + v = smediansorted( 4, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, -2, 6 ); + v = smediansorted( 4, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -187,7 +182,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -201,9 +195,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, 2, 1 ); + v = smediansorted( 4, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js index 36f903a3dee2..6c564c924f00 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, 2 ); + v = smediansorted( 4, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, -2 ); + v = smediansorted( 4, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -196,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smediansorted( N, x1, 2 ); + v = smediansorted( 4, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js index 66d42f1c0fb6..0f2b394a2422 100644 --- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, 2 ); + v = smediansorted( 4, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = smediansorted( N, x, -2 ); + v = smediansorted( 4, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -205,9 +199,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = smediansorted( N, x1, 2 ); + v = smediansorted( 4, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.js index 2df45e43d8cc..b639e404def1 100644 --- a/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.js @@ -31,7 +31,7 @@ var smidrange = require( './../lib/smidrange.js' ); // VARIABLES // var options = { - 'dtype': 'float64' + 'dtype': 'float32' }; diff --git a/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.ndarray.native.js index 5164fb819b8c..47a10e10a637 100644 --- a/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smidrange/benchmark/benchmark.ndarray.native.js @@ -36,7 +36,7 @@ var opts = { 'skip': ( smidrange instanceof Error ) }; var options = { - 'dtype': 'float64' + 'dtype': 'float32' }; diff --git a/lib/node_modules/@stdlib/stats/base/smidrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smidrange/docs/repl.txt index 2c911ea03b31..cdb3e4d5ad77 100644 --- a/lib/node_modules/@stdlib/stats/base/smidrange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smidrange/docs/repl.txt @@ -19,7 +19,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -62,7 +62,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/smidrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/smidrange/src/addon.c index ca29937de569..5796a9ed44bd 100644 --- a/lib/node_modules/@stdlib/stats/base/smidrange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/smidrange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/smidrange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smidrange( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smidrange)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smidrange_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smidrange_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/smidrange/src/main.c b/lib/node_modules/@stdlib/stats/base/smidrange/src/main.c index d56b942112d5..6283987bec0b 100644 --- a/lib/node_modules/@stdlib/stats/base/smidrange/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/smidrange/src/main.c @@ -37,7 +37,7 @@ float API_SUFFIX(stdlib_strided_smidrange)( const CBLAS_INT N, const float *X, c } /** -* Computes the mid-range of a single-precision floating-point strided array and using alternative indexing semantics. +* Computes the mid-range of a single-precision floating-point strided array using alternative indexing semantics. * * @param N number of indexed elements * @param X input array @@ -53,7 +53,7 @@ float API_SUFFIX(stdlib_strided_smidrange_ndarray)( const CBLAS_INT N, const flo float v; if ( N <= 0 ) { - return 0.0 / 0.0; // NaN + return 0.0f / 0.0f; // NaN } if ( N == 1 || strideX == 0 ) { return X[ offsetX ]; @@ -73,5 +73,5 @@ float API_SUFFIX(stdlib_strided_smidrange_ndarray)( const CBLAS_INT N, const flo max = v; } } - return ( max+min ) / 2.0; + return ( max+min ) / 2.0f; } diff --git a/lib/node_modules/@stdlib/stats/base/smin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smin/docs/repl.txt index 404cab17a4cb..d72e478b5e36 100644 --- a/lib/node_modules/@stdlib/stats/base/smin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smin/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/smin/src/addon.c b/lib/node_modules/@stdlib/stats/base/smin/src/addon.c index a391736a6f29..18be1896e816 100644 --- a/lib/node_modules/@stdlib/stats/base/smin/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/smin/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/smin.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smin( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smin)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smin_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smin_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/sminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sminabs/docs/repl.txt index 589a58aaa4ed..ff26c1f9fbd9 100644 --- a/lib/node_modules/@stdlib/stats/base/sminabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/sminabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/sminabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/sminabs/src/addon.c index 174671b61acd..bcadad62db92 100644 --- a/lib/node_modules/@stdlib/stats/base/sminabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/sminabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/sminabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sminabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sminabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sminabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sminabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/README.md b/lib/node_modules/@stdlib/stats/base/sminsorted/README.md index 2d988bb3a57e..0b8552e30be4 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/README.md +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/README.md @@ -36,7 +36,7 @@ limitations under the License. var sminsorted = require( '@stdlib/stats/base/sminsorted' ); ``` -#### sminsorted( N, x, stride ) +#### sminsorted( N, x, strideX ) Computes the minimum value of a sorted single-precision floating-point strided array `x`. @@ -44,15 +44,13 @@ Computes the minimum value of a sorted single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = sminsorted( N, x, 1 ); +var v = sminsorted( x.length, x, 1 ); // returns 1.0 x = new Float32Array( [ 3.0, 2.0, 1.0 ] ); -N = x.length; -v = sminsorted( N, x, 1 ); +v = sminsorted( x.length, x, 1 ); // returns 1.0 ``` @@ -60,18 +58,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: sorted input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: index increment for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the minimum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = sminsorted( N, x, 2 ); +var v = sminsorted( 4, x, 2 ); // returns 1.0 ``` @@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = sminsorted( N, x1, 2 ); +var v = sminsorted( 4, x1, 2 ); // returns 1.0 ``` -#### sminsorted.ndarray( N, x, stride, offset ) +#### sminsorted.ndarray( N, x, strideX, offsetX ) Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -100,26 +93,23 @@ Computes the minimum value of a sorted single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -var N = x.length; -var v = sminsorted.ndarray( N, x, 1, 0 ); +var v = sminsorted.ndarray( x.length, x, 1, 0 ); // returns 1.0 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = sminsorted.ndarray( N, x, 2, 1 ); +var v = sminsorted.ndarray( 4, x, 2, 1 ); // returns 1.0 ``` @@ -145,16 +135,13 @@ var v = sminsorted.ndarray( N, x, 2, 1 ); ```javascript -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var sminsorted = require( '@stdlib/stats/base/sminsorted' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = sminsorted( x.length, x, 1 ); @@ -165,6 +152,123 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/sminsorted.h" +``` + +#### stdlib_strided_sminsorted( N, \*X, strideX ) + +Computes the minimum value of a sorted single-precision floating-point strided array. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_sminsorted( 3, x, 1 ); +// returns 1.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_sminsorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sminsorted_ndarray( N, \*X, strideX, offsetX ) + +Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f }; + +float v = stdlib_strided_sminsorted_ndarray( 3, x, 1, 0 ); +// returns 1.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_sminsorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/sminsorted.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the minimum value: + float v = stdlib_strided_sminsorted( N, x, strideX ); + + // Print the result: + printf( "min: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js index 89ed34128746..dbe64cce9803 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sminsorted = require( './../lib/sminsorted.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var sminsorted = require( './../lib/sminsorted.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js index 46d041cfe1e6..2ae34f28c2cf 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var sminsorted = tryRequire( resolve( __dirname, './../lib/sminsorted.native.js' var opts = { 'skip': ( sminsorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js index 47374c1da0f8..48c1e0a7bcde 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js @@ -22,12 +22,19 @@ var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sminsorted = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -38,13 +45,7 @@ var sminsorted = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js index c26c3b438aa8..433e57b181b9 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js @@ -23,8 +23,8 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -35,6 +35,9 @@ var sminsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( sminsorted instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -47,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = i; - } + var x = linspace( -len/2, len/2, len, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c index 871fc4baf5d5..a78f92e4d87d 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c @@ -82,9 +82,9 @@ static double tic( void ) { * * @return random number */ -static double rand_double( void ) { +static float rand_float( void ) { int r = rand(); - return (double)r / ( (double)RAND_MAX + 1.0 ); + return (float)r / ( (float)RAND_MAX + 1.0f ); } /** @@ -94,7 +94,7 @@ static double rand_double( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sminsorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = i; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sminsorted_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS; + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt index 24308e8dbbc9..a3ceec7bc64c 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt @@ -1,13 +1,13 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the minimum value of a sorted single-precision floating-point strided array. The input strided array must be sorted in either strictly ascending or descending order. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -22,8 +22,8 @@ x: Float32Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,22 +37,19 @@ > {{alias}}( x.length, x, 1 ) 1.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + > {{alias}}( 3, x, 2 ) -2.0 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 3, x1, 2 ) -2.0 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics. @@ -68,10 +65,10 @@ x: Float32Array Sorted input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,8 +85,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1 ) -2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts index b31aac869805..8309813835b3 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts @@ -27,7 +27,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length + * @param strideX - stride length * @returns minimum value * * @example @@ -38,15 +38,15 @@ interface Routine { * var v = sminsorted( x.length, x, 1 ); * // returns 1.0 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics. * * @param N - number of indexed elements * @param x - sorted input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns minimum value * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = sminsorted.ndarray( x.length, x, 1, 0 ); * // returns 1.0 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - sorted input array -* @param stride - stride length +* @param strideX - stride length * @returns minimum value * * @example diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c index 960eadf4538b..7ba730cd529f 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/sminsorted.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the minimum value: - float v = stdlib_strided_sminsorted( N, x, stride ); + float v = stdlib_strided_sminsorted( N, x, strideX ); // Print the result: printf( "min: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js index 3365c9442ffd..6ff2f407fbf1 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js @@ -18,16 +18,13 @@ 'use strict'; -var Float32Array = require( '@stdlib/array/float32' ); +var linspace = require( '@stdlib/array/linspace' ); var sminsorted = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = i - 5.0; -} +var options = { + 'dtype': 'float32' +}; +var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); var v = sminsorted( x.length, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the minimum value of a sorted single-precision floating-point strided array. */ -float stdlib_strided_sminsorted( const int64_t N, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sminsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sminsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js index 30ca8ac6db06..4f073370b4b0 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js @@ -28,20 +28,17 @@ * var sminsorted = require( '@stdlib/stats/base/sminsorted' ); * * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = sminsorted( N, x, 1 ); +* var v = sminsorted( x.length, x, 1 ); * // returns 1.0 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var sminsorted = require( '@stdlib/stats/base/sminsorted' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sminsorted.ndarray( N, x, 2, 1 ); +* var v = sminsorted.ndarray( 4, x, 2, 1 ); * // returns -3.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js index da4cf5058734..157f1015f56b 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js @@ -31,32 +31,30 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} minimum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sminsorted( N, x, 2, 1 ); +* var v = sminsorted( 4, x, 2, 1 ); * // returns -3.0 */ -function sminsorted( N, x, stride, offset ) { +function sminsorted( N, x, strideX, offsetX ) { var v1; var v2; if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return x[ 0 ]; } - v1 = x[ offset ]; - v2 = x[ offset + ((N-1)*stride) ]; + v1 = x[ offsetX ]; + v2 = x[ offsetX + ((N-1)*strideX) ]; if ( isnanf( v1 ) || isnanf( v2 ) ) { return NaN; } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js index 7c64eb780966..a592bf398e2c 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './sminsorted.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './sminsorted.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} minimum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sminsorted( N, x, 2, 1 ); +* var v = sminsorted( 4, x, 2, 1 ); * // returns -3.0 */ -function sminsorted( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function sminsorted( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js index 787df41ce295..38047d3b7932 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,48 +31,19 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} minimum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = sminsorted( N, x, 1 ); +* var v = sminsorted( x.length, x, 1 ); * // returns 1.0 */ -function sminsorted( N, x, stride ) { - var v1; - var v2; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - v1 = x[ (1-N) * stride ]; - v2 = x[ 0 ]; - } else { - v1 = x[ 0 ]; - v2 = x[ (N-1) * stride ]; - } - if ( isnanf( v1 ) || isnanf( v2 ) ) { - return NaN; - } - if ( v1 === v2 ) { - if ( isNegativeZerof( v1 ) || isNegativeZerof( v2 ) ) { - return -0.0; - } - return v1; - } - if ( v1 < v2 ) { - return v1; - } - return v2; +function sminsorted( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js index 21c3a7138274..203035ca0b28 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - sorted input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} minimum value * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); -* var N = x.length; * -* var v = sminsorted( N, x, 1 ); +* var v = sminsorted( x.length, x, 1 ); * // returns 1.0 */ -function sminsorted( N, x, stride ) { - return addon( N, x, stride ); +function sminsorted( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json index dd2eadc21a8c..5cd4cc1df6c7 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,19 +27,80 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/sminsorted.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nanf", - "@stdlib/math/base/assert/is-negative-zerof" + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" ] } ] diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c new file mode 100644 index 000000000000..76b55f6a96d8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sminsorted.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sminsorted)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sminsorted_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp deleted file mode 100644 index 6a69ec5a76b3..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sminsorted.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sminsorted { - - /** - * Computes the minimum value of a sorted single-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: sorted input array - * - `stride`: stride length - */ - napi_value node_sminsorted( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sminsorted( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sminsorted, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sminsorted diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/main.c b/lib/node_modules/@stdlib/stats/base/sminsorted/src/main.c new file mode 100644 index 000000000000..5141b7d0bd7b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/src/main.c @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sminsorted.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/assert/is_negative_zerof.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the minimum value of a sorted single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sminsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sminsorted_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X sorted input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sminsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + float v1; + float v2; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + v1 = X[ offsetX ]; + v2 = X[ ( (N-1)*strideX ) + offsetX ]; + if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) { + return 0.0f / 0.0f; // NaN + } + if ( v1 == v2 ) { + if ( stdlib_base_is_negative_zerof( v1 ) || stdlib_base_is_negative_zerof( v2 ) ) { + return -0.0f; + } + return v1; + } + if ( v1 < v2 ) { + return v1; + } + return v2; +} diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/sminsorted.c b/lib/node_modules/@stdlib/stats/base/sminsorted/src/sminsorted.c deleted file mode 100644 index 010e8b4fecf3..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/src/sminsorted.c +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sminsorted.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include "stdlib/math/base/assert/is_negative_zerof.h" -#include - -/** -* Computes the minimum value of a sorted single-precision floating-point strided array. -* -* @param N number of indexed elements -* @param X sorted input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sminsorted( const int64_t N, const float *X, const int64_t stride ) { - float v1; - float v2; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - v1 = X[ (1-N) * stride ]; - v2 = X[ 0 ]; - } else { - v1 = X[ 0 ]; - v2 = X[ (N-1) * stride ]; - } - if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) { - return 0.0f / 0.0f; // NaN - } - if ( v1 == v2 ) { - if ( stdlib_base_is_negative_zerof( v1 ) || stdlib_base_is_negative_zerof( v2 ) ) { - return -0.0f; - } - return v1; - } - if ( v1 < v2 ) { - return v1; - } - return v2; -} diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js index 957da06a2064..b04416da13d8 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, 2, 0 ); + v = sminsorted( 4, x, 2, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, -2, 6 ); + v = sminsorted( 4, x, -2, 6 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, 2, 1 ); + v = sminsorted( 4, x, 2, 1 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js index 63b639f20159..31a8b7596f9c 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0, 2.0, // 1 -7.0, - 3.0, // 2 + 3.0, // 2 3.0, 4.0, // 3 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, 2, 0 ); + v = sminsorted( 4, x, 2, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, -2, 6 ); + v = sminsorted( 4, x, -2, 6 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, 2, 1 ); + v = sminsorted( 4, x, 2, 1 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js index 1335e2c4c2b5..8dcf5387c212 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, 2 ); + v = sminsorted( 4, x, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, -2 ); + v = sminsorted( 4, x, -2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sminsorted( N, x1, 2 ); + v = sminsorted( 4, x1, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js index 5ce498094816..56d2100968ad 100644 --- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js +++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, 2 ); + v = sminsorted( 4, x, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sminsorted( N, x, -2 ); + v = sminsorted( 4, x, -2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sminsorted( N, x1, 2 ); + v = sminsorted( 4, x1, 2 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/README.md b/lib/node_modules/@stdlib/stats/base/smskmax/README.md index e2ad2ab9bbfa..71bb372c047c 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/README.md +++ b/lib/node_modules/@stdlib/stats/base/smskmax/README.md @@ -38,7 +38,7 @@ var smskmax = require( '@stdlib/stats/base/smskmax' ); #### smskmax( N, x, strideX, mask, strideMask ) -Computes the maximum value of a single-precision floating-point strided array `x` according to a `mask`. +Computes the maximum value of a single-precision floating-point strided array according to a mask. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -55,22 +55,20 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation. -- **strideMask**: index increment for `mask`. +- **strideMask**: stride length for `mask`. -The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the maximum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = smskmax( N, x, 2, mask, 2 ); +var v = smskmax( 4, x, 2, mask, 2 ); // returns 4.0 ``` @@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element @@ -89,15 +86,13 @@ var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smskmax( N, x1, 2, mask1, 2 ); +var v = smskmax( 4, x1, 2, mask1, 2 ); // returns 4.0 ``` #### smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) -Computes the maximum value of a single-precision floating-point strided array according to a `mask` and using alternative indexing semantics. +Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -115,18 +110,16 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetMask**: starting index for `mask`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the maximum value for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = smskmax.ndarray( N, x, 2, 1, mask, 2, 1 ); +var v = smskmax.ndarray( 4, x, 2, 1, mask, 2, 1 ); // returns 4.0 ``` @@ -151,26 +144,19 @@ var v = smskmax.ndarray( N, x, 2, 1, mask, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var smskmax = require( '@stdlib/stats/base/smskmax' ); -var mask; -var x; -var i; - -x = new Float32Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); @@ -182,6 +168,125 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smskmax.h" +``` + +#### stdlib_strided_smskmax( N, \*X, strideX, \*Mask, strideMask ) + +Computes the maximum value of a single-precision floating-point strided array according to a mask. + +```c +#include + +const float x[] = { 1.0f, -2.0f, 2.0f }; +const uint8_t mask[] = { 0, 1, 0 }; + +float v = stdlib_strided_smskmax( 3, x, 1, mask, 1 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. + +```c +float stdlib_strided_smskmax( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); +``` + + + +#### stdlib_strided_smskmax_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask ) + +Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. + +```c +#include + +const float x[] = { 1.0f, -2.0f, 2.0f }; +const uint8_t mask[] = { 0, 1, 0 }; + +float v = stdlib_strided_smskmax( 3, x, 1, 0, mask, 1, 0 ); +// returns 2.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. +- **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`. + +```c +float stdlib_strided_smskmax_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smskmax.h" +#include +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f }; + + // Create a mask array: + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride lengths: + const int strideX = 2; + const int strideMask = 2; + + // Compute the maximum value: + float v = stdlib_strided_smskmax( N, x, strideX, mask, strideMask ); + + // Print the result: + printf( "max: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js index 47997f5b23a1..b254209a6c8f 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var smskmax = require( './../lib/smskmax.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var smskmax = require( './../lib/smskmax.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js index 1dda873319e0..34565afb2736 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var smskmax = tryRequire( resolve( __dirname, './../lib/smskmax.native.js' ) ); var opts = { 'skip': ( smskmax instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js index 8688bb4b952f..9973aec76ca4 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var smskmax = require( './../lib/ndarray.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var smskmax = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js index 428acc411123..bbb9f4179406 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var smskmax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( smskmax instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c index ec8aea961efe..93db04f3976e 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { unsigned char mask[ len ]; double elapsed; float x[ len ]; @@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smskmax( len, x, 1, mask, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + unsigned char mask[ len ]; + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + mask[ i ] = 1; // missing + } else { + mask[ i ] = 0; + } + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smskmax_ndarray( len, x, 1, 0, mask, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -148,7 +189,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt index fdf6aeed93b9..f754e875f8da 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt @@ -3,8 +3,8 @@ Computes the maximum value of a single-precision floating-point strided array according to a mask. - The `N` and `stride` parameters determine which elements are accessed at - runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce offsets, use a typed array views. @@ -26,13 +26,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. mask: Uint8Array Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. Returns ------- @@ -50,8 +50,7 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, mask, 2 ) + > {{alias}}( 3, x, 2, mask, 2 ) 2.0 // Using view offsets: @@ -59,10 +58,10 @@ > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, mask1, 2 ) + > {{alias}}( 3, x1, 2, mask1, 2 ) 2.0 + {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. @@ -80,7 +79,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -89,7 +88,7 @@ Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. offsetMask: integer Starting index for `mask`. @@ -110,8 +109,7 @@ // Using offset parameter: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 ) 2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c index 7104cc61b476..ef9f92b60f1a 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c @@ -22,17 +22,17 @@ int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f }; // Create a mask array: - uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; // Specify the number of elements: - int64_t N = 5; + const int N = 5; // Specify the stride lengths: - int64_t strideX = 2; - int64_t strideMask = 2; + const int strideX = 2; + const int strideMask = 2; // Compute the maximum value: float v = stdlib_strided_smskmax( N, x, strideX, mask, strideMask ); diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js b/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js index f591561cf536..08c7e8393443 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js @@ -18,26 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var smskmax = require( './../lib' ); -var mask; -var x; -var i; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; -x = new Float32Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi b/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' /* @@ -31,7 +32,12 @@ extern "C" { /** * Computes the maximum value of a single-precision floating-point strided array according to a mask. */ -float stdlib_strided_smskmax( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ); +float API_SUFFIX(stdlib_strided_smskmax)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); + +/** +* Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smskmax_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js index dac40cd51c57..dcd23b298e2d 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js @@ -37,14 +37,12 @@ * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smskmax = require( '@stdlib/stats/base/smskmax' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskmax.ndarray( N, x, 2, 1, mask, 2, 1 ); +* var v = smskmax.ndarray( 5, x, 2, 1, mask, 2, 1 ); * // returns 4.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js index 645818caaa6b..5223d6302d3c 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js @@ -41,13 +41,11 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskmax( N, x, 2, 1, mask, 2, 1 ); +* var v = smskmax( 5, x, 2, 1, mask, 2, 1 ); * // returns 4.0 */ function smskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js index ea92fb555efb..837b973303ec 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); -var addon = require( './smskmax.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -42,27 +40,15 @@ var addon = require( './smskmax.native.js' ); * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskmax( N, x, 2, 1, mask, 2, 1 ); +* var v = smskmax( 5, x, 2, 1, mask, 2, 1 ); * // returns 4.0 */ function smskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { - var viewX; - var viewM; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideMask < 0 ) { - offsetMask += (N-1) * strideMask; - } - viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len - return addon( N, viewX, strideX, viewM, strideMask ); + return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js index f7f26f8618fb..11616551b44d 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -47,55 +47,9 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); * // returns 2.0 */ function smskmax( N, x, strideX, mask, strideMask ) { - var max; - var ix; - var im; - var v; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( mask[ im ] === 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i === N ) { - return NaN; - } - max = x[ ix ]; - if ( isnanf( max ) ) { - return max; - } - i += 1; - for ( i; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( mask[ im ] ) { - continue; - } - v = x[ ix ]; - if ( isnanf( v ) ) { - return v; - } - if ( v > max || ( v === max && isPositiveZerof( v ) ) ) { - max = v; - } - } - return max; + var ox = stride2offset( N, strideX ); + var om = stride2offset( N, strideMask ); + return ndarray( N, x, strideX, ox, mask, strideMask, om ); } diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json b/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json index 28dc8675bba9..cce54abfb135 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,79 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smskmax.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-positive-zerof", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/argv-strided-uint8array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-positive-zerof" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nanf", "@stdlib/math/base/assert/is-positive-zerof" ] diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c new file mode 100644 index 000000000000..58cfc0b30502 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smskmax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/argv_strided_uint8array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smskmax)( N, X, strideX, Mask, strideMask ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smskmax_ndarray)( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp deleted file mode 100644 index d886197df62e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp +++ /dev/null @@ -1,153 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smskmax.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smskmax { - - /** - * Computes the maximum value of a single-precision floating-point strided array according to a mask. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Mask`: mask array - * - `strideMask`: `Mask` stride length - */ - napi_value node_smskmax( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideMask; - status = napi_get_value_int64( env, argv[ 4 ], &strideMask ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t mlen; - void *Mask; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_uint8_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smskmax( N, (float *)X, strideX, (uint8_t *)Mask, strideMask ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smskmax, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smskmax diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/main.c b/lib/node_modules/@stdlib/stats/base/smskmax/src/main.c new file mode 100644 index 000000000000..ab94f2006259 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smskmax/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smskmax.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/assert/is_positive_zerof.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include + +/** +* Computes the maximum value of a single-precision floating-point strided array according to a mask. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Mask mask array +* @param strideMask Mask stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smskmax)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask ); + return API_SUFFIX(stdlib_strided_smskmax_ndarray)( N, X, strideX, ox, Mask, strideMask, om ); +} + +/** +* Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Mask mask array +* @param strideMask Mask stride length +* @param offsetMask starting index for Mask +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smskmax_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) { + CBLAS_INT ix; + CBLAS_INT im; + CBLAS_INT i; + float max; + float v; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + ix = offsetX; + im = offsetMask; + for ( i = 0; i < N; i++ ) { + if ( Mask[ im ] == 0 ) { + break; + } + ix += strideX; + im += strideMask; + } + if ( i == N ) { + return 0.0f / 0.0f; // NaN + } + max = X[ ix ]; + if ( stdlib_base_is_nanf( max ) ) { + return 0.0f / 0.0f; // NaN + } + i += 1; + for (; i < N; i++ ) { + ix += strideX; + im += strideMask; + if ( Mask[ im ] ) { + continue; + } + v = X[ ix ]; + if ( stdlib_base_is_nanf( v ) ) { + return 0.0f / 0.0f; // NaN + } + if ( v > max || ( v == max && stdlib_base_is_positive_zerof( v ) ) ) { + max = v; + } + } + return max; +} diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/smskmax.c b/lib/node_modules/@stdlib/stats/base/smskmax/src/smskmax.c deleted file mode 100644 index ad890d782b67..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smskmax/src/smskmax.c +++ /dev/null @@ -1,84 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smskmax.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include "stdlib/math/base/assert/is_positive_zerof.h" -#include - -/** -* Computes the maximum value of a single-precision floating-point strided array according to a mask. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Mask mask array -* @param strideMask Mask stride length -* @return output value -*/ -float stdlib_strided_smskmax( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) { - int64_t ix; - int64_t im; - int64_t i; - float max; - float v; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( Mask[ im ] == 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i == N ) { - return 0.0f / 0.0f; // NaN - } - max = X[ ix ]; - if ( stdlib_base_is_nanf( max ) ) { - return 0.0f / 0.0f; // NaN - } - i += 1; - for (; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( Mask[ im ] ) { - continue; - } - v = X[ ix ]; - if ( stdlib_base_is_nanf( v ) ) { - return 0.0f / 0.0f; // NaN - } - if ( v > max || ( v == max && stdlib_base_is_positive_zerof( v ) ) ) { - max = v; - } - } - return max; -} diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js index d08097930cb4..509a5f2a53c2 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, 2, 0, mask, 2, 0 ); + v = smskmax( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, -2, 8, mask, -2, 8 ); + v = smskmax( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { tape( 'the function supports `offset` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, 2, 1, mask, 2, 1 ); + v = smskmax( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js index e280af72a159..de09098a5eab 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu v = smskmax( 0, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnanf( v ), true, 'returns expected value' ); - v = smskmax( -1, x, 1, 0, mask, 1 ); + v = smskmax( -1, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnanf( v ), true, 'returns expected value' ); t.end(); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, 2, 0, mask, 2, 0 ); + v = smskmax( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, -2, 8, mask, -2, 8 ); + v = smskmax( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test( tape( 'the function supports `offset` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, 2, 1, mask, 2, 1 ); + v = smskmax( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js index 841e5625dad0..1e1507f85132 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, 2, mask, 2 ); + v = smskmax( 5, x, 2, mask, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, -2, mask, -2 ); + v = smskmax( 5, x, -2, mask, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = smskmax( N, x1, 2, mask1, 2 ); + v = smskmax( 5, x1, 2, mask1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js index 56ed75b21da2..921cc8928926 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, 2, mask, 2 ); + v = smskmax( 5, x, 2, mask, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = smskmax( N, x, -2, mask, -2 ); + v = smskmax( 5, x, -2, mask, -2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); @@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = smskmax( N, x1, 2, mask1, 2 ); + v = smskmax( 5, x1, 2, mask1, 2 ); t.strictEqual( v, 4.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/README.md b/lib/node_modules/@stdlib/stats/base/smskmin/README.md index 438ef08759dd..b0148329d337 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/README.md +++ b/lib/node_modules/@stdlib/stats/base/smskmin/README.md @@ -38,7 +38,7 @@ var smskmin = require( '@stdlib/stats/base/smskmin' ); #### smskmin( N, x, strideX, mask, strideMask ) -Computes the minimum value of a single-precision floating-point strided array `x` according to a `mask`. +Computes the minimum value of a single-precision floating-point strided array according to a mask. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -55,22 +55,20 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation. -- **strideMask**: index increment for `mask`. +- **strideMask**: stride length for `mask`. -The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the minimum value of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 7.0, -2.0, -4.0, 3.0, -5.0, -6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = smskmin( N, x, 2, mask, 2 ); +var v = smskmin( 4, x, 2, mask, 2 ); // returns -4.0 ``` @@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element @@ -89,15 +86,13 @@ var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smskmin( N, x1, 2, mask1, 2 ); +var v = smskmin( 4, x1, 2, mask1, 2 ); // returns -2.0 ``` #### smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) -Computes the minimum value of a single-precision floating-point strided array according to a `mask` and using alternative indexing semantics. +Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -115,18 +110,16 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetMask**: starting index for `mask`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the minimum value for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = smskmin.ndarray( N, x, 2, 1, mask, 2, 1 ); +var v = smskmin.ndarray( 4, x, 2, 1, mask, 2, 1 ); // returns -2.0 ``` @@ -151,26 +144,19 @@ var v = smskmin.ndarray( N, x, 2, 1, mask, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var smskmin = require( '@stdlib/stats/base/smskmin' ); -var mask; -var x; -var i; - -x = new Float32Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); @@ -182,6 +168,125 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smskmin.h" +``` + +#### stdlib_strided_smskmin( N, \*X, strideX, \*Mask, strideMask ) + +Computes the minimum value of a single-precision floating-point strided array according to a mask. + +```c +#include + +const float x[] = { 1.0f, -2.0f, 2.0f }; +const uint8_t mask[] = { 0, 1, 0 }; + +float v = stdlib_strided_smskmin( 3, x, 1, mask, 1 ); +// returns 1.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. + +```c +float stdlib_strided_smskmin( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); +``` + + + +#### stdlib_strided_smskmin_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask ) + +Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. + +```c +#include + +const float x[] = { 1.0f, -2.0f, 2.0f }; +const uint8_t mask[] = { 0, 1, 0 }; + +float v = stdlib_strided_smskmin( 3, x, 1, 0, mask, 1, 0 ); +// returns 1.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. +- **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`. + +```c +float stdlib_strided_smskmin_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smskmin.h" +#include +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f }; + + // Create a mask array: + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride lengths: + const int strideX = 2; + const int strideMask = 2; + + // Compute the minimum value: + float v = stdlib_strided_smskmin( N, x, strideX, mask, strideMask ); + + // Print the result: + printf( "min: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js index 471c2ac0c4a9..3fafcab185f0 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var smskmin = require( './../lib/smskmin.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var smskmin = require( './../lib/smskmin.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js index e1bfc310b5c6..4867be6bec1c 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var smskmin = tryRequire( resolve( __dirname, './../lib/smskmin.native.js' ) ); var opts = { 'skip': ( smskmin instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js index c5c025a0b737..369e4216d24a 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var smskmin = require( './../lib/ndarray.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var smskmin = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js index f33919372b7c..150638f7797a 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var smskmin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( smskmin instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c index 00ce0704edd4..7fca587720f6 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { unsigned char mask[ len ]; double elapsed; float x[ len ]; @@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smskmin( len, x, 1, mask, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + unsigned char mask[ len ]; + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + mask[ i ] = 1; // missing + } else { + mask[ i ] = 0; + } + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smskmin_ndarray( len, x, 1, 0, mask, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -148,7 +189,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt index 636adf41126f..430e74a3d1c4 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt @@ -3,8 +3,8 @@ Computes the minimum value of a single-precision floating-point strided array according to a mask. - The `N` and `stride` parameters determine which elements are accessed at - runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce offsets, use a typed array views. @@ -26,13 +26,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. mask: Uint8Array Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. Returns ------- @@ -47,11 +47,10 @@ > {{alias}}( x.length, x, 1, mask, 1 ) -2.0 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, mask, 2 ) + > {{alias}}( 3, x, 2, mask, 2 ) -2.0 // Using view offsets: @@ -59,10 +58,10 @@ > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, mask1, 2 ) + > {{alias}}( 3, x1, 2, mask1, 2 ) -2.0 + {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. @@ -80,7 +79,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -89,7 +88,7 @@ Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. offsetMask: integer Starting index for `mask`. @@ -110,8 +109,7 @@ // Using offset parameter: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 ) -2.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c index 551febff6aad..0d1e8106827e 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c @@ -22,17 +22,17 @@ int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f }; // Create a mask array: - uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; // Specify the number of elements: - int64_t N = 5; + const int N = 5; // Specify the stride lengths: - int64_t strideX = 2; - int64_t strideMask = 2; + const int strideX = 2; + const int strideMask = 2; // Compute the minimum value: float v = stdlib_strided_smskmin( N, x, strideX, mask, strideMask ); diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js b/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js index 8c2afc2c7d38..8d8fb3138e8f 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js @@ -18,26 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var smskmin = require( './../lib' ); -var mask; -var x; -var i; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; -x = new Float32Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi b/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' /* @@ -31,7 +32,12 @@ extern "C" { /** * Computes the minimum value of a single-precision floating-point strided array according to a mask. */ -float stdlib_strided_smskmin( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ); +float API_SUFFIX(stdlib_strided_smskmin)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); + +/** +* Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smskmin_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js index ed69d14be484..bc09c6e5c326 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js @@ -37,14 +37,12 @@ * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smskmin = require( '@stdlib/stats/base/smskmin' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskmin.ndarray( N, x, 2, 1, mask, 2, 1 ); +* var v = smskmin.ndarray( 5, x, 2, 1, mask, 2, 1 ); * // returns -2.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js index c8c4ecdfa914..35b86124278b 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js @@ -41,13 +41,11 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskmin( N, x, 2, 1, mask, 2, 1 ); +* var v = smskmin( 5, x, 2, 1, mask, 2, 1 ); * // returns -2.0 */ function smskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js index f473b63a9a7c..7dc599165947 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); -var addon = require( './smskmin.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -52,17 +50,7 @@ var addon = require( './smskmin.native.js' ); * // returns -2.0 */ function smskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { - var viewX; - var viewM; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideMask < 0 ) { - offsetMask += (N-1) * strideMask; - } - viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len - return addon( N, viewX, strideX, viewM, strideMask ); + return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js index e673b47c6137..899799e0850c 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js @@ -20,8 +20,8 @@ // MODULES // -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -47,55 +47,9 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); * // returns -2.0 */ function smskmin( N, x, strideX, mask, strideMask ) { - var min; - var ix; - var im; - var v; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( mask[ im ] === 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i === N ) { - return NaN; - } - min = x[ ix ]; - if ( isnanf( min ) ) { - return min; - } - i += 1; - for ( i; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( mask[ im ] ) { - continue; - } - v = x[ ix ]; - if ( isnanf( v ) ) { - return v; - } - if ( v < min || ( v === min && isNegativeZerof( v ) ) ) { - min = v; - } - } - return min; + var ox = stride2offset( N, strideX ); + var om = stride2offset( N, strideMask ); + return ndarray( N, x, strideX, ox, mask, strideMask, om ); } diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json b/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json index e277545bd6d8..6fdc59ed195e 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,79 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smskmin.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-negative-zerof", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/argv-strided-uint8array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-negative-zerof" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/math/base/assert/is-negative-zerof" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nanf", "@stdlib/math/base/assert/is-negative-zerof" ] diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c new file mode 100644 index 000000000000..f26d4ca1722f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smskmin.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/argv_strided_uint8array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smskmin)( N, X, strideX, Mask, strideMask ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smskmin_ndarray)( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp deleted file mode 100644 index b8a4e250d35f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp +++ /dev/null @@ -1,153 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smskmin.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smskmin { - - /** - * Computes the minimum value of a single-precision floating-point strided array according to a mask. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Mask`: mask array - * - `strideMask`: `Mask` stride length - */ - napi_value node_smskmin( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideMask; - status = napi_get_value_int64( env, argv[ 4 ], &strideMask ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t mlen; - void *Mask; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_uint8_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smskmin( N, (float *)X, strideX, (uint8_t *)Mask, strideMask ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smskmin, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smskmin diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/main.c b/lib/node_modules/@stdlib/stats/base/smskmin/src/main.c new file mode 100644 index 000000000000..ace83332caf5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smskmin/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smskmin.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/math/base/assert/is_negative_zerof.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include + +/** +* Computes the minimum value of a single-precision floating-point strided array according to a mask. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Mask mask array +* @param strideMask Mask stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smskmin)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask ); + return API_SUFFIX(stdlib_strided_smskmin_ndarray)( N, X, strideX, ox, Mask, strideMask, om ); +} + +/** +* Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Mask mask array +* @param strideMask Mask stride length +* @param offsetMask starting index for Mask +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smskmin_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) { + CBLAS_INT ix; + CBLAS_INT im; + CBLAS_INT i; + float min; + float v; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + ix = offsetX; + im = offsetMask; + for ( i = 0; i < N; i++ ) { + if ( Mask[ im ] == 0 ) { + break; + } + ix += strideX; + im += strideMask; + } + if ( i == N ) { + return 0.0f / 0.0f; // NaN + } + min = X[ ix ]; + if ( stdlib_base_is_nanf( min ) ) { + return 0.0f / 0.0f; // NaN + } + i += 1; + for (; i < N; i++ ) { + ix += strideX; + im += strideMask; + if ( Mask[ im ] ) { + continue; + } + v = X[ ix ]; + if ( stdlib_base_is_nanf( v ) ) { + return 0.0f / 0.0f; // NaN + } + if ( v < min || ( v == min && stdlib_base_is_negative_zerof( v ) ) ) { + min = v; + } + } + return min; +} diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/smskmin.c b/lib/node_modules/@stdlib/stats/base/smskmin/src/smskmin.c deleted file mode 100644 index fabb56941c92..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smskmin/src/smskmin.c +++ /dev/null @@ -1,84 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smskmin.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include "stdlib/math/base/assert/is_negative_zerof.h" -#include - -/** -* Computes the minimum value of a single-precision floating-point strided array according to a mask. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Mask mask array -* @param strideMask Mask stride length -* @return output value -*/ -float stdlib_strided_smskmin( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) { - int64_t ix; - int64_t im; - int64_t i; - float min; - float v; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( Mask[ im ] == 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i == N ) { - return 0.0f / 0.0f; // NaN - } - min = X[ ix ]; - if ( stdlib_base_is_nanf( min ) ) { - return 0.0f / 0.0f; // NaN - } - i += 1; - for (; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( Mask[ im ] ) { - continue; - } - v = X[ ix ]; - if ( stdlib_base_is_nanf( v ) ) { - return 0.0f / 0.0f; // NaN - } - if ( v < min || ( v == min && stdlib_base_is_negative_zerof( v ) ) ) { - min = v; - } - } - return min; -} diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js index 2b365f6f8315..083be7f8dce7 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, 2, 0, mask, 2, 0 ); + v = smskmin( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, -2, 8, mask, -2, 8 ); + v = smskmin( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { tape( 'the function supports `offset` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, 2, 1, mask, 2, 1 ); + v = smskmin( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js index 5242fea20c17..03603c536c73 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu v = smskmin( 0, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnanf( v ), true, 'returns expected value' ); - v = smskmin( -1, x, 1, 0, mask, 1 ); + v = smskmin( -1, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnanf( v ), true, 'returns expected value' ); t.end(); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, 2, 0, mask, 2, 0 ); + v = smskmin( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, -2, 8, mask, -2, 8 ); + v = smskmin( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test( tape( 'the function supports `offset` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, 2, 1, mask, 2, 1 ); + v = smskmin( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js index 9555714033a1..e9c3b38ad928 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, 2, mask, 2 ); + v = smskmin( 5, x, 2, mask, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, -2, mask, -2 ); + v = smskmin( 5, x, -2, mask, -2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = smskmin( N, x1, 2, mask1, 2 ); + v = smskmin( 5, x1, 2, mask1, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js index b529948e34e9..be0553016e32 100644 --- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, 2, mask, 2 ); + v = smskmin( 5, x, 2, mask, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = smskmin( N, x, -2, mask, -2 ); + v = smskmin( 5, x, -2, mask, -2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); @@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = smskmin( N, x1, 2, mask1, 2 ); + v = smskmin( 5, x1, 2, mask1, 2 ); t.strictEqual( v, -2.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/README.md b/lib/node_modules/@stdlib/stats/base/smskrange/README.md index b2816e520d9c..e63c44af60bb 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/README.md +++ b/lib/node_modules/@stdlib/stats/base/smskrange/README.md @@ -40,7 +40,7 @@ var smskrange = require( '@stdlib/stats/base/smskrange' ); #### smskrange( N, x, strideX, mask, strideMask ) -Computes the [range][range] of a single-precision floating-point strided array `x` according to a `mask`. +Computes the [range][range] of a single-precision floating-point strided array according to a mask. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -57,22 +57,20 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **strideX**: index increment for `x`. +- **strideX**: stride length for `x`. - **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation. -- **strideMask**: index increment for `mask`. +- **strideMask**: stride length for `mask`. -The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the [range][range] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the [range][range] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = smskrange( N, x, 2, mask, 2 ); +var v = smskrange( 4, x, 2, mask, 2 ); // returns 11.0 ``` @@ -83,7 +81,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element @@ -91,15 +88,13 @@ var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = smskrange( N, x1, 2, mask1, 2 ); +var v = smskrange( 4, x1, 2, mask1, 2 ); // returns 6.0 ``` #### smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) -Computes the [range][range] of a single-precision floating-point strided array according to a `mask` and using alternative indexing semantics. +Computes the [range][range] of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -117,18 +112,16 @@ The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetMask**: starting index for `mask`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [range][range] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the [range][range] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); var Uint8Array = require( '@stdlib/array/uint8' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); -var N = floor( x.length / 2 ); -var v = smskrange.ndarray( N, x, 2, 1, mask, 2, 1 ); +var v = smskrange.ndarray( 4, x, 2, 1, mask, 2, 1 ); // returns 6.0 ``` @@ -153,26 +146,19 @@ var v = smskrange.ndarray( N, x, 2, 1, mask, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var smskrange = require( '@stdlib/stats/base/smskrange' ); -var mask; -var x; -var i; - -x = new Float32Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); @@ -184,6 +170,125 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/smskrange.h" +``` + +#### stdlib_strided_smskrange( N, \*X, strideX, \*Mask, strideMask ) + +Computes the [range][range] of a single-precision floating-point strided array according to a mask. + +```c +#include + +const float x[] = { 1.0f, -2.0f, 2.0f }; +const uint8_t mask[] = { 0, 1, 0 }; + +float v = stdlib_strided_smskrange( 3, x, 1, mask, 1 ); +// returns 1.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. + +```c +float stdlib_strided_smskrange( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); +``` + + + +#### stdlib_strided_smskrange_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask ) + +Computes the [range][range] of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. + +```c +#include + +const float x[] = { 1.0f, -2.0f, 2.0f }; +const uint8_t mask[] = { 0, 1, 0 }; + +float v = stdlib_strided_smskrange( 3, x, 1, 0, mask, 1, 0 ); +// returns 1.0f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. +- **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. +- **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`. + +```c +float stdlib_strided_smskrange_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/smskrange.h" +#include +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f }; + + // Create a mask array: + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + + // Specify the number of elements: + const int N = 5; + + // Specify the stride lengths: + const int strideX = 2; + const int strideMask = 2; + + // Compute the range: + float v = stdlib_strided_smskrange( N, x, strideX, mask, strideMask ); + + // Print the result: + printf( "range: %f\n", v ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js index 5a5b591a0bfa..62f5bb0783f6 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var smskrange = require( './../lib/smskrange.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var smskrange = require( './../lib/smskrange.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js index c17bcdd06803..f88173beb42d 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var smskrange = tryRequire( resolve( __dirname, './../lib/smskrange.native.js' ) var opts = { 'skip': ( smskrange instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js index bf308f0f9834..7a4187e30aec 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js @@ -21,15 +21,24 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var pkg = require( './../package.json' ).name; var smskrange = require( './../lib/ndarray.js' ); +// VARIABLES // + +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; + + // FUNCTIONS // /** @@ -40,20 +49,8 @@ var smskrange = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js index 9d761ad414ce..2dbfb2c311fe 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js @@ -22,11 +22,10 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -37,6 +36,12 @@ var smskrange = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( smskrange instanceof Error ) }; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; // FUNCTIONS // @@ -49,20 +54,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var mask; - var x; - var i; - - x = new Float32Array( len ); - mask = new Uint8Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var mask = bernoulli( len, 0.2, bernoulliOptions ); + var x = uniform( len, -10.0, 10.0, uniformOptions ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c index 8530c1a782eb..f71175f6c01f 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { unsigned char mask[ len ]; double elapsed; float x[ len ]; @@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_smskrange( len, x, 1, mask, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + unsigned char mask[ len ]; + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + mask[ i ] = 1; // missing + } else { + mask[ i ] = 0; + } + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_smskrange_ndarray( len, x, 1, 0, mask, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -148,7 +189,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt index b8fdf5db347b..8e8aefcc405f 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt @@ -3,8 +3,8 @@ Computes the range of a single-precision floating-point strided array according to a mask. - The `N` and `stride` parameters determine which elements are accessed at - runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce offsets, use a typed array views. @@ -26,13 +26,13 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. mask: Uint8Array Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. Returns ------- @@ -50,8 +50,7 @@ // Using `N` and `stride` parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, x, 2, mask, 2 ) + > {{alias}}( 3, x, 2, mask, 2 ) 4.0 // Using view offsets: @@ -59,10 +58,10 @@ > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, x1, 2, mask1, 2 ) + > {{alias}}( 3, x1, 2, mask1, 2 ) 4.0 + {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) Computes the range of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. @@ -80,7 +79,7 @@ Input array. strideX: integer - Index increment for `x`. + Stride length for `x`. offsetX: integer Starting index for `x`. @@ -89,7 +88,7 @@ Mask array. strideMask: integer - Index increment for `mask`. + Stride length for `mask`. offsetMask: integer Starting index for `mask`. @@ -110,8 +109,7 @@ // Using offset parameter: > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] ); > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 ) + > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 ) 4.0 See Also diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c index a0c6f6f8148a..66cea0336e64 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c @@ -22,17 +22,17 @@ int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f }; // Create a mask array: - uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; + const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; // Specify the number of elements: - int64_t N = 5; + const int N = 5; // Specify the stride lengths: - int64_t strideX = 2; - int64_t strideMask = 2; + const int strideX = 2; + const int strideMask = 2; // Compute the range: float v = stdlib_strided_smskrange( N, x, strideX, mask, strideMask ); diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js b/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js index 4d2c7d22f6dc..f39eab3a7777 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js @@ -18,26 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var bernoulli = require( '@stdlib/random/array/bernoulli' ); var smskrange = require( './../lib' ); -var mask; -var x; -var i; +var uniformOptions = { + 'dtype': 'float32' +}; +var bernoulliOptions = { + 'dtype': 'uint8' +}; -x = new Float32Array( 10 ); -mask = new Uint8Array( x.length ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - mask[ i ] = 1; - } else { - mask[ i ] = 0; - } - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = uniform( 10, -50.0, 50.0, uniformOptions ); +var mask = bernoulli( x.length, 0.2, bernoulliOptions ); console.log( x ); console.log( mask ); diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi b/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' /* @@ -31,7 +32,12 @@ extern "C" { /** * Computes the range of a single-precision floating-point strided array according to a mask. */ -float stdlib_strided_smskrange( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ); +float API_SUFFIX(stdlib_strided_smskrange)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); + +/** +* Computes the range of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_smskrange_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js index 7d80a61a3b01..706215b9af9d 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js @@ -37,14 +37,12 @@ * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var smskrange = require( '@stdlib/stats/base/smskrange' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskrange.ndarray( N, x, 2, 1, mask, 2, 1 ); +* var v = smskrange.ndarray( 5, x, 2, 1, mask, 2, 1 ); * // returns 6.0 */ diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js index 6adc0019d3b8..b5e440b85c6b 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js @@ -41,13 +41,11 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskrange( N, x, 2, 1, mask, 2, 1 ); +* var v = smskrange( 5, x, 2, 1, mask, 2, 1 ); * // returns 6.0 */ function smskrange( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js index fd585dddcb46..a78caef56b78 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js @@ -20,9 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var Uint8Array = require( '@stdlib/array/uint8' ); -var addon = require( './smskrange.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -42,27 +40,15 @@ var addon = require( './smskrange.native.js' ); * @example * var Float32Array = require( '@stdlib/array/float32' ); * var Uint8Array = require( '@stdlib/array/uint8' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] ); -* var N = floor( x.length / 2 ); * -* var v = smskrange( N, x, 2, 1, mask, 2, 1 ); +* var v = smskrange( 5, x, 2, 1, mask, 2, 1 ); * // returns 6.0 */ function smskrange( N, x, strideX, offsetX, mask, strideMask, offsetMask ) { - var viewX; - var viewM; - if ( strideX < 0 ) { - offsetX += (N-1) * strideX; - } - if ( strideMask < 0 ) { - offsetMask += (N-1) * strideMask; - } - viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len - viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len - return addon( N, viewX, strideX, viewM, strideMask ); + return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js index 4271ae2074a7..2ebbc7254dc4 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js @@ -20,8 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -47,59 +47,9 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); * // returns 4.0 */ function smskrange( N, x, strideX, mask, strideMask ) { - var max; - var min; - var ix; - var im; - var v; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( mask[ im ] === 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i === N ) { - return NaN; - } - min = x[ ix ]; - if ( isnanf( min ) ) { - return min; - } - max = min; - i += 1; - for ( i; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( mask[ im ] ) { - continue; - } - v = x[ ix ]; - if ( isnanf( v ) ) { - return v; - } - if ( v < min ) { - min = v; - } else if ( v > max ) { - max = v; - } - } - return float64ToFloat32( max - min ); + var ox = stride2offset( N, strideX ); + var om = stride2offset( N, strideMask ); + return ndarray( N, x, strideX, ox, mask, strideMask, om ); } diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json b/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json index c7df6f471c22..e0c0f648c89a 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,76 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/smskrange.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/argv-strided-uint8array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/math/base/assert/is-nanf" ] } diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c new file mode 100644 index 000000000000..f4099c0c4d48 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smskrange.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/argv_strided_uint8array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smskrange)( N, X, strideX, Mask, strideMask ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_smskrange_ndarray)( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp deleted file mode 100644 index 5293805d7560..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp +++ /dev/null @@ -1,153 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smskrange.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_smskrange { - - /** - * Computes the range of a single-precision floating-point strided array according to a mask. - * - * ## Notes - * - * - When called from JavaScript, the function expects five arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `strideX`: `X` stride length - * - `Mask`: mask array - * - `strideMask`: `Mask` stride length - */ - napi_value node_smskrange( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 5; - napi_value argv[ 5 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 5 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res1; - status = napi_is_typedarray( env, argv[ 1 ], &res1 ); - assert( status == napi_ok ); - if ( res1 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - bool res3; - status = napi_is_typedarray( env, argv[ 3 ], &res3 ); - assert( status == napi_ok ); - if ( res3 == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - - napi_valuetype vtype4; - status = napi_typeof( env, argv[ 4 ], &vtype4 ); - assert( status == napi_ok ); - if ( vtype4 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t strideX; - status = napi_get_value_int64( env, argv[ 2 ], &strideX ); - assert( status == napi_ok ); - - int64_t strideMask; - status = napi_get_value_int64( env, argv[ 4 ], &strideMask ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_typedarray_type vtype3; - size_t mlen; - void *Mask; - status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype3 != napi_uint8_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." ); - return nullptr; - } - if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_smskrange( N, (float *)X, strideX, (uint8_t *)Mask, strideMask ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smskrange, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_smskrange diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/main.c b/lib/node_modules/@stdlib/stats/base/smskrange/src/main.c new file mode 100644 index 000000000000..f77c8b190320 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/smskrange/src/main.c @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/smskrange.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include + +/** +* Computes the range of a single-precision floating-point strided array according to a mask. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Mask mask array +* @param strideMask Mask stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smskrange)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask ); + return API_SUFFIX(stdlib_strided_smskrange_ndarray)( N, X, strideX, ox, Mask, strideMask, om ); +} + +/** +* Computes the range of a single-precision floating-point strided array according to a mask and using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Mask mask array +* @param strideMask Mask stride length +* @param offsetMask starting index for Mask +* @return output value +*/ +float API_SUFFIX(stdlib_strided_smskrange_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) { + CBLAS_INT ix; + CBLAS_INT im; + CBLAS_INT i; + float max; + float min; + float v; + + if ( N <= 0 ) { + return 0.0f / 0.0f; // NaN + } + ix = offsetX; + im = offsetMask; + for ( i = 0; i < N; i++ ) { + if ( Mask[ im ] == 0 ) { + break; + } + ix += strideX; + im += strideMask; + } + if ( i == N ) { + return 0.0f / 0.0f; // NaN + } + min = X[ ix ]; + if ( stdlib_base_is_nanf( min ) ) { + return 0.0f / 0.0f; // NaN + } + max = min; + i += 1; + for (; i < N; i++ ) { + ix += strideX; + im += strideMask; + if ( Mask[ im ] ) { + continue; + } + v = X[ ix ]; + if ( stdlib_base_is_nanf( v ) ) { + return 0.0f / 0.0f; // NaN + } + if ( v < min ) { + min = v; + } else if ( v > max ) { + max = v; + } + } + return max - min; +} diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/smskrange.c b/lib/node_modules/@stdlib/stats/base/smskrange/src/smskrange.c deleted file mode 100644 index 76f8f58b90ec..000000000000 --- a/lib/node_modules/@stdlib/stats/base/smskrange/src/smskrange.c +++ /dev/null @@ -1,87 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/smskrange.h" -#include "stdlib/math/base/assert/is_nanf.h" -#include - -/** -* Computes the range of a single-precision floating-point strided array according to a mask. -* -* @param N number of indexed elements -* @param X input array -* @param strideX X stride length -* @param Mask mask array -* @param strideMask Mask stride length -* @return output value -*/ -float stdlib_strided_smskrange( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) { - int64_t ix; - int64_t im; - int64_t i; - float max; - float min; - float v; - - if ( N <= 0 ) { - return 0.0f / 0.0f; // NaN - } - if ( strideX < 0 ) { - ix = (1-N) * strideX; - } else { - ix = 0; - } - if ( strideMask < 0 ) { - im = (1-N) * strideMask; - } else { - im = 0; - } - for ( i = 0; i < N; i++ ) { - if ( Mask[ im ] == 0 ) { - break; - } - ix += strideX; - im += strideMask; - } - if ( i == N ) { - return 0.0f / 0.0f; // NaN - } - min = X[ ix ]; - if ( stdlib_base_is_nanf( min ) ) { - return 0.0f / 0.0f; // NaN - } - max = min; - i += 1; - for (; i < N; i++ ) { - ix += strideX; - im += strideMask; - if ( Mask[ im ] ) { - continue; - } - v = X[ ix ]; - if ( stdlib_base_is_nanf( v ) ) { - return 0.0f / 0.0f; // NaN - } - if ( v < min ) { - min = v; - } else if ( v > max ) { - max = v; - } - } - return max - min; -} diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js index a6cd963b305a..c76c1e7e3649 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', fun tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, 2, 0, mask, 2, 0 ); + v = smskrange( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, -2, 8, mask, -2, 8 ); + v = smskrange( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { tape( 'the function supports `offset` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, 2, 1, mask, 2, 1 ); + v = smskrange( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js index d917632f957c..ff73ab2f459e 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu v = smskrange( 0, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnanf( v ), true, 'returns expected value' ); - v = smskrange( -1, x, 1, 0, mask, 1 ); + v = smskrange( -1, x, 1, 0, mask, 1, 0 ); t.strictEqual( isnanf( v ), true, 'returns expected value' ); t.end(); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', opt tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, 2, 0, mask, 2, 0 ); + v = smskrange( 5, x, 2, 0, mask, 2, 0 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, -2, 8, mask, -2, 8 ); + v = smskrange( 5, x, -2, 8, mask, -2, 8 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test( tape( 'the function supports `offset` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) { 1, 1 // 4 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, 2, 1, mask, 2, 1 ); + v = smskrange( 5, x, 2, 1, mask, 2, 1 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js index e1b424e0a57b..829148a81b61 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', fun tape( 'the function supports `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, 2, mask, 2 ); + v = smskrange( 5, x, 2, mask, 2 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) { tape( 'the function supports negative `stride` parameters', function test( t ) { var mask; - var N; var x; var v; @@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) { 0 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, -2, mask, -2 ); + v = smskrange( 5, x, -2, mask, -2 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = smskrange( N, x1, 2, mask1, 2 ); + v = smskrange( 5, x1, 2, mask1, 2 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js index 99aebd738b93..4dad84d3ec10 100644 --- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js +++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', opt tape( 'the function supports `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { 1 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, 2, mask, 2 ); + v = smskrange( 5, x, 2, mask, 2 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) { tape( 'the function supports negative `stride` parameters', opts, function test( t ) { var mask; - var N; var x; var v; @@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test( 0 ]); - N = floor( x.length / 2 ); - v = smskrange( N, x, -2, mask, -2 ); + v = smskrange( 5, x, -2, mask, -2 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); @@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var mask1; var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor( x1.length/2 ); - v = smskrange( N, x1, 2, mask1, 2 ); + v = smskrange( 5, x1, 2, mask1, 2 ); t.strictEqual( v, 6.0, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/snanmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanmax/docs/repl.txt index caef57994607..9a6bb2612e5f 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmax/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/snanmax/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/snanmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanmax/src/addon.c index f7217a4b3fd8..326fb3233757 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmax/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/snanmax/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/snanmax.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmax( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanmax)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmax_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanmax_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/snanmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanmaxabs/docs/repl.txt index c29db10babed..97254ae921ea 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmaxabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/snanmaxabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -64,7 +64,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/snanmaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanmaxabs/src/addon.c index 8c16b476a185..58e3de9207b2 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmaxabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/snanmaxabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/snanmaxabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmaxabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanmaxabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmaxabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanmaxabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/snanmean/include.gypi b/lib/node_modules/@stdlib/stats/base/snanmean/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmean/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanmean/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmean( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanmean/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanmean/src/addon.cpp deleted file mode 100644 index 2d7ec86ae26b..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanmean/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanmean.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanmean { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanmean( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanmean( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanmean, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanmean diff --git a/lib/node_modules/@stdlib/stats/base/snanmeanors/include.gypi b/lib/node_modules/@stdlib/stats/base/snanmeanors/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmeanors/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanmeanors/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmeanors( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanmeanors/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanmeanors/src/addon.cpp deleted file mode 100644 index 4c44691564d0..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanmeanors/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanmeanors.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanmeanors { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanmeanors( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanmeanors( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanmeanors, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanmeanors diff --git a/lib/node_modules/@stdlib/stats/base/snanmeanpn/include.gypi b/lib/node_modules/@stdlib/stats/base/snanmeanpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmeanpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanmeanpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmeanpn( N, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanmeanpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanmeanpn/src/addon.cpp deleted file mode 100644 index 7ff459f9d6aa..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanmeanpn/src/addon.cpp +++ /dev/null @@ -1,117 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanmeanpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanmeanpn { - - /** - * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects three arguments: - * - * - `N`: number of indexed elements - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanmeanpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 3; - napi_value argv[ 3 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 3 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 1 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype2; - status = napi_typeof( env, argv[ 2 ], &vtype2 ); - assert( status == napi_ok ); - if ( vtype2 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 2 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype1; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype1 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanmeanpn( N, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanmeanpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanmeanpn diff --git a/lib/node_modules/@stdlib/stats/base/snanmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanmin/docs/repl.txt index bd12cbb05c2a..99170e029f1e 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmin/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/snanmin/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/snanmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanmin/src/addon.c index d5f2e67d0f71..e36768c26789 100644 --- a/lib/node_modules/@stdlib/stats/base/snanmin/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/snanmin/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/snanmin.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmin( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanmin)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanmin_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanmin_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/snanminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanminabs/docs/repl.txt index 42217e100067..f7f18a82315c 100644 --- a/lib/node_modules/@stdlib/stats/base/snanminabs/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/snanminabs/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -64,7 +64,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/snanminabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanminabs/src/addon.c index d621975b1d36..3841945ad564 100644 --- a/lib/node_modules/@stdlib/stats/base/snanminabs/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/snanminabs/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/snanminabs.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanminabs( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanminabs)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanminabs_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanminabs_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/snanrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanrange/docs/repl.txt index 4843c9294708..4434e141f3e0 100644 --- a/lib/node_modules/@stdlib/stats/base/snanrange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/snanrange/docs/repl.txt @@ -20,7 +20,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -63,7 +63,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/snanrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanrange/src/addon.c index 341ae4a6f487..3b3fe7fe8a80 100644 --- a/lib/node_modules/@stdlib/stats/base/snanrange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/snanrange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/snanrange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanrange( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanrange)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanrange_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanrange_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevch( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp deleted file mode 100644 index ff8de9c5c6d6..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanstdevch.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanstdevch { - - /** - * Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanstdevch( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanstdevch( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevch, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanstdevch diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevpn( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp deleted file mode 100644 index 19a75e25bb53..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanstdevpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanstdevpn { - - /** - * Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanstdevpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanstdevpn( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanstdevpn diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevtk( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp deleted file mode 100644 index 0b8b81775319..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanstdevtk.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanstdevtk { - - /** - * Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanstdevtk( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanstdevtk( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevtk, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanstdevtk diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevwd( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp deleted file mode 100644 index 1da417d16c69..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanstdevwd.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanstdevwd { - - /** - * Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanstdevwd( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanstdevwd( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevwd, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanstdevwd diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevyc( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp deleted file mode 100644 index ecaf47683a53..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanstdevyc.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanstdevyc { - - /** - * Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanstdevyc( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanstdevyc( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevyc, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanstdevyc diff --git a/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariance( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp deleted file mode 100644 index 43eb6036c054..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanvariance.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanvariance { - - /** - * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanvariance( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanvariance( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariance, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanvariance diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancech( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp deleted file mode 100644 index 9a88d0e0c69f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanvariancech.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanvariancech { - - /** - * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanvariancech( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanvariancech( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariancech, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanvariancech diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancetk( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp deleted file mode 100644 index d3c973cef0e7..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanvariancetk.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanvariancetk { - - /** - * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanvariancetk( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanvariancetk( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariancetk, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanvariancetk diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancewd( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp deleted file mode 100644 index 7903326e673f..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanvariancewd.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanvariancewd { - - /** - * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanvariancewd( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanvariancewd( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariancewd, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanvariancewd diff --git a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvarianceyc( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp deleted file mode 100644 index 3cc800e7bbbe..000000000000 --- a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/snanvarianceyc.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_snanvarianceyc { - - /** - * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_snanvarianceyc( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_snanvarianceyc( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvarianceyc, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_snanvarianceyc diff --git a/lib/node_modules/@stdlib/stats/base/srange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/srange/docs/repl.txt index 1b69b0e8eeb3..41a7f8952484 100644 --- a/lib/node_modules/@stdlib/stats/base/srange/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/srange/docs/repl.txt @@ -19,7 +19,7 @@ Input array. strideX: integer - Stride Length. + Stride length. Returns ------- @@ -62,7 +62,7 @@ Input array. strideX: integer - Stride Length. + Stride length. offsetX: integer Starting index. diff --git a/lib/node_modules/@stdlib/stats/base/srange/src/addon.c b/lib/node_modules/@stdlib/stats/base/srange/src/addon.c index a21211178c98..15d96715fefc 100644 --- a/lib/node_modules/@stdlib/stats/base/srange/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/srange/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/srange.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_srange( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_srange)( N, X, strideX ), v ); return v; } @@ -53,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_srange_ndarray( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_srange_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sstdev( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp deleted file mode 100644 index 3bd3a912050e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sstdev.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sstdev { - - /** - * Computes the standard deviation of a single-precision floating-point strided array. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_sstdev( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sstdev( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdev, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sstdev diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/README.md b/lib/node_modules/@stdlib/stats/base/sstdevch/README.md index 24a8bf737b56..1c93917e9cd2 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/README.md +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var sstdevch = require( '@stdlib/stats/base/sstdevch' ); ``` -#### sstdevch( N, correction, x, stride ) +#### sstdevch( N, correction, x, strideX ) Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -106,9 +106,8 @@ Computes the [standard deviation][standard-deviation] of a single-precision floa var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sstdevch( N, 1, x, 1 ); +var v = sstdevch( x.length, 1, x, 1 ); // returns ~2.0817 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = sstdevch( N, 1, x, 2 ); +var v = sstdevch( 4, 1, x, 2 ); // returns 2.5 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = sstdevch( N, 1, x1, 2 ); +var v = sstdevch( 4, 1, x1, 2 ); // returns 2.5 ``` -#### sstdevch.ndarray( N, correction, x, stride, offset ) +#### sstdevch.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [standard deviation][standard-deviation] of a single-precision floa var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sstdevch.ndarray( N, 1, x, 1, 0 ); +var v = sstdevch.ndarray( x.length, 1, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = sstdevch.ndarray( N, 1, x, 2, 1 ); +var v = sstdevch.ndarray( 4, 1, x, 2, 1 ); // returns 2.5 ``` @@ -203,18 +194,12 @@ var v = sstdevch.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sstdevch = require( '@stdlib/stats/base/sstdevch' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = sstdevch( x.length, 1, x, 1 ); @@ -225,6 +210,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/sstdevch.h" +``` + +#### stdlib_strided_sstdevch( N, correction, \*X, strideX ) + +Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_sstdevch( 3, 1.0f, x, 1 ); +// returns ~2.0817f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_sstdevch( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sstdevch_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_sstdevch_ndarray( 3, 1.0f, x, 1, 0 ); +// returns ~2.0817f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_sstdevch_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/sstdevch.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + float v = stdlib_strided_sstdevch( N, 1.0f, x, strideX ); + + // Print the result: + printf( "sample standard deviation: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.js index 663e54fed1ec..206951394d74 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sstdevch = require( './../lib/sstdevch.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var sstdevch = require( './../lib/sstdevch.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.native.js index 0777bdd0fa4c..2c14bddb6097 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var sstdevch = tryRequire( resolve( __dirname, './../lib/sstdevch.native.js' ) ) var opts = { 'skip': ( sstdevch instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.js index f91428cc52c1..cc4418ab0f17 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sstdevch = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var sstdevch = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.native.js index e3247026b535..c7149feff66f 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var sstdevch = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sstdevch instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/c/benchmark.length.c index 375597db721d..c2a390face9f 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sstdevch( len, 1.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sstdevch_ndarray( len, 1.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sstdevch/docs/repl.txt index 1f28293c2dcb..ed32838b4e4d 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~2.0817 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/sstdevch/docs/types/index.d.ts index 2991f80ea79f..7ff4ae469cf3 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = sstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: Float32Array, stride: number ): number; + ( N: number, correction: number, x: Float32Array, strideX: number ): number; /** * Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = sstdevch.ndarray( x.length, 1, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/sstdevch/examples/c/example.c index a925ebf869f0..1c421bc9e956 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/examples/c/example.c @@ -17,7 +17,6 @@ */ #include "stdlib/stats/base/sstdevch.h" -#include #include int main( void ) { @@ -25,13 +24,13 @@ int main( void ) { const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard deviation: - float v = stdlib_strided_sstdevch( N, 1, x, stride ); + float v = stdlib_strided_sstdevch( N, 1.0f, x, strideX ); // Print the result: printf( "sample standard deviation: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/examples/index.js b/lib/node_modules/@stdlib/stats/base/sstdevch/examples/index.js index aa4cd3c7d3f4..8b7991439029 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sstdevch = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = sstdevch( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. */ -float stdlib_strided_sstdevch( const int64_t N, const float correction, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sstdevch)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sstdevch_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/index.js b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/index.js index fefe0bed6918..178ead451581 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/index.js @@ -28,20 +28,17 @@ * var sstdevch = require( '@stdlib/stats/base/sstdevch' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sstdevch( N, 1, x, 1 ); +* var v = sstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var sstdevch = require( '@stdlib/stats/base/sstdevch' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sstdevch.ndarray( N, 1, x, 2, 1 ); +* var v = sstdevch.ndarray( 4, 1, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.js index 3e67ceca31d0..ebea54801db6 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.js @@ -20,9 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var svariancech = require( '@stdlib/stats/base/svariancech' ).ndarray; -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var sqrtf = require( '@stdlib/math/base/special/sqrtf' ); // MAIN // @@ -33,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sstdevch( N, 1, x, 2, 1 ); +* var v = sstdevch( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function sstdevch( N, correction, x, stride, offset ) { - return float64ToFloat32( sqrt( svariancech( N, correction, x, stride, offset ) ) ); // eslint-disable-line max-len +function sstdevch( N, correction, x, strideX, offsetX ) { + return sqrtf( svariancech( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.native.js index 177e2a759f3a..396cf28be1e8 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './sstdevch.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './sstdevch.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sstdevch( N, 1, x, 2, 1 ); +* var v = sstdevch( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function sstdevch( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function sstdevch( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.js b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.js index b674c47cad83..e9506bd0c2a8 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.js @@ -20,9 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var svariancech = require( '@stdlib/stats/base/svariancech' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -33,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sstdevch( N, 1, x, 1 ); +* var v = sstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function sstdevch( N, correction, x, stride ) { - return float64ToFloat32( sqrt( svariancech( N, correction, x, stride ) ) ); +function sstdevch( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.native.js b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.native.js index 1abab9c35be7..1cc9ba0329ba 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/lib/sstdevch.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sstdevch( N, 1, x, 1 ); +* var v = sstdevch( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function sstdevch( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function sstdevch( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json b/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json index a093653896c5..3c41125e784d 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,80 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/sstdevch.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", + "@stdlib/stats/base/svariancech", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", + "@stdlib/stats/base/svariancech" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", + "@stdlib/stats/base/svariancech" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", "@stdlib/stats/base/svariancech" ] } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c b/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c new file mode 100644 index 000000000000..4801553bba76 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sstdevch.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sstdevch)( N, correction, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sstdevch_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp deleted file mode 100644 index c8c2266b7b4e..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sstdevch.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sstdevch { - - /** - * Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_sstdevch( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sstdevch( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdevch, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sstdevch diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/src/main.c b/lib/node_modules/@stdlib/stats/base/sstdevch/src/main.c new file mode 100644 index 000000000000..a75922a72094 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sstdevch.h" +#include "stdlib/stats/base/svariancech.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/sqrtf.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sstdevch)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sstdevch_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sstdevch_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrtf( API_SUFFIX(stdlib_strided_svariancech_ndarray)( N, correction, X, strideX, offsetX ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/src/sstdevch.c b/lib/node_modules/@stdlib/stats/base/sstdevch/src/sstdevch.c deleted file mode 100644 index a360f8bd5e93..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/src/sstdevch.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sstdevch.h" -#include "stdlib/stats/base/svariancech.h" -#include -#include - -/** -* Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sstdevch( const int64_t N, const float correction, const float *X, const int64_t stride ) { - return sqrtf( stdlib_strided_svariancech( N, correction, X, stride ) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.js index f2b057687166..eda27ec1d66a 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -132,7 +131,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -147,15 +145,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, 2, 0 ); + v = sstdevch( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -170,8 +166,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, -2, 6 ); + v = sstdevch( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -204,9 +198,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, 2, 1 ); + v = sstdevch( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.native.js index f6003819471e..ec964b0f6e23 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -141,7 +140,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -156,15 +154,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, 2, 0 ); + v = sstdevch( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -179,8 +175,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, -2, 6 ); + v = sstdevch( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -199,7 +194,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -213,9 +207,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, 2, 1 ); + v = sstdevch( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.js b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.js index 42533852c78e..84c53b7055e3 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -132,7 +131,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -147,15 +145,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, 2 ); + v = sstdevch( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -170,8 +166,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, -2 ); + v = sstdevch( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -192,7 +187,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -208,9 +202,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sstdevch( N, 1, x1, 2 ); + v = sstdevch( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.native.js b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.native.js index b1df91e34db1..e548096497cc 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevch/test/test.sstdevch.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -141,7 +140,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -156,15 +154,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, 2 ); + v = sstdevch( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -179,8 +175,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevch( N, 1, x, -2 ); + v = sstdevch( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -201,7 +196,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -217,9 +211,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sstdevch( N, 1, x1, 2 ); + v = sstdevch( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sstdevpn( N, correction, X, stride ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp deleted file mode 100644 index a1e51a8fb99a..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sstdevpn.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sstdevpn { - - /** - * Computes the standard deviation of a single-precision floating-point strided array using a two-pass algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_sstdevpn( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sstdevpn( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdevpn, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sstdevpn diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/README.md b/lib/node_modules/@stdlib/stats/base/sstdevtk/README.md index 86674e29aff4..1498c1b4c16d 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var sstdevtk = require( '@stdlib/stats/base/sstdevtk' ); ``` -#### sstdevtk( N, correction, x, stride ) +#### sstdevtk( N, correction, x, strideX ) Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array `x` using a one-pass textbook algorithm. @@ -106,9 +106,8 @@ Computes the [standard deviation][standard-deviation] of a single-precision floa var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sstdevtk( N, 1, x, 1 ); +var v = sstdevtk( x.length, 1, x, 1 ); // returns ~2.0817 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = sstdevtk( N, 1, x, 2 ); +var v = sstdevtk( 4, 1, x, 2 ); // returns 2.5 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = sstdevtk( N, 1, x1, 2 ); +var v = sstdevtk( 4, 1, x1, 2 ); // returns 2.5 ``` -#### sstdevtk.ndarray( N, correction, x, stride, offset ) +#### sstdevtk.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [standard deviation][standard-deviation] of a single-precision floa var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = sstdevtk.ndarray( N, 1, x, 1, 0 ); +var v = sstdevtk.ndarray( x.length, 1, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = sstdevtk.ndarray( N, 1, x, 2, 1 ); +var v = sstdevtk.ndarray( 4, 1, x, 2, 1 ); // returns 2.5 ``` @@ -203,18 +194,12 @@ var v = sstdevtk.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sstdevtk = require( '@stdlib/stats/base/sstdevtk' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = sstdevtk( x.length, 1, x, 1 ); @@ -225,6 +210,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/sstdevtk.h" +``` + +#### stdlib_strided_sstdevtk( N, correction, \*X, strideX ) + +Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array using a one-pass textbook algorithm. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_sstdevtk( 3, 1.0f, x, 1 ); +// returns ~2.0817f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_sstdevtk( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sstdevtk_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [standard deviation][standard-deviation] of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_sstdevtk_ndarray( 3, 1.0f, x, 1, 0 ); +// returns ~2.0817f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_sstdevtk_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/sstdevtk.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the standard deviation: + float v = stdlib_strided_sstdevtk( N, 1.0f, x, strideX ); + + // Print the result: + printf( "sample standard deviation: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.js index 05de32988883..ec40ebb180dd 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sstdevtk = require( './../lib/sstdevtk.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var sstdevtk = require( './../lib/sstdevtk.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.native.js index b1c66f23ec2e..f6523e340361 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var sstdevtk = tryRequire( resolve( __dirname, './../lib/sstdevtk.native.js' ) ) var opts = { 'skip': ( sstdevtk instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.js index d2b415197ca6..ce3e1a9beb39 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var sstdevtk = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var sstdevtk = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.native.js index 6a84ddf986f0..9e51fb20c09e 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var sstdevtk = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { 'skip': ( sstdevtk instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/c/benchmark.length.c index b6c3a8e591c8..c9f82507574f 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_sstdevtk( len, 1.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_sstdevtk_ndarray( len, 1.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/repl.txt index f83b2be549e7..7a5e015582f8 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~2.0817 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,8 +107,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/types/index.d.ts index 0325f1cef5b5..8835c1211427 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = sstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: Float32Array, stride: number ): number; + ( N: number, correction: number, x: Float32Array, strideX: number ): number; /** * Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = sstdevtk.ndarray( x.length, 1, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/c/example.c index 657892c7aa22..1cdc2edd5df7 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/sstdevtk.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the standard deviation: - float v = stdlib_strided_sstdevtk( N, 1.0f, x, stride ); + float v = stdlib_strided_sstdevtk( N, 1.0f, x, strideX ); // Print the result: printf( "sample standard deviation: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/index.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/index.js index 5ca813c1cfaa..23cb58c3550d 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var sstdevtk = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = sstdevtk( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi index 868c5c12e852..26476a8c2655 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi @@ -36,7 +36,7 @@ # Source files: 'src_files': [ - '<(src_dir)/addon.cpp', + '<(src_dir)/addon.c', ' +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. */ -float stdlib_strided_sstdevtk( const int64_t N, const float correction, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_sstdevtk)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_sstdevtk_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/index.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/index.js index 3279d7c0c5f2..4536a63c9ba7 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/index.js @@ -28,20 +28,17 @@ * var sstdevtk = require( '@stdlib/stats/base/sstdevtk' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sstdevtk( N, 1, x, 1 ); +* var v = sstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var sstdevtk = require( '@stdlib/stats/base/sstdevtk' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sstdevtk.ndarray( N, 1, x, 2, 1 ); +* var v = sstdevtk.ndarray( 4, 1, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.js index 22a5aa92c5c1..ea4dd05a113b 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.js @@ -20,9 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var svariancetk = require( '@stdlib/stats/base/svariancetk' ).ndarray; -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var sqrtf = require( '@stdlib/math/base/special/sqrtf' ); // MAIN // @@ -33,22 +32,20 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sstdevtk( N, 1, x, 2, 1 ); +* var v = sstdevtk( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function sstdevtk( N, correction, x, stride, offset ) { - return float64ToFloat32( sqrt( svariancetk( N, correction, x, stride, offset ) ) ); // eslint-disable-line max-len +function sstdevtk( N, correction, x, strideX, offsetX ) { + return sqrtf( svariancetk( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.native.js index acddf0abe4ac..4eef67c6335b 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './sstdevtk.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './sstdevtk.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = sstdevtk( N, 1, x, 2, 1 ); +* var v = sstdevtk( 4, 1, x, 2, 1 ); * // returns 2.5 */ -function sstdevtk( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function sstdevtk( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.js index 4af02be1e10c..f9f5dbf19af6 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.js @@ -20,9 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var svariancetk = require( '@stdlib/stats/base/svariancetk' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -33,20 +32,19 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sstdevtk( N, 1, x, 1 ); +* var v = sstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function sstdevtk( N, correction, x, stride ) { - return float64ToFloat32( sqrt( svariancetk( N, correction, x, stride ) ) ); +function sstdevtk( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.native.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.native.js index da92dca89fc9..0f907d47fda6 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/lib/sstdevtk.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = sstdevtk( N, 1, x, 1 ); +* var v = sstdevtk( x.length, 1, x, 1 ); * // returns ~2.0817 */ -function sstdevtk( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function sstdevtk( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json b/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json index 52ce8a7859a2..1c762ef1fad2 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -24,17 +27,80 @@ ], "confs": [ { + "task": "build", + "wasm": false, "src": [ - "./src/sstdevtk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", + "@stdlib/stats/base/svariancetk", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", + "@stdlib/stats/base/svariancetk" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", + "@stdlib/stats/base/svariancetk" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/special/sqrtf", "@stdlib/stats/base/svariancetk" ] } diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c new file mode 100644 index 000000000000..fc51ae12b2a7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sstdevtk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sstdevtk)( N, correction, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_sstdevtk_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp deleted file mode 100644 index e5cf7ae08a37..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp +++ /dev/null @@ -1,130 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sstdevtk.h" -#include -#include -#include -#include -#include - -/** -* Add-on namespace. -*/ -namespace stdlib_stats_base_sstdevtk { - - /** - * Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. - * - * ## Notes - * - * - When called from JavaScript, the function expects four arguments: - * - * - `N`: number of indexed elements - * - `correction`: degrees of freedom adjustment - * - `X`: input array - * - `stride`: stride length - */ - napi_value node_sstdevtk( napi_env env, napi_callback_info info ) { - napi_status status; - - size_t argc = 4; - napi_value argv[ 4 ]; - status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr ); - assert( status == napi_ok ); - - if ( argc < 4 ) { - napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." ); - return nullptr; - } - - napi_valuetype vtype0; - status = napi_typeof( env, argv[ 0 ], &vtype0 ); - assert( status == napi_ok ); - if ( vtype0 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." ); - return nullptr; - } - - napi_valuetype vtype1; - status = napi_typeof( env, argv[ 1 ], &vtype1 ); - assert( status == napi_ok ); - if ( vtype1 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." ); - return nullptr; - } - - bool res; - status = napi_is_typedarray( env, argv[ 2 ], &res ); - assert( status == napi_ok ); - if ( res == false ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - - napi_valuetype vtype3; - status = napi_typeof( env, argv[ 3 ], &vtype3 ); - assert( status == napi_ok ); - if ( vtype3 != napi_number ) { - napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." ); - return nullptr; - } - - int64_t N; - status = napi_get_value_int64( env, argv[ 0 ], &N ); - assert( status == napi_ok ); - - double correction; - status = napi_get_value_double( env, argv[ 1 ], &correction ); - assert( status == napi_ok ); - - int64_t stride; - status = napi_get_value_int64( env, argv[ 3 ], &stride ); - assert( status == napi_ok ); - - napi_typedarray_type vtype2; - size_t xlen; - void *X; - status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr ); - assert( status == napi_ok ); - if ( vtype2 != napi_float32_array ) { - napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." ); - return nullptr; - } - if ( (N-1)*llabs(stride) >= (int64_t)xlen ) { - napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." ); - return nullptr; - } - - napi_value v; - status = napi_create_double( env, (double)stdlib_strided_sstdevtk( N, (float)correction, (float *)X, stride ), &v ); - assert( status == napi_ok ); - - return v; - } - - napi_value Init( napi_env env, napi_value exports ) { - napi_status status; - napi_value fcn; - status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdevtk, NULL, &fcn ); - assert( status == napi_ok ); - return fcn; - } - - NAPI_MODULE( NODE_GYP_MODULE_NAME, Init ) -} // end namespace stdlib_stats_base_sstdevtk diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/main.c b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/main.c new file mode 100644 index 000000000000..6851d2876fe9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/main.c @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/sstdevtk.h" +#include "stdlib/stats/base/svariancetk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/special/sqrtf.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sstdevtk)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_sstdevtk_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_sstdevtk_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + return stdlib_base_sqrtf( API_SUFFIX(stdlib_strided_svariancetk_ndarray)( N, correction, X, strideX, offsetX ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/sstdevtk.c b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/sstdevtk.c deleted file mode 100644 index 460798fb1faf..000000000000 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/sstdevtk.c +++ /dev/null @@ -1,35 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/sstdevtk.h" -#include "stdlib/stats/base/svariancetk.h" -#include -#include - -/** -* Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_sstdevtk( const int64_t N, const float correction, const float *X, const int64_t stride ) { - return sqrtf( stdlib_strided_svariancetk( N, correction, X, stride ) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.js index 2035f0ed1093..525b1541db08 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -132,7 +131,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -147,15 +145,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, 2, 0 ); + v = sstdevtk( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -170,8 +166,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, -2, 6 ); + v = sstdevtk( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -190,7 +185,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -204,9 +198,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, 2, 1 ); + v = sstdevtk( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.native.js index 73b8b8943f7d..917cbb81a727 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -141,7 +140,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -156,15 +154,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, 2, 0 ); + v = sstdevtk( 4, 1, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -179,8 +175,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, -2, 6 ); + v = sstdevtk( 4, 1, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -199,7 +194,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -213,9 +207,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, 2, 1 ); + v = sstdevtk( 4, 1, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.js index fa773ac22269..7e5192e11387 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -132,7 +131,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -147,15 +145,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, 2 ); + v = sstdevtk( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -170,8 +166,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, -2 ); + v = sstdevtk( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -192,7 +187,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -208,9 +202,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sstdevtk( N, 1, x1, 2 ); + v = sstdevtk( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.native.js b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.native.js index 0289ba091ca6..2aed3408d827 100644 --- a/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.native.js +++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/test/test.sstdevtk.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var abs = require( '@stdlib/math/base/special/abs' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); @@ -141,7 +140,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -156,15 +154,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, 2 ); + v = sstdevtk( 4, 1, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -179,8 +175,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = sstdevtk( N, 1, x, -2 ); + v = sstdevtk( 4, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -201,7 +196,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -217,9 +211,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = sstdevtk( N, 1, x1, 2 ); + v = sstdevtk( 4, 1, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/README.md b/lib/node_modules/@stdlib/stats/base/svariancech/README.md index 5ce6463a8869..77a42a2410ff 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/README.md +++ b/lib/node_modules/@stdlib/stats/base/svariancech/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var svariancech = require( '@stdlib/stats/base/svariancech' ); ``` -#### svariancech( N, correction, x, stride ) +#### svariancech( N, correction, x, strideX ) Computes the [variance][variance] of a single-precision floating-point strided array `x` using a one-pass trial mean algorithm. @@ -106,9 +106,8 @@ Computes the [variance][variance] of a single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = svariancech( N, 1, x, 1 ); +var v = svariancech( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = svariancech( N, 1, x, 2 ); +var v = svariancech( 4, 1, x, 2 ); // returns 6.25 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = svariancech( N, 1, x1, 2 ); +var v = svariancech( 4, 1, x1, 2 ); // returns 6.25 ``` -#### svariancech.ndarray( N, correction, x, stride, offset ) +#### svariancech.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [variance][variance] of a single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = svariancech.ndarray( N, 1, x, 1, 0 ); +var v = svariancech.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = svariancech.ndarray( N, 1, x, 2, 1 ); +var v = svariancech.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -203,18 +194,12 @@ var v = svariancech.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var svariancech = require( '@stdlib/stats/base/svariancech' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = svariancech( x.length, 1, x, 1 ); @@ -225,6 +210,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/svariancech.h" +``` + +#### stdlib_strided_svariancech( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass trial mean algorithm. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_svariancech( 3, 1.0f, x, 1 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_svariancech( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_svariancech_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_svariancech_ndarray( 3, 1.0f, x, 1, 0 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_svariancech_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/svariancech.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + float v = stdlib_strided_svariancech( N, 1.0f, x, strideX ); + + // Print the result: + printf( "sample variance: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.js index 22aef2e6c6f3..00594a670f28 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var svariancech = require( './../lib/svariancech.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var svariancech = require( './../lib/svariancech.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.native.js index 18664692c881..e3a0318931aa 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var svariancech = tryRequire( resolve( __dirname, './../lib/svariancech.native.j var opts = { 'skip': ( svariancech instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.js index 5f5ebe3520a9..edcac8ff8af9 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var svariancech = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var svariancech = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.native.js index 2f7f5ff76d19..861da256e2bf 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var svariancech = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( svariancech instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/c/benchmark.length.c index 094ee2ab4aac..1115b18e28f7 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/svariancech/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_svariancech( len, 1.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_svariancech_ndarray( len, 1.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/svariancech/docs/repl.txt index e9b42ff0eab2..63e3ebfa40f1 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/svariancech/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed + The `N` and stride parameters determine which elements in `x` are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -31,8 +31,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -89,10 +86,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -109,8 +106,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/svariancech/docs/types/index.d.ts index b9868dc971f0..f42a47f880ca 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/svariancech/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = svariancech( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float32Array, stride: number ): number; + ( N: number, correction: number, x: Float32Array, strideX: number ): number; /** * Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = svariancech.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/svariancech/examples/c/example.c index 4cd932ac2ba9..bd36ed41f9c3 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/svariancech/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/svariancech.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - float v = stdlib_strided_svariancech( N, 1.0f, x, stride ); + float v = stdlib_strided_svariancech( N, 1.0f, x, strideX ); // Print the result: printf( "sample variance: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/examples/index.js b/lib/node_modules/@stdlib/stats/base/svariancech/examples/index.js index d792f7f431ff..d42a70e4d701 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var svariancech = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = svariancech( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/include/stdlib/stats/base/svariancech.h b/lib/node_modules/@stdlib/stats/base/svariancech/include/stdlib/stats/base/svariancech.h index a4378f32c6c1..82f4ef22fb5e 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/include/stdlib/stats/base/svariancech.h +++ b/lib/node_modules/@stdlib/stats/base/svariancech/include/stdlib/stats/base/svariancech.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SVARIANCECH_H #define STDLIB_STATS_BASE_SVARIANCECH_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. */ -float stdlib_strided_svariancech( const int64_t N, const float correction, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_svariancech)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_svariancech_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/lib/index.js b/lib/node_modules/@stdlib/stats/base/svariancech/lib/index.js index a8c6056c4cb1..4379a4b2db15 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/lib/index.js @@ -28,20 +28,17 @@ * var svariancech = require( '@stdlib/stats/base/svariancech' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svariancech( N, 1, x, 1 ); +* var v = svariancech( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var svariancech = require( '@stdlib/stats/base/svariancech' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svariancech.ndarray( N, 1, x, 2, 1 ); +* var v = svariancech.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.js index 07d86d84cd29..192cde25b06c 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.js @@ -42,21 +42,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svariancech( N, 1, x, 2, 1 ); +* var v = svariancech( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function svariancech( N, correction, x, stride, offset ) { +function svariancech( N, correction, x, strideX, offsetX ) { var mu; var ix; var M2; @@ -69,14 +67,14 @@ function svariancech( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - ix = offset; + ix = offsetX; // Use an estimate for the mean: mu = x[ ix ]; - ix += stride; + ix += strideX; // Compute the variance... M2 = 0.0; @@ -85,7 +83,7 @@ function svariancech( N, correction, x, stride, offset ) { d = float64ToFloat32( x[ ix ] - mu ); M2 = float64ToFloat32( M2 + float64ToFloat32( d*d ) ); M = float64ToFloat32( M + d ); - ix += stride; + ix += strideX; } return float64ToFloat32( float64ToFloat32(M2/n) - float64ToFloat32( float64ToFloat32(M/N)*float64ToFloat32(M/n) ) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.native.js index 1a52aaeab82c..011ca2f8bc2d 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './svariancech.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './svariancech.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svariancech( N, 1, x, 2, 1 ); +* var v = svariancech( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function svariancech( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function svariancech( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.js b/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.js index 2beb4d08e5e5..e123513e872a 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.js @@ -20,7 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -42,53 +43,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svariancech( N, 1, x, 1 ); +* var v = svariancech( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function svariancech( N, correction, x, stride ) { - var mu; - var ix; - var M2; - var M; - var d; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - // Use an estimate for the mean: - mu = x[ ix ]; - ix += stride; - - // Compute the variance... - M2 = 0.0; - M = 0.0; - for ( i = 1; i < N; i++ ) { - d = float64ToFloat32( x[ ix ] - mu ); - M2 = float64ToFloat32( M2 + float64ToFloat32( d*d ) ); - M = float64ToFloat32( M + d ); - ix += stride; - } - return float64ToFloat32( float64ToFloat32(M2/n) - float64ToFloat32( float64ToFloat32(M/N)*float64ToFloat32(M/n) ) ); // eslint-disable-line max-len +function svariancech( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.native.js b/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.native.js index 131e0b70875e..81b7c0527276 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/lib/svariancech.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svariancech( N, 1, x, 1 ); +* var v = svariancech( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function svariancech( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function svariancech( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/manifest.json b/lib/node_modules/@stdlib/stats/base/svariancech/manifest.json index 3033ab4596d1..b608e04ab4e1 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/svariancech/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -26,53 +27,74 @@ ], "confs": [ { - "task": "build", + "task": "build", + "wasm": false, "src": [ - "./src/svariancech.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-float", "@stdlib/napi/argv-strided-float32array", - "@stdlib/napi/create-double", - "@stdlib/napi/argv-float" + "@stdlib/napi/create-double" ] }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/svariancech.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/svariancech.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/src/addon.c b/lib/node_modules/@stdlib/stats/base/svariancech/src/addon.c index 3eab2d06afa8..0077d11c5cf9 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/svariancech/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/svariancech.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,10 +37,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ) - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_svariancech( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_svariancech)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_svariancech_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/src/main.c b/lib/node_modules/@stdlib/stats/base/svariancech/src/main.c new file mode 100644 index 000000000000..e901a82dd69a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/svariancech/src/main.c @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/svariancech.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. +* +* ## Method +* +* - This implementation uses a one-pass trial mean approach, as suggested by Chan et al (1983). +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). +* - Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis, Ltd.: 242–47. doi:[10.1080/00031305.1983.10483115](https://doi.org/10.1080/00031305.1983.10483115). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_svariancech)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_svariancech_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_svariancech_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double dN; + double dM; + double n; + float mu; + float M2; + float M; + float d; + + dN = (double)N; + n = dN - (double)correction; + if ( N <= 0 || n <= 0.0f ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0f; + } + ix = offsetX; + // Use an estimate for the mean: + mu = X[ ix ]; + ix += strideX; + + // Compute the variance... + M2 = 0.0f; + M = 0.0f; + for ( i = 1; i < N; i++ ) { + d = X[ ix ] - mu; + M2 += d * d; + M += d; + ix += strideX; + } + dM = (double)M; + return (float)((double)M2/n) - ( (float)(dM/dN) * (float)(dM/n) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/src/svariancech.c b/lib/node_modules/@stdlib/stats/base/svariancech/src/svariancech.c deleted file mode 100644 index 9c253c3d52e6..000000000000 --- a/lib/node_modules/@stdlib/stats/base/svariancech/src/svariancech.c +++ /dev/null @@ -1,81 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/svariancech.h" -#include - -/** -* Computes the variance of a single-precision floating-point strided array using a one-pass trial mean algorithm. -* -* ## Method -* -* - This implementation uses a one-pass trial mean approach, as suggested by Chan et al (1983). -* -* ## References -* -* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). -* - Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154). -* - Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis, Ltd.: 242–47. doi:[10.1080/00031305.1983.10483115](https://doi.org/10.1080/00031305.1983.10483115). -* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_svariancech( const int64_t N, const float correction, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double dN; - double dM; - double n; - float mu; - float M2; - float M; - float d; - - dN = (double)N; - n = dN - (double)correction; - if ( N <= 0 || n <= 0.0f ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0f; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - // Use an estimate for the mean: - mu = X[ ix ]; - ix += stride; - - // Compute the variance... - M2 = 0.0f; - M = 0.0f; - for ( i = 1; i < N; i++ ) { - d = X[ ix ] - mu; - M2 += d * d; - M += d; - ix += stride; - } - dM = (double)M; - return (float)((double)M2/n) - ( (float)(dM/dN) * (float)(dM/n) ); -} diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.js index 54ffc7f1fce0..8320c6fa975a 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, 2, 0 ); + v = svariancech( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, -2, 6 ); + v = svariancech( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, 2, 1 ); + v = svariancech( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.native.js index 1378efaf0744..6d7d2daf7c00 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, 2, 0 ); + v = svariancech( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, -2, 6 ); + v = svariancech( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, 2, 1 ); + v = svariancech( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.js b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.js index d45205eb2a2e..ec070f6379ef 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, 2 ); + v = svariancech( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, -2 ); + v = svariancech( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = svariancech( N, 1, x1, 2 ); + v = svariancech( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.native.js b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.native.js index 873b18b7b974..d5abc24325f3 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancech/test/test.svariancech.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, 2 ); + v = svariancech( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = svariancech( N, 1, x, -2 ); + v = svariancech( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = svariancech( N, 1, x1, 2 ); + v = svariancech( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/README.md b/lib/node_modules/@stdlib/stats/base/svariancetk/README.md index 4b894f4dc155..12f336c325ab 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/README.md +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/README.md @@ -128,7 +128,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var svariancetk = require( '@stdlib/stats/base/svariancetk' ); ``` -#### svariancetk( N, correction, x, stride ) +#### svariancetk( N, correction, x, strideX ) Computes the [variance][variance] of a single-precision floating-point strided array `x` using a one-pass textbook algorithm. @@ -136,9 +136,8 @@ Computes the [variance][variance] of a single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = svariancetk( N, 1, x, 1 ); +var v = svariancetk( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -147,18 +146,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = svariancetk( N, 1, x, 2 ); +var v = svariancetk( 4, 1, x, 2 ); // returns 6.25 ``` @@ -168,18 +165,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = svariancetk( N, 1, x1, 2 ); +var v = svariancetk( 4, 1, x1, 2 ); // returns 6.25 ``` -#### svariancetk.ndarray( N, correction, x, stride, offset ) +#### svariancetk.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -187,26 +181,23 @@ Computes the [variance][variance] of a single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = svariancetk.ndarray( N, 1, x, 1, 0 ); +var v = svariancetk.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = svariancetk.ndarray( N, 1, x, 2, 1 ); +var v = svariancetk.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -233,18 +224,12 @@ var v = svariancetk.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var svariancetk = require( '@stdlib/stats/base/svariancetk' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = svariancetk( x.length, 1, x, 1 ); @@ -255,6 +240,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/svariancetk.h" +``` + +#### stdlib_strided_svariancetk( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass textbook algorithm. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_svariancetk( 3, 1.0f, x, 1 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_svariancetk( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_svariancetk_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_svariancetk_ndarray( 3, 1.0f, x, 1, 0 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_svariancetk_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/svariancetk.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + float v = stdlib_strided_svariancetk( N, 1.0f, x, strideX ); + + // Print the result: + printf( "sample variance: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.js index e6c17d389515..68820a10499a 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var svariancetk = require( './../lib/svariancetk.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var svariancetk = require( './../lib/svariancetk.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.native.js index 508cd67a79ee..f2950786c9a4 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var svariancetk = tryRequire( resolve( __dirname, './../lib/svariancetk.native.j var opts = { 'skip': ( svariancetk instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.js index 1be7a010f9ea..5fd2d978c543 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var svariancetk = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var svariancetk = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.native.js index b8ee9f86b8a8..4653bf3c9957 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var svariancetk = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( svariancetk instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/c/benchmark.length.c index de8acc00ca4d..be9104e27bb7 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_svariancetk( len, 1.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_svariancetk_ndarray( len, 1.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/svariancetk/docs/repl.txt index 3b0c5aa6b271..807fbf2a6c32 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/docs/repl.txt @@ -1,9 +1,9 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. - The `N` and `stride` parameters determine which elements in `x` are accessed + The `N` and stride parameters determine which elements in `x` are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed @@ -31,8 +31,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -89,10 +86,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -109,8 +106,7 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/svariancetk/docs/types/index.d.ts index 6a75bb018ed3..4e1d7827a817 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = svariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float32Array, stride: number ): number; + ( N: number, correction: number, x: Float32Array, strideX: number ): number; /** * Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = svariancetk.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/svariancetk/examples/c/example.c index 4909c52eb7ae..9698c2e7f97e 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/svariancetk.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - float v = stdlib_strided_svariancetk( N, 1, x, stride ); + float v = stdlib_strided_svariancetk( N, 1, x, strideX ); // Print the result: printf( "sample variance: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/examples/index.js b/lib/node_modules/@stdlib/stats/base/svariancetk/examples/index.js index 1a4a057f9488..4e89f58a31e2 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var svariancetk = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = svariancetk( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/include/stdlib/stats/base/svariancetk.h b/lib/node_modules/@stdlib/stats/base/svariancetk/include/stdlib/stats/base/svariancetk.h index b4a8f0cbd6a9..4f6366146d49 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/include/stdlib/stats/base/svariancetk.h +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/include/stdlib/stats/base/svariancetk.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SVARIANCETK_H #define STDLIB_STATS_BASE_SVARIANCETK_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. */ -float stdlib_strided_svariancetk( const int64_t N, const float correction, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_svariancetk)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_svariancetk_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/index.js b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/index.js index b9283ea995ac..5bb06e131722 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/index.js @@ -28,20 +28,17 @@ * var svariancetk = require( '@stdlib/stats/base/svariancetk' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svariancetk( N, 1, x, 1 ); +* var v = svariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var svariancetk = require( '@stdlib/stats/base/svariancetk' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svariancetk.ndarray( N, 1, x, 2, 1 ); +* var v = svariancetk.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.js index 07c97fee7a34..92296881aa92 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.js @@ -31,21 +31,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svariancetk( N, 1, x, 2, 1 ); +* var v = svariancetk( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function svariancetk( N, correction, x, stride, offset ) { +function svariancetk( N, correction, x, strideX, offsetX ) { var S2; var ix; var S; @@ -57,17 +55,17 @@ function svariancetk( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - ix = offset; + ix = offsetX; S2 = 0.0; S = 0.0; for ( i = 0; i < N; i++ ) { v = x[ ix ]; S2 = float64ToFloat32( S2 + float64ToFloat32( v*v ) ); S = float64ToFloat32( S+v ); - ix += stride; + ix += strideX; } return float64ToFloat32( float64ToFloat32(S2 - float64ToFloat32(float64ToFloat32(S/N)*S)) / n ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.native.js index 482170b170a4..16957455180b 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './svariancetk.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './svariancetk.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svariancetk( N, 1, x, 2, 1 ); +* var v = svariancetk( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function svariancetk( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function svariancetk( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.js b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.js index 66198282ad6c..e1a008842f14 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.js @@ -20,7 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -31,47 +32,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svariancetk( N, 1, x, 1 ); +* var v = svariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function svariancetk( N, correction, x, stride ) { - var S2; - var ix; - var S; - var v; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - S2 = 0.0; - S = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - S2 = float64ToFloat32( S2 + float64ToFloat32( v*v ) ); - S = float64ToFloat32( S+v ); - ix += stride; - } - return float64ToFloat32( float64ToFloat32(S2 - float64ToFloat32(float64ToFloat32(S/N)*S)) / n ); // eslint-disable-line max-len +function svariancetk( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.native.js b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.native.js index 7920c3aa65cd..a205afa0e5b0 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/lib/svariancetk.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svariancetk( N, 1, x, 1 ); +* var v = svariancetk( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function svariancetk( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function svariancetk( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/manifest.json b/lib/node_modules/@stdlib/stats/base/svariancetk/manifest.json index 2880e5ff0344..b608e04ab4e1 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -26,53 +27,74 @@ ], "confs": [ { - "task": "build", + "task": "build", + "wasm": false, "src": [ - "./src/svariancetk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-float", "@stdlib/napi/argv-strided-float32array", - "@stdlib/napi/create-double", - "@stdlib/napi/argv-float" + "@stdlib/napi/create-double" ] }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/svariancetk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/svariancetk.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/src/addon.c b/lib/node_modules/@stdlib/stats/base/svariancetk/src/addon.c index 01132ff6312d..596ae385aad3 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/svariancetk.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -36,10 +37,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2) - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_svariancetk( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ) + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_svariancetk)( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_svariancetk_ndarray)( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/src/main.c b/lib/node_modules/@stdlib/stats/base/svariancetk/src/main.c new file mode 100644 index 000000000000..d7929c0e8ad6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/src/main.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2025 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/svariancetk.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_svariancetk)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_svariancetk_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_svariancetk_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double dN; + double n; + float S2; + float S; + float v; + + dN = (double)N; + n = dN - (double)correction; + if ( N <= 0 || n <= 0.0f ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0f; + } + ix = offsetX; + S2 = 0.0f; + S = 0.0f; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + S2 += v * v; + S += v; + ix += strideX; + } + return (double)(S2 - ( (float)((double)S/dN) * S ) ) / n; +} diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/src/svariancetk.c b/lib/node_modules/@stdlib/stats/base/svariancetk/src/svariancetk.c deleted file mode 100644 index 1ab9705c4e1d..000000000000 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/src/svariancetk.c +++ /dev/null @@ -1,62 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/svariancetk.h" -#include - -/** -* Computes the variance of a single-precision floating-point strided array using a one-pass textbook algorithm. -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_svariancetk( const int64_t N, const float correction, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double dN; - double n; - float S2; - float S; - float v; - - dN = (double)N; - n = dN - (double)correction; - if ( N <= 0 || n <= 0.0f ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0f; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - S2 = 0.0f; - S = 0.0f; - for ( i = 0; i < N; i++ ) { - v = X[ ix ]; - S2 += v * v; - S += v; - ix += stride; - } - return (double)(S2 - ( (float)((double)S/dN) * S ) ) / n; -} diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.js index 286e9c481ddd..36b432ca4a2e 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, 2, 0 ); + v = svariancetk( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, -2, 6 ); + v = svariancetk( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, 2, 1 ); + v = svariancetk( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.native.js index b067183e9cf5..fc3d41f0e8c1 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, 2, 0 ); + v = svariancetk( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, -2, 6 ); + v = svariancetk( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, 2, 1 ); + v = svariancetk( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.js b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.js index 42b5f4638747..3b0e9d6b9e22 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, 2 ); + v = svariancetk( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, -2 ); + v = svariancetk( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = svariancetk( N, 1, x1, 2 ); + v = svariancetk( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.native.js b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.native.js index abdc71fcb029..a4a5940f8ee5 100644 --- a/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.native.js +++ b/lib/node_modules/@stdlib/stats/base/svariancetk/test/test.svariancetk.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, 2 ); + v = svariancetk( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = svariancetk( N, 1, x, -2 ); + v = svariancetk( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = svariancetk( N, 1, x1, 2 ); + v = svariancetk( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/README.md b/lib/node_modules/@stdlib/stats/base/svarianceyc/README.md index b10f32fc6bbb..7c217e50da0c 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/README.md +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/README.md @@ -98,7 +98,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var svarianceyc = require( '@stdlib/stats/base/svarianceyc' ); ``` -#### svarianceyc( N, correction, x, stride ) +#### svarianceyc( N, correction, x, strideX ) Computes the [variance][variance] of a single-precision floating-point strided array `x` using a one-pass algorithm proposed by Youngs and Cramer. @@ -106,9 +106,8 @@ Computes the [variance][variance] of a single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = svarianceyc( N, 1, x, 1 ); +var v = svarianceyc( x.length, 1, x, 1 ); // returns ~4.3333 ``` @@ -117,18 +116,16 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); -var N = floor( x.length / 2 ); -var v = svarianceyc( N, 1, x, 2 ); +var v = svarianceyc( 4, 1, x, 2 ); // returns 6.25 ``` @@ -138,18 +135,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [ ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = svarianceyc( N, 1, x1, 2 ); +var v = svarianceyc( 4, 1, x1, 2 ); // returns 6.25 ``` -#### svarianceyc.ndarray( N, correction, x, stride, offset ) +#### svarianceyc.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -157,26 +151,23 @@ Computes the [variance][variance] of a single-precision floating-point strided a var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -var N = x.length; -var v = svarianceyc.ndarray( N, 1, x, 1, 0 ); +var v = svarianceyc.ndarray( x.length, 1, x, 1, 0 ); // returns ~4.33333 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var N = floor( x.length / 2 ); -var v = svarianceyc.ndarray( N, 1, x, 2, 1 ); +var v = svarianceyc.ndarray( 4, 1, x, 2, 1 ); // returns 6.25 ``` @@ -202,18 +193,12 @@ var v = svarianceyc.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var svarianceyc = require( '@stdlib/stats/base/svarianceyc' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = svarianceyc( x.length, 1, x, 1 ); @@ -224,6 +209,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/svarianceyc.h" +``` + +#### stdlib_strided_svarianceyc( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_svarianceyc( 3, 1, x, 1 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than 0 has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where c corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to 0 is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to 1 is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **x**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `x`. + +```c +float stdlib_strided_svarianceyc( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_svarianceyc_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. + +```c +const float x[] = { 1.0f, -2.0f, 2.0f }; + +float v = stdlib_strided_srange_ndarray( 3, 1, x, 1, 0 ); +// returns ~4.33333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction** `[in] float`: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_svarianceyc_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/svarianceyc.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the variance: + float v = stdlib_strided_svarianceyc( N, 1.0f, x, strideX ); + + // Print the result: + printf( "sample variance: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.js index 4c4b88cace53..4f797d9a04b9 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var svarianceyc = require( './../lib/svarianceyc.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var svarianceyc = require( './../lib/svarianceyc.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10, 10, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.native.js index f73c73480731..ac3eed32893a 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var svarianceyc = tryRequire( resolve( __dirname, './../lib/svarianceyc.native.j var opts = { 'skip': ( svarianceyc instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10, 10, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.js index ec4a91a25751..62bae635a6fc 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.js @@ -21,14 +21,20 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var svarianceyc = require( './../lib/ndarray.js' ); +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + // FUNCTIONS // /** @@ -39,13 +45,7 @@ var svarianceyc = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10, 10, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.native.js index 8f9604ba6521..3dbafab017de 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,9 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -36,6 +35,9 @@ var svarianceyc = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) var opts = { 'skip': ( svarianceyc instanceof Error ) }; +var options = { + 'dtype': 'float32' +}; // FUNCTIONS // @@ -48,13 +50,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10, 10, options ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/c/benchmark.length.c index ec0cc594aaa0..58d05b4c6c9f 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; float v; @@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) { v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_svarianceyc( len, 1.0f, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_svarianceyc_ndarray( len, 1.0f, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +177,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/repl.txt index c690da3ac3f5..c8320f182444 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -31,8 +31,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -46,22 +46,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: + // Using `N` and stride parameters: > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, 1, x, stride ) + > {{alias}}( 3, 1, x, 2 ) ~4.3333 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, 1, x1, stride ) + > {{alias}}( 3, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -90,10 +87,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -110,10 +107,8 @@ // Using offset parameter: > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~4.3333 See Also -------- - diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/types/index.d.ts index eb640d094f58..bbc7845b6ac5 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/docs/types/index.d.ts @@ -28,7 +28,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = svarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float32Array, stride: number ): number; + ( N: number, correction: number, x: Float32Array, strideX: number ): number; /** * Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -47,8 +47,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = svarianceyc.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/c/example.c index 1d781c4c705b..487730dc1402 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/svarianceyc.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; // Specify the number of elements: - int64_t N = 4; + const int N = 4; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the variance: - float v = stdlib_strided_svarianceyc( N, 1.0f, x, stride ); + float v = stdlib_strided_svarianceyc( N, 1.0f, x, strideX ); // Print the result: printf( "sample variance: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/index.js index 25f0b017410f..8273e6e91f19 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/examples/index.js @@ -18,18 +18,12 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); var svarianceyc = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); -} +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float32' +}); console.log( x ); var v = svarianceyc( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/include/stdlib/stats/base/svarianceyc.h b/lib/node_modules/@stdlib/stats/base/svarianceyc/include/stdlib/stats/base/svarianceyc.h index 031d5f018000..ae23270a7b5c 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/include/stdlib/stats/base/svarianceyc.h +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/include/stdlib/stats/base/svarianceyc.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SVARIANCEYC_H #define STDLIB_STATS_BASE_SVARIANCEYC_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. */ -float stdlib_strided_svarianceyc( const int64_t N, const float correction, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_svarianceyc)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_svarianceyc_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/index.js index 0448f6def64f..5835bc2ddedd 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/index.js @@ -28,20 +28,17 @@ * var svarianceyc = require( '@stdlib/stats/base/svarianceyc' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svarianceyc( N, 1, x, 1 ); +* var v = svarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var svarianceyc = require( '@stdlib/stats/base/svarianceyc' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svarianceyc.ndarray( N, 1, x, 2, 1 ); +* var v = svarianceyc.ndarray( 4, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.js index f2ff0bf51164..27aa0836a8e7 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.js @@ -39,21 +39,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svarianceyc( N, 1, x, 2, 1 ); +* var v = svarianceyc( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function svarianceyc( N, correction, x, stride, offset ) { +function svarianceyc( N, correction, x, strideX, offsetX ) { var sum; var ix; var S; @@ -66,18 +64,18 @@ function svarianceyc( N, correction, x, stride, offset ) { if ( N <= 0 || n <= 0.0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { + if ( N === 1 || strideX === 0 ) { return 0.0; } - sum = x[ offset ]; - ix = offset + stride; + sum = x[ offsetX ]; + ix = offsetX + strideX; S = 0.0; for ( i = 2; i <= N; i++ ) { v = x[ ix ]; sum = float64ToFloat32( sum+v ); d = float64ToFloat32( float64ToFloat32( i*v ) - sum ); S = float64ToFloat32( S + float64ToFloat32( float64ToFloat32( float64ToFloat32( 1.0/(i*(i-1)) ) * d ) * d ) ); // eslint-disable-line max-len - ix += stride; + ix += strideX; } return float64ToFloat32( S/n ); } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.native.js index b2defbd30d7d..bfc7102da52c 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './svarianceyc.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './svarianceyc.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); -* var N = floor( x.length / 2 ); * -* var v = svarianceyc( N, 1, x, 2, 1 ); +* var v = svarianceyc( 4, 1, x, 2, 1 ); * // returns 6.25 */ -function svarianceyc( N, correction, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, correction, view, stride ); +function svarianceyc( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.js index 231ff2d6b467..2332c207a715 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.js @@ -20,7 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -39,50 +40,19 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svarianceyc( N, 1, x, 1 ); +* var v = svarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function svarianceyc( N, correction, x, stride ) { - var sum; - var ix; - var S; - var v; - var d; - var n; - var i; - - n = N - correction; - if ( N <= 0 || n <= 0.0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return 0.0; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = x[ ix ]; - ix += stride; - S = 0.0; - for ( i = 2; i <= N; i++ ) { - v = x[ ix ]; - sum = float64ToFloat32( sum+v ); - d = float64ToFloat32( float64ToFloat32( i*v ) - sum ); - S = float64ToFloat32( S + float64ToFloat32( float64ToFloat32( float64ToFloat32( 1.0/(i*(i-1)) ) * d ) * d ) ); // eslint-disable-line max-len - ix += stride; - } - return float64ToFloat32( S/n ); +function svarianceyc( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.native.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.native.js index 7be67f8937d1..fb01afc45cb0 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/lib/svarianceyc.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, 2.0 ] ); -* var N = x.length; * -* var v = svarianceyc( N, 1, x, 1 ); +* var v = svarianceyc( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function svarianceyc( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function svarianceyc( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/manifest.json b/lib/node_modules/@stdlib/stats/base/svarianceyc/manifest.json index 84a0318f76e3..47febd9f446e 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -26,19 +27,20 @@ ], "confs": [ { - "task": "build", + "task": "build", + "wasm": false, "src": [ - "./src/svarianceyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ "@stdlib/napi/export", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", "@stdlib/napi/argv-strided-float32array", @@ -48,22 +50,25 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/svarianceyc.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/svarianceyc.c" + "./src/main.c" ], "include": [ "./include" @@ -72,7 +77,26 @@ "-lm" ], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/src/addon.c b/lib/node_modules/@stdlib/stats/base/svarianceyc/src/addon.c index f6a7f461b80e..ec11ab8e854a 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/src/addon.c @@ -36,10 +36,28 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ) - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_svarianceyc( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_svarianceyc( N, correction, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_svarianceyc_ndarray( N, correction, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/src/main.c b/lib/node_modules/@stdlib/stats/base/svarianceyc/src/main.c new file mode 100644 index 000000000000..abb8ba71ad76 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/src/main.c @@ -0,0 +1,86 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/svarianceyc.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. +* +* ## Method +* +* - This implementation uses a one-pass algorithm, as proposed by Youngs and Cramer (1971). +* +* ## References +* +* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value +*/ +float API_SUFFIX(stdlib_strided_svarianceyc)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_svarianceyc_ndarray)( N, correction, X, strideX, ox ); +} + + +/** +* Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index of X +* @return output value +*/ +float API_SUFFIX(stdlib_strided_svarianceyc_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double di; + float sum; + double n; + float S; + float v; + float d; + + n = (double)N - (double)correction; + if ( N <= 0 || n <= 0.0f ) { + return 0.0f / 0.0f; // NaN + } + if ( N == 1 || strideX == 0 ) { + return 0.0f; + } + ix = offsetX; + sum = X[ ix ]; + ix += strideX; + S = 0.0f; + for ( i = 2; i <= N; i++ ) { + di = (double)i; + v = X[ ix ]; + sum += v; + d = (float)(di*(double)v) - sum; + S += (float)(1.0/(di*(di-1.0))) * d * d; + ix += strideX; + } + return (double)S / n; +} diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/src/svarianceyc.c b/lib/node_modules/@stdlib/stats/base/svarianceyc/src/svarianceyc.c deleted file mode 100644 index 0b74c6148e04..000000000000 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/src/svarianceyc.c +++ /dev/null @@ -1,73 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -#include "stdlib/stats/base/svarianceyc.h" -#include - -/** -* Computes the variance of a single-precision floating-point strided array using a one-pass algorithm proposed by Youngs and Cramer. -* -* ## Method -* -* - This implementation uses a one-pass algorithm, as proposed by Youngs and Cramer (1971). -* -* ## References -* -* - Youngs, Edward A., and Elliot M. Cramer. 1971. "Some Results Relevant to Choice of Sum and Sum-of-Product Algorithms." _Technometrics_ 13 (3): 657–65. doi:[10.1080/00401706.1971.10488826](https://doi.org/10.1080/00401706.1971.10488826). -* -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value -*/ -float stdlib_strided_svarianceyc( const int64_t N, const float correction, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - double di; - float sum; - double n; - float S; - float v; - float d; - - n = (double)N - (double)correction; - if ( N <= 0 || n <= 0.0f ) { - return 0.0f / 0.0f; // NaN - } - if ( N == 1 || stride == 0 ) { - return 0.0f; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - sum = X[ ix ]; - ix += stride; - S = 0.0f; - for ( i = 2; i <= N; i++ ) { - di = (double)i; - v = X[ ix ]; - sum += v; - d = (float)(di*(double)v) - sum; - S += (float)(1.0/(di*(di-1.0))) * d * d; - ix += stride; - } - return (double)S / n; -} diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.js index 4744735e1b4f..0ad58b76d89f 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, 2, 0 ); + v = svarianceyc( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, -2, 6 ); + v = svarianceyc( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -194,9 +188,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, 2, 1 ); + v = svarianceyc( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.native.js index 1209c9324116..5aa8b35322d9 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, 2, 0 ); + v = svarianceyc( 4, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, -2, 6 ); + v = svarianceyc( 4, 1, x, -2, 6 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -203,9 +197,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 3.0, 4.0 // 3 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, 2, 1 ); + v = svarianceyc( 4, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.js index 4f7b762d4610..b3958706e4b5 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -122,7 +121,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -137,15 +135,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, 2 ); + v = svarianceyc( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -160,8 +156,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, -2 ); + v = svarianceyc( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -182,7 +177,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -198,9 +192,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = svarianceyc( N, 1, x1, 2 ); + v = svarianceyc( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.native.js b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.native.js index 3fd5c7b2faa6..36114f5da184 100644 --- a/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.native.js +++ b/lib/node_modules/@stdlib/stats/base/svarianceyc/test/test.svarianceyc.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -131,7 +130,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -146,15 +144,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, 2 ); + v = svarianceyc( 4, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -169,8 +165,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - N = floor( x.length / 2 ); - v = svarianceyc( N, 1, x, -2 ); + v = svarianceyc( 4, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); @@ -191,7 +186,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -207,9 +201,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = svarianceyc( N, 1, x1, 2 ); + v = svarianceyc( 4, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/chi2test/test/test.js b/lib/node_modules/@stdlib/stats/chi2test/test/test.js index 81add87308b2..5f207deaabb5 100644 --- a/lib/node_modules/@stdlib/stats/chi2test/test/test.js +++ b/lib/node_modules/@stdlib/stats/chi2test/test/test.js @@ -74,7 +74,7 @@ tape( 'the function throws an error if the `x` argument is not a 2d array of arr } }); -tape( 'the function throws an error if `x` does not only contain non-negative numbers', function test( t ) { +tape( 'the function throws an error if `x` does not only contain nonnegative numbers', function test( t ) { var value = [ [ -2, 4 ], [ 1, 3 ] diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/README.md b/lib/node_modules/@stdlib/stats/strided/dcumax/README.md new file mode 100644 index 000000000000..924b3d275855 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/README.md @@ -0,0 +1,332 @@ + + +# dcumax + +> Calculate the cumulative maximum of double-precision floating-point strided array elements. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dcumax = require( '@stdlib/stats/strided/dcumax' ); +``` + +#### dcumax( N, x, strideX, y, strideY ) + +Computes the cumulative maximum of double-precision floating-point strided array elements. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var y = new Float64Array( x.length ); + +dcumax( x.length, x, 1, y, 1 ); +// y => [ 1.0, 1.0, 2.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **y**: output [`Float64Array`][@stdlib/array/float64]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative maximum of every other element in `x`, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var y = new Float64Array( x.length ); + +var v = dcumax( 4, x, 2, y, 1 ); +// y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( x0.length ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element + +dcumax( 4, x1, -2, y1, 1 ); +// y0 => [ 0.0, 0.0, 0.0, 4.0, 4.0, 4.0, 4.0, 0.0 ] +``` + +#### dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Computes the cumulative maximum of double-precision floating-point strided array elements using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var y = new Float64Array( x.length ); + +dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ 1.0, 1.0, 2.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative maximum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var y = new Float64Array( x.length ); + +dcumax.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); +// y => [ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0, 1.0, 1.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dcumax = require( '@stdlib/stats/strided/dcumax' ); + +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = new Float64Array( x.length ); +console.log( y ); + +dcumax( x.length, x, 1, y, -1 ); +console.log( y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/dcumax.h" +``` + +#### stdlib_strided_dcumax( N, \*X, strideX, \*Y, strideY ) + +Computes the cumulative maximum of double-precision floating-point strided array elements. + +```c +const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dcumax( 4, x, 2, y, -2 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_dcumax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_dcumax_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + +Computes the cumulative maximum of double-precision floating-point strided array elements using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dcumax_ndarray( 4, x, 2, 0, y, -2, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_dcumax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/dcumax.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; + double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative maximum: + stdlib_strided_dcumax( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %lf\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +* * * + +## See Also + +- [`@stdlib/stats/base/cumax`][@stdlib/stats/base/cumax]: calculate the cumulative maximum of a strided array. +- [`@stdlib/stats/base/dcumin`][@stdlib/stats/base/dcumin]: calculate the cumulative minimum of double-precision floating-point strided array elements. +- [`@stdlib/stats/base/scumax`][@stdlib/stats/base/scumax]: calculate the cumulative maximum of single-precision floating-point strided array elements. + +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + +[@stdlib/stats/base/cumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumax + +[@stdlib/stats/base/dcumin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcumin + +[@stdlib/stats/base/scumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumax + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/benchmark/benchmark.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/benchmark.ndarray.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/benchmark/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..3ce2730bdacd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/benchmark/c/benchmark.length.c @@ -0,0 +1,197 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumax.h" +#include +#include +#include +#include +#include + +#define NAME "dcumax" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double x[ len ]; + double y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + y[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dcumax( len, x, 1, y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + y[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dcumax_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dcumax/binding.gyp similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/binding.gyp rename to lib/node_modules/@stdlib/stats/strided/dcumax/binding.gyp diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dcumax/docs/repl.txt new file mode 100644 index 000000000000..7696995cbac8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/docs/repl.txt @@ -0,0 +1,113 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Computes the cumulative maximum of double-precision floating-point strided + array elements. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Float64Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + out: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ 1.0, 1.0, 2.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}( 3, x, 2, y, 2 ) + [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); + > {{alias}}( 3, x1, 2, y1, 1 ) + [ -2.0, 2.0, 2.0 ] + > y0 + [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Computes the cumulative maximum of double-precision floating-point strided + array elements using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the `offset` parameter supports indexing semantics based on a + starting index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float64Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + out: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ 1.0, 1.0, 2.0 ] + + // Advanced indexing: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) + [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dcumax/docs/types/index.d.ts similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/docs/types/index.d.ts rename to lib/node_modules/@stdlib/stats/strided/dcumax/docs/types/index.d.ts diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dcumax/docs/types/test.ts similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/docs/types/test.ts rename to lib/node_modules/@stdlib/stats/strided/dcumax/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dcumax/examples/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/examples/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dcumax/examples/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dcumax/examples/c/example.c new file mode 100644 index 000000000000..b635ba917444 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumax.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; + double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative maximum: + stdlib_strided_dcumax( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %lf\n", i, y[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dcumax/examples/index.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/examples/index.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/examples/index.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/include.gypi b/lib/node_modules/@stdlib/stats/strided/dcumax/include.gypi similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/include.gypi rename to lib/node_modules/@stdlib/stats/strided/dcumax/include.gypi diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/include/stdlib/stats/base/dcumax.h b/lib/node_modules/@stdlib/stats/strided/dcumax/include/stdlib/stats/strided/dcumax.h similarity index 92% rename from lib/node_modules/@stdlib/stats/base/dcumax/include/stdlib/stats/base/dcumax.h rename to lib/node_modules/@stdlib/stats/strided/dcumax/include/stdlib/stats/strided/dcumax.h index 8bb5629a81a3..e594f9709817 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumax/include/stdlib/stats/base/dcumax.h +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/include/stdlib/stats/strided/dcumax.h @@ -16,8 +16,8 @@ * limitations under the License. */ -#ifndef STDLIB_STATS_BASE_DCUMAX_H -#define STDLIB_STATS_BASE_DCUMAX_H +#ifndef STDLIB_STATS_STRIDED_DCUMAX_H +#define STDLIB_STATS_STRIDED_DCUMAX_H #include "stdlib/blas/base/shared.h" @@ -42,4 +42,4 @@ void API_SUFFIX(stdlib_strided_dcumax_ndarray)( const CBLAS_INT N, const double } #endif -#endif // !STDLIB_STATS_BASE_DCUMAX_H +#endif // !STDLIB_STATS_STRIDED_DCUMAX_H diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/dcumax.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/dcumax.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/lib/dcumax.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/lib/dcumax.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/dcumax.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/dcumax.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/lib/dcumax.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/lib/dcumax.native.js diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/lib/index.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/index.js new file mode 100644 index 000000000000..ed50b41f6b08 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the cumulative maximum of double-precision floating-point strided array elements. +* +* @module @stdlib/stats/strided/dcumax +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dcumax = require( '@stdlib/stats/strided/dcumax' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float64Array( x.length ); +* +* dcumax( x.length, x, 1, y, 1 ); +* // y => [ 1.0, 1.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dcumax = require( '@stdlib/stats/strided/dcumax' ); +* +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float64Array( x.length ); +* +* dcumax.ndarray( 4, x, 2, 1, y, 1, 0 ); +* // y => [ 1.0, 1.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dcumax; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dcumax = main; +} else { + dcumax = tmp; +} + + +// EXPORTS // + +module.exports = dcumax; + +// exports: { "ndarray": "dcumax.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/main.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/main.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/lib/main.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/lib/main.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/lib/native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/lib/native.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/ndarray.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/lib/ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/lib/ndarray.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/lib/ndarray.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/lib/ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/lib/ndarray.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/manifest.json b/lib/node_modules/@stdlib/stats/strided/dcumax/manifest.json similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/manifest.json rename to lib/node_modules/@stdlib/stats/strided/dcumax/manifest.json diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/package.json b/lib/node_modules/@stdlib/stats/strided/dcumax/package.json new file mode 100644 index 000000000000..67b6360c165b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/package.json @@ -0,0 +1,79 @@ +{ + "name": "@stdlib/stats/strided/dcumax", + "version": "0.0.0", + "description": "Calculate the cumulative maximum of double-precision floating-point strided array elements.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "range", + "extremes", + "domain", + "extent", + "accumulate", + "cumulative", + "strided", + "strided array", + "typed", + "array", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dcumax/src/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/src/Makefile rename to lib/node_modules/@stdlib/stats/strided/dcumax/src/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dcumax/src/addon.c new file mode 100644 index 000000000000..4b446caf5b3f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumax.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_dcumax)( N, X, strideX, Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_dcumax_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/strided/dcumax/src/main.c b/lib/node_modules/@stdlib/stats/strided/dcumax/src/main.c new file mode 100644 index 000000000000..88d5d3b54ece --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumax/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_positive_zero.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative maximum of double-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void API_SUFFIX(stdlib_strided_dcumax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_dcumax_ndarray)( N, X, strideX, ox, Y, strideY, oy ); + return; +} + +/** +* Computes the cumulative maximum of double-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Y output array +* @param strideY Y stride length +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_dcumax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + double max; + double v; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + max = X[ ix ]; + Y[ iy ] = max; + + iy += strideY; + i = 1; + if ( !stdlib_base_is_nan( max ) ) { + for (; i < N; i++ ) { + ix += strideX; + v = X[ ix ]; + if ( stdlib_base_is_nan( v ) ) { + max = v; + break; + } + if ( v > max || ( v == max && stdlib_base_is_positive_zero( v ) ) ) { + max = v; + } + Y[ iy ] = max; + iy += strideY; + } + } + if ( stdlib_base_is_nan( max ) ) { + for (; i < N; i++ ) { + Y[ iy ] = max; + iy += strideY; + } + } + return; +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/test/test.dcumax.js b/lib/node_modules/@stdlib/stats/strided/dcumax/test/test.dcumax.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/test/test.dcumax.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/test/test.dcumax.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/test/test.dcumax.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/test/test.dcumax.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/test/test.dcumax.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/test/test.dcumax.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/test/test.js b/lib/node_modules/@stdlib/stats/strided/dcumax/test/test.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/test/test.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumax/test/test.ndarray.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/test/test.ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/test/test.ndarray.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumax/test/test.ndarray.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumax/test/test.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumax/test/test.ndarray.native.js diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/README.md b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/README.md new file mode 100644 index 000000000000..8050b03c49e1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/README.md @@ -0,0 +1,337 @@ + + + + +# dcumaxabs + +> Calculate the cumulative maximum absolute value of double-precision floating-point strided array elements. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dcumaxabs = require( '@stdlib/stats/strided/dcumaxabs' ); +``` + +#### dcumaxabs( N, x, strideX, y, strideY ) + +Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var y = new Float64Array( x.length ); + +dcumaxabs( x.length, x, 1, y, 1 ); +// y => [ 1.0, 2.0, 2.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **y**: output [`Float64Array`][@stdlib/array/float64]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in `x`, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); +var y = new Float64Array( x.length ); + +var v = dcumaxabs( 4, x, 2, y, 1 ); +// y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( x0.length ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element + +dcumaxabs( 4, x1, -2, y1, 1 ); +// y0 => [ 0.0, 0.0, 0.0, 4.0, 4.0, 4.0, 4.0, 0.0 ] +``` + +#### dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var y = new Float64Array( x.length ); + +dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ 1.0, 2.0, 2.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the cumulative maximum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var y = new Float64Array( x.length ); + +dcumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 ); +// y => [ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dcumaxabs = require( '@stdlib/stats/strided/dcumaxabs' ); + +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = new Float64Array( x.length ); +console.log( y ); + +dcumaxabs( x.length, x, 1, y, -1 ); +console.log( y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/dcumaxabs.h" +``` + +#### stdlib_strided_dcumaxabs( N, \*X, strideX, \*Y, strideY ) + +Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. + +```c +const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dcumaxabs( 4, x, 2, y, -2 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[out] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_dcumaxabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); +``` + +#### stdlib_strided_dcumaxabs_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + +Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; +double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dcumaxabs_ndarray( 4, x, 2, 0, y, -2, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[out] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_dcumaxabs_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/dcumaxabs.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; + double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative maximum absolute value: + stdlib_strided_dcumaxabs( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %lf\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +* * * + +## See Also + +- [`@stdlib/stats/base/cumaxabs`][@stdlib/stats/base/cumaxabs]: calculate the cumulative maximum absolute value of a strided array. +- [`@stdlib/stats/strided/dcumax`][@stdlib/stats/strided/dcumax]: calculate the cumulative maximum of double-precision floating-point strided array elements. +- [`@stdlib/stats/base/dcuminabs`][@stdlib/stats/base/dcuminabs]: calculate the cumulative minimum absolute value of double-precision floating-point strided array elements. +- [`@stdlib/stats/base/scumaxabs`][@stdlib/stats/base/scumaxabs]: calculate the cumulative maximum absolute value of single-precision floating-point strided array elements. + +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + +[@stdlib/stats/base/cumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/cumaxabs + +[@stdlib/stats/strided/dcumax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dcumax + +[@stdlib/stats/base/dcuminabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dcuminabs + +[@stdlib/stats/base/scumaxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/scumaxabs + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js new file mode 100644 index 000000000000..de4111f74aa8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var pkg = require( './../package.json' ).name; +var dcumaxabs = require( './../lib/dcumaxabs.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); + return benchmark; + + function benchmark( b ) { + var v; + var i; + + for ( i = 0; i < len; i++ ) { + y[ i ] = 0.0; + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dcumaxabs( x.length, x, 1, y, 1 ); + if ( isnan( v[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js new file mode 100644 index 000000000000..7c534ac99c4d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.native.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dcumaxabs = tryRequire( resolve( __dirname, './../lib/dcumaxabs.native.js' ) ); +var opts = { + 'skip': ( dcumaxabs instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); + return benchmark; + + function benchmark( b ) { + var v; + var i; + + for ( i = 0; i < len; i++ ) { + y[ i ] = 0.0; + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dcumaxabs( x.length, x, 1, y, 1 ); + if ( isnan( v[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+'::native:len='+len, opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..68e51184c963 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var pkg = require( './../package.json' ).name; +var dcumaxabs = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); + return benchmark; + + function benchmark( b ) { + var v; + var i; + + for ( i = 0; i < len; i++ ) { + y[ i ] = 0.0; + } + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( v[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i%len ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( pkg+':ndarray:len='+len, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js similarity index 90% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js index ce5d0c2b83d3..6941181db116 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/benchmark.ndarray.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/array/uniform' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -36,6 +36,9 @@ var dcumaxabs = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ) var opts = { 'skip': ( dcumaxabs instanceof Error ) }; +var options = { + 'dtype': 'float64' +}; // FUNCTIONS // @@ -48,15 +51,8 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var y; - var i; - - x = new Float64Array( len ); - y = new Float64Array( len ); - for ( i = 0; i < x.length; i++ ) { - x[ i ] = ( randu()*20.0 ) - 10.0; - } + var x = uniform( len, -10.0, 10.0, options ); + var y = new Float64Array( len ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..7abccc81a5a4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/benchmark/c/benchmark.length.c @@ -0,0 +1,197 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumaxabs.h" +#include +#include +#include +#include +#include + +#define NAME "dcumaxabs" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double x[ len ]; + double y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + y[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dcumaxabs( len, x, 1, y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double y[ len ]; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + y[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dcumaxabs_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ len-1 ] != y[ len-1 ] ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/binding.gyp similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/binding.gyp rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/binding.gyp diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/repl.txt new file mode 100644 index 000000000000..593b624fef87 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/repl.txt @@ -0,0 +1,113 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Computes the cumulative maximum absolute value of double-precision floating- + point strided array elements. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Float64Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + out: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ 1.0, 2.0, 2.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}( 3, x, 2, y, 2 ) + [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( x0.length ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); + > {{alias}}( 3, x1, 2, y1, 1 ) + [ 2.0, 2.0, 2.0 ] + > y0 + [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Computes the cumulative maximum absolute value of double-precision floating- + point strided array elements using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the `offset` parameter supports indexing semantics based on a + starting index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float64Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + out: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ 1.0, 2.0, 2.0 ] + + // Advanced indexing: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( x.length ); + > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 ) + [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/types/index.d.ts similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/types/index.d.ts rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/types/index.d.ts diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/types/test.ts similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/types/test.ts rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/c/example.c new file mode 100644 index 000000000000..5fc6b375eeca --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumaxabs.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 }; + double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of elements: + const int N = 4; + + // Specify stride lengths: + const int strideX = 2; + const int strideY = -2; + + // Compute the cumulative maximum absolute value: + stdlib_strided_dcumaxabs( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %d ] = %lf\n", i, y[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/index.js new file mode 100644 index 000000000000..112096e25a9e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dcumaxabs = require( './../lib' ); + +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = new Float64Array( x.length ); +console.log( y ); + +dcumaxabs( x.length, x, 1, y, -1 ); +console.log( y ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/include.gypi b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/include.gypi similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/include.gypi rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/include.gypi diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/include/stdlib/stats/strided/dcumaxabs.h b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/include/stdlib/stats/strided/dcumaxabs.h new file mode 100644 index 000000000000..41ae5fa34d7b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/include/stdlib/stats/strided/dcumaxabs.h @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_STATS_STRIDED_DCUMAXABS_H +#define STDLIB_STATS_STRIDED_DCUMAXABS_H + +#include "stdlib/blas/base/shared.h" + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. +*/ +void API_SUFFIX(stdlib_strided_dcumaxabs)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics. +*/ +void API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_STATS_STRIDED_DCUMAXABS_H diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/dcumaxabs.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/dcumaxabs.js new file mode 100644 index 000000000000..01fc61f72912 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/dcumaxabs.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float64Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float64Array( x.length ); +* var N = x.length; +* +* var v = dcumaxabs( N, x, 1, y, 1 ); +* // returns [ 1.0, 2.0, 2.0 ] +*/ +function dcumaxabs( N, x, strideX, y, strideY ) { + var ox = stride2offset( N, strideX ); + var oy = stride2offset( N, strideY ); + return ndarray( N, x, strideX, ox, y, strideY, oy ); +} + + +// EXPORTS // + +module.exports = dcumaxabs; diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/dcumaxabs.native.js similarity index 96% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/dcumaxabs.native.js index d5b5bd45a3b4..6948472d98a5 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/dcumaxabs.native.js @@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' ); * * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); * var y = new Float64Array( x.length ); -* var N = x.length; * -* var v = dcumaxabs( N, x, 1, y, 1 ); +* var v = dcumaxabs( x.length, x, 1, y, 1 ); * // returns [ 1.0, 2.0, 2.0 ] */ function dcumaxabs( N, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/index.js new file mode 100644 index 000000000000..a24a64bf6057 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the cumulative maximum absolute value of double-precision floating-point strided array elements. +* +* @module @stdlib/stats/strided/dcumaxabs +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dcumaxabs = require( '@stdlib/stats/strided/dcumaxabs' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float64Array( x.length ); +* +* dcumaxabs( x.length, x, 1, y, 1 ); +* // y => [ 1.0, 2.0, 2.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dcumaxabs = require( '@stdlib/stats/strided/dcumaxabs' ); +* +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float64Array( x.length ); +* +* dcumaxabs.ndarray( 4, x, 2, 1, y, 1, 0 ); +* // y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dcumaxabs; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dcumaxabs = main; +} else { + dcumaxabs = tmp; +} + + +// EXPORTS // + +module.exports = dcumaxabs; + +// exports: { "ndarray": "dcumaxabs.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/main.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/main.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/main.js diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/native.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/native.js diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/ndarray.js new file mode 100644 index 000000000000..3aa253e7995b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/ndarray.js @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); + + +// MAIN // + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Float64Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float64Array( x.length ); +* +* var v = dcumaxabs( 4, x, 2, 1, y, 1, 0 ); +* // returns [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] +*/ +function dcumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { + var max; + var ix; + var iy; + var v; + var i; + + if ( N <= 0 ) { + return y; + } + ix = offsetX; + iy = offsetY; + + max = abs( x[ ix ] ); + y[ iy ] = max; + + iy += strideY; + i = 1; + if ( isnan( max ) === false ) { + for ( i; i < N; i++ ) { + ix += strideX; + v = abs( x[ ix ] ); + if ( isnan( v ) ) { + max = v; + break; + } + if ( v > max ) { + max = v; + } + y[ iy ] = max; + iy += strideY; + } + } + if ( isnan( max ) ) { + for ( i; i < N; i++ ) { + y[ iy ] = max; + iy += strideY; + } + } + return y; +} + + +// EXPORTS // + +module.exports = dcumaxabs; diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/ndarray.native.js new file mode 100644 index 000000000000..960146df5f94 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/lib/ndarray.native.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Float64Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float64Array( x.length ); +* +* var v = dcumaxabs( 4, x, 2, 1, y, 1, 0 ); +* // returns [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] +*/ +function dcumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) { + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); + return y; +} + + +// EXPORTS // + +module.exports = dcumaxabs; diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/manifest.json b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/manifest.json new file mode 100644 index 000000000000..39b3db80d9d8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/manifest.json @@ -0,0 +1,106 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/blas/base/shared", + "@stdlib/math/base/special/abs", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/abs" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/package.json b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/package.json new file mode 100644 index 000000000000..8a39b9f50b73 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/package.json @@ -0,0 +1,82 @@ +{ + "name": "@stdlib/stats/strided/dcumaxabs", + "version": "0.0.0", + "description": "Calculate the cumulative maximum absolute value of double-precision floating-point strided array elements.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "abs", + "absolute", + "absolute value", + "range", + "extremes", + "domain", + "extent", + "accumulate", + "cumulative", + "strided", + "strided array", + "typed", + "array", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/src/Makefile rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/addon.c new file mode 100644 index 000000000000..438fc8cd5699 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumaxabs.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_dcumaxabs)( N, X, strideX, Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/main.c b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/main.c new file mode 100644 index 000000000000..3a9247e24d83 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/src/main.c @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dcumaxabs.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/abs.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param Y output array +* @param strideY Y stride length +*/ +void API_SUFFIX(stdlib_strided_dcumaxabs)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( N, X, strideX, ox, Y, strideY, oy ); + return; +} + +/** +* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX X stride length +* @param offsetX starting index for X +* @param Y output array +* @param strideY Y stride length +* @param offsetY starting index for Y +*/ +void API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + double max; + double v; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + max = stdlib_base_abs( X[ ix ] ); + Y[ iy ] = max; + + iy += strideY; + i = 1; + if ( !stdlib_base_is_nan( max ) ) { + for (; i < N; i++ ) { + ix += strideX; + v = stdlib_base_abs( X[ ix ] ); + if ( stdlib_base_is_nan( v ) ) { + max = v; + break; + } + if ( v > max ) { + max = v; + } + Y[ iy ] = max; + iy += strideY; + } + } + if ( stdlib_base_is_nan( max ) ) { + for (; i < N; i++ ) { + Y[ iy ] = max; + iy += strideY; + } + } + return; +} diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.dcumaxabs.js similarity index 95% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.dcumaxabs.js index a34eec63dc72..dfcf306b1349 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.dcumaxabs.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, 2, y, 1 ); + dcumaxabs( 3, x, 2, y, 1 ); expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumaxabs( N, x, 1, y, 2 ); + dcumaxabs( 3, x, 1, y, 2 ); expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, -2, y, -1 ); + dcumaxabs( 3, x, -2, y, -1 ); expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, 2, y, -1 ); + dcumaxabs( 3, x, 2, y, -1 ); expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float64Array([ @@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - dcumaxabs( N, x1, -2, y1, 1 ); + dcumaxabs( 3, x1, -2, y1, 1 ); expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 6.0, 6.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.dcumaxabs.native.js similarity index 95% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.dcumaxabs.native.js index b51b3dcbc763..89eddb305f9d 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.dcumaxabs.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, 2, y, 1 ); + dcumaxabs( 3, x, 2, y, 1 ); expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumaxabs( N, x, 1, y, 2 ); + dcumaxabs( 3, x, 1, y, 2 ); expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, -2, y, -1 ); + dcumaxabs( 3, x, -2, y, -1 ); expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t ) var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t ) 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, 2, y, -1 ); + dcumaxabs( 3, x, 2, y, -1 ); expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) { var y0; var x1; var y1; - var N; // Initial arrays... x0 = new Float64Array([ @@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element - N = floor( x0.length / 2 ); - - dcumaxabs( N, x1, -2, y1, 1 ); + dcumaxabs( 3, x1, -2, y1, 1 ); expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 6.0, 6.0 ] ); t.deepEqual( y0, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.js diff --git a/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.ndarray.js new file mode 100644 index 000000000000..9ad6bb70ddca --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.ndarray.js @@ -0,0 +1,328 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dcumaxabs = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dcumaxabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( dcumaxabs.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the cumulative maximum absolute value', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] ); + y = new Float64Array( x.length ); + dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + + expected = new Float64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0 + ]); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( [ -0.0, 0.0, -0.0 ] ); + y = new Float64Array( x.length ); + dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + + expected = new Float64Array([ + 0.0, + 0.0, + 0.0 + ]); + for ( i = 0; i < y.length; i++ ) { + if ( isPositiveZero( expected[ i ] ) ) { + t.strictEqual( isPositiveZero( y[ i ] ), true, 'returns expected value. i: ' + i ); + } else { + t.strictEqual( y[ i ], expected[ i ], true, 'returns expected value. i: ' + i ); + } + } + + x = new Float64Array( [ NaN ] ); + y = new Float64Array( x.length ); + dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + + for ( i = 0; i < y.length; i++ ) { + t.strictEqual( isnan( y[ i ] ), true, 'returns expected value. i: ' + i ); + } + + x = new Float64Array( [ NaN, NaN ] ); + y = new Float64Array( x.length ); + dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + + for ( i = 0; i < y.length; i++ ) { + t.strictEqual( isnan( y[ i ] ), true, 'returns expected value. i: ' + i ); + } + + x = new Float64Array( [ 1.0, NaN, 3.0, NaN ] ); + y = new Float64Array( x.length ); + dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + + expected = new Float64Array([ + 1.0, + NaN, + NaN, + NaN + ]); + for ( i = 0; i < y.length; i++ ) { + if ( isnan( expected[ i ] ) ) { + t.strictEqual( isnan( y[ i ] ), true, 'returns expected value. i: ' + i ); + } else { + t.strictEqual( y[ i ], expected[ i ], true, 'returns expected value. i: ' + i ); + } + } + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + out = dcumaxabs( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( out, y, 'same reference' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); + + dcumaxabs( -1, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); + + dcumaxabs( 0, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns `y` unchanged' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + -2.0, + 3.0, // 1 + 4.0, + -5.0 // 2 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + dcumaxabs( 3, x, 2, 0, y, 1, 0 ); + + expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + -2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0 // 2 + ]); + + dcumaxabs( 3, x, 1, 0, y, 2, 0 ); + + expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + -2.0, + 3.0, // 1 + 4.0, + -5.0 // 0 + ]); + y = new Float64Array([ + 0.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + dcumaxabs( 3, x, -2, x.length-1, y, -1, 2 ); + + expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, // 1 + 0.0, // 2 + 0.0, // 3 + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + dcumaxabs( 4, x, 2, 1, y, 1, 0 ); + + expected = new Float64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + 1.0, // 1 + 2.0, // 2 + -2.0, // 3 + -2.0, + 2.0, + 3.0, + 4.0 + ]); + y = new Float64Array([ + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0 // 3 + ]); + + dcumaxabs( 4, x, 1, 0, y, 2, 1 ); + + expected = new Float64Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 0.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + dcumaxabs( 3, x, 2, 0, y, -1, 2 ); + + expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.ndarray.native.js similarity index 94% rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.ndarray.native.js index 0d41b8102f5c..bed988d18cc8 100644 --- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dcumaxabs/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, 2, 0, y, 1, 0 ); + dcumaxabs( 3, x, 2, 0, y, 1, 0 ); expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 0 @@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) { 0.0, 0.0 // 2 ]); - N = 3; - dcumaxabs( N, x, 1, 0, y, 2, 0 ); + dcumaxabs( 3, x, 1, 0, y, 2, 0 ); expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { var expected; var x; var y; - var N; x = new Float64Array([ 1.0, // 2 @@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) { 0.0, 0.0 ]); - N = 3; - dcumaxabs( N, x, -2, x.length-1, y, -1, 2 ); + dcumaxabs( 3, x, -2, x.length-1, y, -1, 2 ); expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) { tape( 'the function supports an `x` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { 0.0, 0.0 ]); - N = floor( x.length / 2 ); - dcumaxabs( N, x, 2, 1, y, 1, 0 ); + dcumaxabs( 4, x, 2, 1, y, 1, 0 ); expected = new Float64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); @@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) { tape( 'the function supports a `y` offset', opts, function test( t ) { var expected; - var N; var x; var y; @@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) { 0.0, 0.0 // 3 ]); - N = floor( x.length / 2 ); - dcumaxabs( N, x, 1, 0, y, 2, 1 ); + dcumaxabs( 4, x, 1, 0, y, 2, 1 ); expected = new Float64Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] ); t.deepEqual( y, expected, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/README.md b/lib/node_modules/@stdlib/stats/strided/dmax/README.md new file mode 100644 index 000000000000..138f416c56cf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/README.md @@ -0,0 +1,305 @@ + + +# dmax + +> Calculate the maximum value of a double-precision floating-point strided array. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dmax = require( '@stdlib/stats/strided/dmax' ); +``` + +#### dmax( N, x, strideX ) + +Computes the maximum value of a double-precision floating-point strided array `x`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); + +var v = dmax( x.length, x, 1 ); +// returns 2.0 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum value of every other element in `x`, + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] ); + +var v = dmax( 4, x, 2 ); +// returns 4.0 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var v = dmax( 4, x1, 2 ); +// returns 4.0 +``` + +#### dmax.ndarray( N, x, strideX, offsetX ) + +Computes the maximum value of a double-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +var N = x.length; + +var v = dmax.ndarray( N, x, 1, 0 ); +// returns 2.0 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); + +var v = dmax.ndarray( 4, x, 2, 1 ); +// returns 4.0 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `NaN`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dmax = require( '@stdlib/stats/strided/dmax' ); + +var x = discreteUniform( 10, -50, 50, { + 'dtype': 'float64' +}); +console.log( x ); + +var v = dmax( x.length, x, 1 ); +console.log( v ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/strided/dmax.h" +``` + +#### stdlib_strided_dmax( N, \*X, strideX ) + +Computes the maximum value of a double-precision floating-point strided array. + +```c +const double x[] = { 1.0, -2.0, 3.0, -4.0 }; + +double v = stdlib_strided_dmax( 4, x, 1 ); +// returns 3.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dmax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dmax_ndarray( N, \*X, strideX, offsetX ) + +Computes the maximum value of a double-precision floating-point strided array using alternative indexing semantics. + +```c +const double x[] = { 1.0, -2.0, 3.0, -4.0 }; + +double v = stdlib_strided_dmax_ndarray( 4, x, 1, 0 ); +// returns 3.0 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dmax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/strided/dmax.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Compute the maximum value: + double v = stdlib_strided_dmax( N, x, strideX ); + + // Print the result: + printf( "max: %lf\n", v ); +} +``` + +
+ + + +
+ + + + + +
+ +* * * + +## See Also + +- [`@stdlib/stats/base/dmin`][@stdlib/stats/base/dmin]: calculate the minimum value of a double-precision floating-point strided array. +- [`@stdlib/stats/base/dnanmax`][@stdlib/stats/base/dnanmax]: calculate the maximum value of a double-precision floating-point strided array, ignoring NaN values. +- [`@stdlib/stats/base/max`][@stdlib/stats/base/max]: calculate the maximum value of a strided array. +- [`@stdlib/stats/base/smax`][@stdlib/stats/base/smax]: calculate the maximum value of a single-precision floating-point strided array. + +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + +[@stdlib/stats/base/dmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dmin + +[@stdlib/stats/base/dnanmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanmax + +[@stdlib/stats/base/max]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/max + +[@stdlib/stats/base/smax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/smax + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.js rename to lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/benchmark/benchmark.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/benchmark/benchmark.ndarray.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/benchmark/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dmax/benchmark/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..04e022e2eaf8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/benchmark/c/benchmark.length.c @@ -0,0 +1,197 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dmax.h" +#include +#include +#include +#include +#include + +#define NAME "dmax" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmax( len, x, 1 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double() * 20000.0 ) - 10000.0; + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dmax_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dmax/binding.gyp similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/binding.gyp rename to lib/node_modules/@stdlib/stats/strided/dmax/binding.gyp diff --git a/lib/node_modules/@stdlib/stats/base/dmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dmax/docs/repl.txt similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/docs/repl.txt rename to lib/node_modules/@stdlib/stats/strided/dmax/docs/repl.txt diff --git a/lib/node_modules/@stdlib/stats/base/dmax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dmax/docs/types/index.d.ts similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/docs/types/index.d.ts rename to lib/node_modules/@stdlib/stats/strided/dmax/docs/types/index.d.ts diff --git a/lib/node_modules/@stdlib/stats/base/dmax/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dmax/docs/types/test.ts similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/docs/types/test.ts rename to lib/node_modules/@stdlib/stats/strided/dmax/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/stats/base/dmax/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dmax/examples/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/examples/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dmax/examples/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dmax/examples/c/example.c new file mode 100644 index 000000000000..a748afd1ca18 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/examples/c/example.c @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dmax.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify the stride length: + const int strideX = 2; + + // Compute the maximum value: + double v = stdlib_strided_dmax( N, x, strideX ); + + // Print the result: + printf( "max: %lf\n", v ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dmax/examples/index.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/examples/index.js rename to lib/node_modules/@stdlib/stats/strided/dmax/examples/index.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/include.gypi b/lib/node_modules/@stdlib/stats/strided/dmax/include.gypi similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/include.gypi rename to lib/node_modules/@stdlib/stats/strided/dmax/include.gypi diff --git a/lib/node_modules/@stdlib/stats/base/dmax/include/stdlib/stats/base/dmax.h b/lib/node_modules/@stdlib/stats/strided/dmax/include/stdlib/stats/strided/dmax.h similarity index 92% rename from lib/node_modules/@stdlib/stats/base/dmax/include/stdlib/stats/base/dmax.h rename to lib/node_modules/@stdlib/stats/strided/dmax/include/stdlib/stats/strided/dmax.h index 05729bfdb17a..4f1f65e047fd 100644 --- a/lib/node_modules/@stdlib/stats/base/dmax/include/stdlib/stats/base/dmax.h +++ b/lib/node_modules/@stdlib/stats/strided/dmax/include/stdlib/stats/strided/dmax.h @@ -16,8 +16,8 @@ * limitations under the License. */ -#ifndef STDLIB_STATS_BASE_DMAX_H -#define STDLIB_STATS_BASE_DMAX_H +#ifndef STDLIB_STATS_STRIDED_DMAX_H +#define STDLIB_STATS_STRIDED_DMAX_H #include "stdlib/blas/base/shared.h" @@ -42,4 +42,4 @@ double API_SUFFIX(stdlib_strided_dmax_ndarray)( const CBLAS_INT N, const double } #endif -#endif // !STDLIB_STATS_BASE_DMAX_H +#endif // !STDLIB_STATS_STRIDED_DMAX_H diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/dmax.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/dmax.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/lib/dmax.js rename to lib/node_modules/@stdlib/stats/strided/dmax/lib/dmax.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/dmax.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/dmax.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/lib/dmax.native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/lib/dmax.native.js diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/lib/index.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/index.js new file mode 100644 index 000000000000..b1050281cd69 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/lib/index.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the maximum value of a double-precision floating-point strided array. +* +* @module @stdlib/stats/strided/dmax +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dmax = require( '@stdlib/stats/strided/dmax' ); +* +* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] ); +* +* var v = dmax( x.length, x, 1 ); +* // returns 2.0 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dmax = require( '@stdlib/stats/strided/dmax' ); +* +* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); +* +* var v = dmax.ndarray( 4, x, 2, 1 ); +* // returns 4.0 +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dmax; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dmax = main; +} else { + dmax = tmp; +} + + +// EXPORTS // + +module.exports = dmax; + +// exports: { "ndarray": "dmax.ndarray" } diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/main.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/main.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/lib/main.js rename to lib/node_modules/@stdlib/stats/strided/dmax/lib/main.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/native.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/lib/native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/lib/native.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/ndarray.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/lib/ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dmax/lib/ndarray.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/lib/ndarray.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/lib/ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/lib/ndarray.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/manifest.json b/lib/node_modules/@stdlib/stats/strided/dmax/manifest.json similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/manifest.json rename to lib/node_modules/@stdlib/stats/strided/dmax/manifest.json diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/package.json b/lib/node_modules/@stdlib/stats/strided/dmax/package.json new file mode 100644 index 000000000000..d97dd43a4b61 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/stats/strided/dmax", + "version": "0.0.0", + "description": "Calculate the maximum value of a double-precision floating-point strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "range", + "extremes", + "domain", + "extent", + "strided", + "strided array", + "typed", + "array", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dmax/src/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/src/Makefile rename to lib/node_modules/@stdlib/stats/strided/dmax/src/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dmax/src/addon.c new file mode 100644 index 000000000000..c47b1ff69fce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2024 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dmax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_double.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmax)( N, X, strideX ), v ); + return v; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmax_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/strided/dmax/src/main.c b/lib/node_modules/@stdlib/stats/strided/dmax/src/main.c new file mode 100644 index 000000000000..9f266a71ac04 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmax/src/main.c @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/strided/dmax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/assert/is_positive_zero.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Computes the maximum value of a double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dmax_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the maximum value of a double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dmax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + double max; + double v; + + if ( N <= 0 ) { + return 0.0 / 0.0; // NaN + } + if ( N == 1 || strideX == 0 ) { + return X[ 0 ]; + } + ix = offsetX; + max = X[ ix ]; + for ( i = 1; i < N; i++ ) { + ix += strideX; + v = X[ ix ]; + if ( stdlib_base_is_nan( v ) ) { + return v; + } + if ( v > max || ( v == max && stdlib_base_is_positive_zero( v ) ) ) { + max = v; + } + } + return max; +} diff --git a/lib/node_modules/@stdlib/stats/base/dmax/test/test.dmax.js b/lib/node_modules/@stdlib/stats/strided/dmax/test/test.dmax.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/test/test.dmax.js rename to lib/node_modules/@stdlib/stats/strided/dmax/test/test.dmax.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/test/test.dmax.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/test/test.dmax.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/test/test.dmax.native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/test/test.dmax.native.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/test/test.js b/lib/node_modules/@stdlib/stats/strided/dmax/test/test.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/test/test.js rename to lib/node_modules/@stdlib/stats/strided/dmax/test/test.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmax/test/test.ndarray.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/test/test.ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dmax/test/test.ndarray.js diff --git a/lib/node_modules/@stdlib/stats/base/dmax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmax/test/test.ndarray.native.js similarity index 100% rename from lib/node_modules/@stdlib/stats/base/dmax/test/test.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dmax/test/test.ndarray.native.js diff --git a/lib/node_modules/@stdlib/strided/base/dtype-enum2str/README.md b/lib/node_modules/@stdlib/strided/base/dtype-enum2str/README.md index 2c9e1c6016b5..ed8f7795d2c0 100644 --- a/lib/node_modules/@stdlib/strided/base/dtype-enum2str/README.md +++ b/lib/node_modules/@stdlib/strided/base/dtype-enum2str/README.md @@ -126,6 +126,12 @@ str = enum2str( str2enum( 'uint8' ) );
+* * * + +## See Also + +- [`@stdlib/strided/base/dtype-str2enum`][@stdlib/strided/base/dtype-str2enum]: return the enumeration constant associated with a strided array data type string. +
@@ -134,6 +140,12 @@ str = enum2str( str2enum( 'uint8' ) );
+ + +[@stdlib/strided/base/dtype-str2enum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/dtype-str2enum + + +
diff --git a/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md b/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md index 51ddecccbcf4..25c144bfae2a 100644 --- a/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md +++ b/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md @@ -129,6 +129,12 @@ v = resolve( 'uint8' );
+* * * + +## See Also + +- [`@stdlib/strided/base/dtype-resolve-str`][@stdlib/strided/base/dtype-resolve-str]: return the data type string associated with a supported strided array data type value. +
@@ -137,6 +143,12 @@ v = resolve( 'uint8' );
+ + +[@stdlib/strided/base/dtype-resolve-str]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/dtype-resolve-str + + +
diff --git a/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md b/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md index 985f78ff384b..c3342e35c689 100644 --- a/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md +++ b/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md @@ -144,6 +144,13 @@ var im = imag( z );
+* * * + +## See Also + +- [`@stdlib/strided/base/reinterpret-complex128`][@stdlib/strided/base/reinterpret-complex128]: reinterpret a Complex128Array as a Float64Array. +- [`@stdlib/strided/base/reinterpret-complex64`][@stdlib/strided/base/reinterpret-complex64]: reinterpret a Complex64Array as a Float32Array. +
@@ -152,6 +159,14 @@ var im = imag( z );
+ + +[@stdlib/strided/base/reinterpret-complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/reinterpret-complex128 + +[@stdlib/strided/base/reinterpret-complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/reinterpret-complex64 + + +
diff --git a/lib/node_modules/@stdlib/string/base/kebabcase/README.md b/lib/node_modules/@stdlib/string/base/kebabcase/README.md index d5718f03689a..30be604521e8 100644 --- a/lib/node_modules/@stdlib/string/base/kebabcase/README.md +++ b/lib/node_modules/@stdlib/string/base/kebabcase/README.md @@ -93,6 +93,16 @@ out = kebabcase( str );
+* * * + +## See Also + +- [`@stdlib/string/base/camelcase`][@stdlib/string/base/camelcase]: convert a string to camel case. +- [`@stdlib/string/base/lowercase`][@stdlib/string/base/lowercase]: convert a string to lowercase. +- [`@stdlib/string/base/pascalcase`][@stdlib/string/base/pascalcase]: convert a string to Pascal case. +- [`@stdlib/string/base/snakecase`][@stdlib/string/base/snakecase]: convert a string to snake case. +- [`@stdlib/string/base/uppercase`][@stdlib/string/base/uppercase]: convert a string to uppercase. +
@@ -101,6 +111,20 @@ out = kebabcase( str );
+ + +[@stdlib/string/base/camelcase]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/base/camelcase + +[@stdlib/string/base/lowercase]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/base/lowercase + +[@stdlib/string/base/pascalcase]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/base/pascalcase + +[@stdlib/string/base/snakecase]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/base/snakecase + +[@stdlib/string/base/uppercase]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/base/uppercase + + +
diff --git a/lib/node_modules/@stdlib/string/base/right-pad/README.md b/lib/node_modules/@stdlib/string/base/right-pad/README.md index 380800a7d887..4681def9e808 100644 --- a/lib/node_modules/@stdlib/string/base/right-pad/README.md +++ b/lib/node_modules/@stdlib/string/base/right-pad/README.md @@ -109,6 +109,12 @@ logEach( '%s', out );
+* * * + +## See Also + +- [`@stdlib/string/base/left-pad`][@stdlib/string/base/left-pad]: left pad a string. +
@@ -117,6 +123,12 @@ logEach( '%s', out );
+ + +[@stdlib/string/base/left-pad]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/base/left-pad + + +
diff --git a/lib/node_modules/@stdlib/string/left-trim-n/README.md b/lib/node_modules/@stdlib/string/left-trim-n/README.md index 28266c566cf8..462dcf3c7fce 100644 --- a/lib/node_modules/@stdlib/string/left-trim-n/README.md +++ b/lib/node_modules/@stdlib/string/left-trim-n/README.md @@ -200,6 +200,13 @@ baz~~~
+* * * + +## See Also + +- [`@stdlib/string/right-trim-n`][@stdlib/string/right-trim-n]: trim `n` characters from the end of a string. +- [`@stdlib/string/trim`][@stdlib/string/trim]: trim whitespace characters from the beginning and end of a string. +
@@ -212,6 +219,14 @@ baz~~~ [standard-streams]: https://en.wikipedia.org/wiki/Standard_streams + + +[@stdlib/string/right-trim-n]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/right-trim-n + +[@stdlib/string/trim]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/string/trim + + +
diff --git a/lib/node_modules/@stdlib/time/ms2duration/README.md b/lib/node_modules/@stdlib/time/ms2duration/README.md index 5418ace75f1e..fdb0613bada6 100644 --- a/lib/node_modules/@stdlib/time/ms2duration/README.md +++ b/lib/node_modules/@stdlib/time/ms2duration/README.md @@ -50,7 +50,7 @@ duration = ms2duration( 3600000 ); ## Notes -- A duration string is a string containing a sequence of time units. A time unit is a non-negative integer followed by a unit identifier. The following unit identifiers are supported: +- A duration string is a string containing a sequence of time units. A time unit is a nonnegative integer followed by a unit identifier. The following unit identifiers are supported: - `d`: days - `h`: hours diff --git a/lib/node_modules/@stdlib/utils/async/do-until/README.md b/lib/node_modules/@stdlib/utils/async/do-until/README.md index f2ed58ba3e2f..f60a1c9d3c1a 100644 --- a/lib/node_modules/@stdlib/utils/async/do-until/README.md +++ b/lib/node_modules/@stdlib/utils/async/do-until/README.md @@ -75,18 +75,18 @@ doUntilAsync( fcn, predicate, done ); The function to invoke is provided two arguments: -- `i`: iteration number (starting from zero) -- `next`: a callback which must be invoked before proceeding to the next iteration +- `i`: iteration number (starting from zero). +- `next`: a callback which must be invoked before proceeding to the next iteration. The `predicate` function is provided two arguments: -- `i`: iteration number (starting from one) -- `clbk`: a callback indicating whether to invoke `fcn` +- `i`: iteration number (starting from one). +- `clbk`: a callback indicating whether to invoke `fcn`. The `clbk` function accepts two arguments: -- `error`: error object -- `bool`: test result +- `error`: error object. +- `bool`: test result. If the test result is falsy, the function continues invoking `fcn`; otherwise, the function invokes the `done` callback. diff --git a/lib/node_modules/@stdlib/utils/async/do-while/README.md b/lib/node_modules/@stdlib/utils/async/do-while/README.md index afe2f42c6264..825a51e6fb7d 100644 --- a/lib/node_modules/@stdlib/utils/async/do-while/README.md +++ b/lib/node_modules/@stdlib/utils/async/do-while/README.md @@ -75,18 +75,18 @@ doWhileAsync( fcn, predicate, done ); The function to invoke is provided two arguments: -- `i`: iteration number (starting from zero) -- `next`: a callback which must be invoked before proceeding to the next iteration +- `i`: iteration number (starting from zero). +- `next`: a callback which must be invoked before proceeding to the next iteration. The `predicate` function is provided two arguments: -- `i`: iteration number (starting from one) -- `clbk`: a callback indicating whether to invoke `fcn` +- `i`: iteration number (starting from one). +- `clbk`: a callback indicating whether to invoke `fcn`. The `clbk` function accepts two arguments: -- `error`: error object -- `bool`: test result +- `error`: error object. +- `bool`: test result. If the test result is truthy, the function continues invoking `fcn`; otherwise, the function invokes the `done` callback. diff --git a/lib/node_modules/@stdlib/utils/async/if-else/README.md b/lib/node_modules/@stdlib/utils/async/if-else/README.md index 691883ac23c1..38e660477f53 100644 --- a/lib/node_modules/@stdlib/utils/async/if-else/README.md +++ b/lib/node_modules/@stdlib/utils/async/if-else/README.md @@ -66,17 +66,17 @@ ifelseAsync( predicate, 1.0, -1.0, done ); The `predicate` function is provided a single argument: -- `clbk`: callback to invoke upon `predicate` function completion +- `clbk`: callback to invoke upon `predicate` function completion. The callback accepts two arguments: -- `error`: error object -- `bool`: condition used to determine whether to return `x` or `y` +- `error`: error object. +- `bool`: condition used to determine whether to return `x` or `y`. The `done` callback is invoked upon function completion and is provided at most two arguments: -- `error`: error object -- `result`: either `x` or `y` +- `error`: error object. +- `result`: either `x` or `y`.
diff --git a/lib/node_modules/@stdlib/utils/async/if-then/README.md b/lib/node_modules/@stdlib/utils/async/if-then/README.md index e0a78a700e26..fa7a0202f9d0 100644 --- a/lib/node_modules/@stdlib/utils/async/if-then/README.md +++ b/lib/node_modules/@stdlib/utils/async/if-then/README.md @@ -80,16 +80,16 @@ ifthenAsync( predicate, x, y, done ); The `predicate` function is provided a single argument: -- `clbk`: callback to invoke upon `predicate` function completion +- `clbk`: callback to invoke upon `predicate` function completion. The callback accepts two arguments: -- `error`: error object -- `bool`: condition used to determine whether to invoke `x` or `y` +- `error`: error object. +- `bool`: condition used to determine whether to invoke `x` or `y`. Both `x` and `y` are provided a single argument: -- `clbk`: callback to invoke upon function completion +- `clbk`: callback to invoke upon function completion. The callback function accepts any number of arguments, with the first argument reserved for providing an error. If the error argument is falsy, the `done` callback is invoked with its first argument as `null` and all other provided arguments. If the error argument is truthy, the `done` callback is invoked with only an error argument. diff --git a/lib/node_modules/@stdlib/utils/async/map-function/README.md b/lib/node_modules/@stdlib/utils/async/map-function/README.md index b5674a6d1129..79c89f9a1a8d 100644 --- a/lib/node_modules/@stdlib/utils/async/map-function/README.md +++ b/lib/node_modules/@stdlib/utils/async/map-function/README.md @@ -74,13 +74,13 @@ mapFunAsync( fcn, 5, done ); For each iteration, the provided function is invoked with two arguments: -- `index`: invocation index (starting from zero) -- `next`: callback to be invoked upon function completion +- `index`: invocation index (starting from zero). +- `next`: callback to be invoked upon function completion. The `next` callback accepts two arguments: -- `error`: error argument -- `result`: function result +- `error`: error argument. +- `result`: function result. The function accepts the following `options`: diff --git a/lib/node_modules/@stdlib/utils/async/try-catch/README.md b/lib/node_modules/@stdlib/utils/async/try-catch/README.md index 33811b69543a..0dd0f6ffbfef 100644 --- a/lib/node_modules/@stdlib/utils/async/try-catch/README.md +++ b/lib/node_modules/@stdlib/utils/async/try-catch/README.md @@ -69,17 +69,17 @@ trycatchAsync( x, -1.0, done ); The function `x` is provided a single argument: -- `clbk`: callback to invoke upon function completion +- `clbk`: callback to invoke upon function completion. The callback accepts two arguments: -- `error`: error object -- `result`: function result +- `error`: error object. +- `result`: function result. The `done` callback is invoked upon function completion and is provided two arguments: -- `error`: error object -- `result`: either the result of `x` or the provided value `y` +- `error`: error object. +- `result`: either the result of `x` or the provided value `y`. If the function `x` does not return a truthy `error` argument, the `error` argument provided to the `done` callback is `null`. If `x` does return a truthy `error` argument, the `done` callback is invoked with both the `error` and the provided value `y`. diff --git a/lib/node_modules/@stdlib/utils/async/try-then/README.md b/lib/node_modules/@stdlib/utils/async/try-then/README.md index 5da2886ecc5e..1fab8a48f1a7 100644 --- a/lib/node_modules/@stdlib/utils/async/try-then/README.md +++ b/lib/node_modules/@stdlib/utils/async/try-then/README.md @@ -76,7 +76,7 @@ trythenAsync( x, y, done ); The function `x` is provided a single argument: -- `clbk`: callback to invoke upon function completion +- `clbk`: callback to invoke upon function completion. The callback function accepts any number of arguments, with the first argument reserved for providing an error. If the error argument is falsy, the `done` callback is invoked with its first argument as `null` and all other provided arguments. @@ -109,12 +109,12 @@ trythenAsync( x, y, done ); If the error argument is truthy, the function invokes `y`. The number of arguments provided to `y` depends on the function's `length`. If `y` is a unary function, `y` is provided a single argument: -- `clbk`: callback to invoke upon function completion +- `clbk`: callback to invoke upon function completion. Otherwise, `y` is provided two arguments: -- `error`: the error from `x` -- `clbk`: callback to invoke upon function completion +- `error`: the error from `x`. +- `clbk`: callback to invoke upon function completion. The callback function accepts any number of arguments, with the first argument reserved for providing an error. If the error argument is falsy, the `done` callback is invoked with its first argument equal to `null` and all other provided arguments. If the error argument is truthy, the `done` callback is invoked with only the error argument provided by `y`. diff --git a/lib/node_modules/@stdlib/utils/async/until/README.md b/lib/node_modules/@stdlib/utils/async/until/README.md index 3cbc2b2890fb..92dd43b87435 100644 --- a/lib/node_modules/@stdlib/utils/async/until/README.md +++ b/lib/node_modules/@stdlib/utils/async/until/README.md @@ -75,20 +75,20 @@ untilAsync( predicate, fcn, done ); The `predicate` function is provided two arguments: -- `i`: iteration number (starting from zero) -- `clbk`: a callback indicating whether to invoke `fcn` +- `i`: iteration number (starting from zero). +- `clbk`: a callback indicating whether to invoke `fcn`. The `clbk` function accepts two arguments: -- `error`: error object -- `bool`: test result +- `error`: error object. +- `bool`: test result. If the test result is falsy, the function invokes `fcn`; otherwise, the function invokes the `done` callback. The function to invoke is provided two arguments: -- `i`: iteration number (starting from zero) -- `next`: a callback which must be invoked before proceeding to the next iteration +- `i`: iteration number (starting from zero). +- `next`: a callback which must be invoked before proceeding to the next iteration. The first argument of both `clbk` and `next` is an `error` argument. If either function is called with a truthy `error` argument, the function suspends execution and immediately calls the `done` callback for subsequent `error` handling. diff --git a/lib/node_modules/@stdlib/utils/async/while/README.md b/lib/node_modules/@stdlib/utils/async/while/README.md index 1546fa2a4a24..430daeca35f7 100644 --- a/lib/node_modules/@stdlib/utils/async/while/README.md +++ b/lib/node_modules/@stdlib/utils/async/while/README.md @@ -75,20 +75,20 @@ whileAsync( predicate, fcn, done ); The `predicate` function is provided two arguments: -- `i`: iteration number (starting from zero) -- `clbk`: a callback indicating whether to invoke `fcn` +- `i`: iteration number (starting from zero). +- `clbk`: a callback indicating whether to invoke `fcn`. The `clbk` function accepts two arguments: -- `error`: error object -- `bool`: test result +- `error`: error object. +- `bool`: test result. If the test result is truthy, the function invokes `fcn`; otherwise, the function invokes the `done` callback. The function to invoke is provided two arguments: -- `i`: iteration number (starting from zero) -- `next`: a callback which must be invoked before proceeding to the next iteration +- `i`: iteration number (starting from zero). +- `next`: a callback which must be invoked before proceeding to the next iteration. The first argument of both `clbk` and `next` is an `error` argument. If either function is called with a truthy `error` argument, the function suspends execution and immediately calls the `done` callback for subsequent `error` handling. diff --git a/lib/node_modules/@stdlib/utils/find/README.md b/lib/node_modules/@stdlib/utils/find/README.md index 6fb2193e8f86..34e2e4cedf36 100644 --- a/lib/node_modules/@stdlib/utils/find/README.md +++ b/lib/node_modules/@stdlib/utils/find/README.md @@ -46,9 +46,9 @@ Finds elements in an array-like object that satisfy a test condition. The functi The `callback` is provided three arguments: -- **element**: the current element -- **index**: the current element's index -- **array**: the input `array`, `typed array` or `string` +- **element**: the current element. +- **index**: the current element's index. +- **array**: the input `array`, `typed array` or `string`. By default, `k` is the length of `arr` and `returns` is set to `indices`. diff --git a/lib/node_modules/@stdlib/utils/named-typed-tuple/README.md b/lib/node_modules/@stdlib/utils/named-typed-tuple/README.md index a9f5da79213e..def89e74f434 100644 --- a/lib/node_modules/@stdlib/utils/named-typed-tuple/README.md +++ b/lib/node_modules/@stdlib/utils/named-typed-tuple/README.md @@ -357,9 +357,9 @@ y = tuple[ 1 ]; A callback function is provided three arguments: -- `value`: source value -- `index`: source index -- `field`: tuple field +- `value`: source value. +- `index`: source index. +- `field`: tuple field. To set the callback execution context, provide a `thisArg`. @@ -441,8 +441,8 @@ y = tuple[ 1 ]; A callback function is provided two arguments: -- `value`: source object tuple field value -- `field`: source object tuple field name +- `value`: source object tuple field value. +- `field`: source object tuple field name. To set the callback execution context, provide a `thisArg`. @@ -764,10 +764,10 @@ var bool = tuple.every( predicate ); A `predicate` function is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -928,10 +928,10 @@ var p2 = p1.filter( predicate ); A `predicate` function is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -991,10 +991,10 @@ var v = tuple.find( predicate ); A `predicate` function is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -1055,10 +1055,10 @@ var field = tuple.findField( predicate ); A `predicate` function is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -1119,10 +1119,10 @@ var idx = tuple.findIndex( predicate ); A `predicate` function is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -1175,10 +1175,10 @@ console.log( str ); The callback is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -1496,10 +1496,10 @@ var z = p2.z; A callback is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. @@ -1561,11 +1561,11 @@ var v = tuple.reduce( fcn, 0.0 ); A callback is provided five arguments: -- `acc`: accumulated result -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `acc`: accumulated result. +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. @@ -1605,11 +1605,11 @@ var v = tuple.reduceRight( fcn, 0.0 ); A callback is provided five arguments: -- `acc`: accumulated result -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `acc`: accumulated result. +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. @@ -1819,10 +1819,10 @@ var bool = tuple.some( predicate ); A `predicate` function is provided four arguments: -- `value`: tuple element -- `index`: tuple index -- `field`: tuple field name -- `tuple`: tuple on which the method is invoked +- `value`: tuple element. +- `index`: tuple index. +- `field`: tuple field name. +- `tuple`: tuple on which the method is invoked. To set the callback execution context, provide a `thisArg`. diff --git a/lib/node_modules/@stdlib/utils/tabulate-by/README.md b/lib/node_modules/@stdlib/utils/tabulate-by/README.md index d1a323f586df..c2c631708a8b 100644 --- a/lib/node_modules/@stdlib/utils/tabulate-by/README.md +++ b/lib/node_modules/@stdlib/utils/tabulate-by/README.md @@ -56,8 +56,8 @@ var out = tabulateBy( arr, indicator ); An `indicator` function is provided two arguments: -- `value`: collection element -- `index`: collection index +- `value`: collection element. +- `index`: collection index. ```javascript function indicator( v, i ) { @@ -98,9 +98,9 @@ console.log( context.count ); The returned frequency table is an `array` of `arrays`. Each sub-array corresponds to a unique value in the input `collection` and is structured as follows: -- `0`: unique value -- `1`: value count -- `2`: frequency percentage +- `0`: unique value. +- `1`: value count. +- `2`: frequency percentage.
diff --git a/lib/node_modules/@stdlib/utils/tabulate/README.md b/lib/node_modules/@stdlib/utils/tabulate/README.md index a0575dbbe87a..d80694ded1cb 100644 --- a/lib/node_modules/@stdlib/utils/tabulate/README.md +++ b/lib/node_modules/@stdlib/utils/tabulate/README.md @@ -53,9 +53,9 @@ var out = tabulate( arr ); The returned frequency table is an `array` of `arrays`. Each sub-array corresponds to a unique value in the input `collection` and is structured as follows: -- `0`: unique value -- `1`: value count -- `2`: frequency percentage +- `0`: unique value. +- `1`: value count. +- `2`: frequency percentage.
diff --git a/lib/node_modules/@stdlib/utils/until-each-right/README.md b/lib/node_modules/@stdlib/utils/until-each-right/README.md index 1e476a11e229..541082f24efa 100644 --- a/lib/node_modules/@stdlib/utils/until-each-right/README.md +++ b/lib/node_modules/@stdlib/utils/until-each-right/README.md @@ -65,9 +65,9 @@ untilEachRight( arr, predicate, log ); Both the `predicate` function and the `function` to apply are provided three arguments: -- `value`: collection element -- `index`: collection index -- `collection`: input collection +- `value`: collection element. +- `index`: collection index. +- `collection`: input collection. Basic support for dynamic collections is provided. Note, however, that index incrementation is **not** guaranteed to be monotonically **decreasing**. diff --git a/lib/node_modules/@stdlib/utils/while-each-right/README.md b/lib/node_modules/@stdlib/utils/while-each-right/README.md index a76f920b4be3..37a30a499f83 100644 --- a/lib/node_modules/@stdlib/utils/while-each-right/README.md +++ b/lib/node_modules/@stdlib/utils/while-each-right/README.md @@ -65,9 +65,9 @@ whileEachRight( arr, predicate, log ); Both the `predicate` function and the `function` to apply are provided three arguments: -- `value`: collection element -- `index`: collection index -- `collection`: input collection +- `value`: collection element. +- `index`: collection index. +- `collection`: input collection. Basic support for dynamic collections is provided. Note, however, that index incrementation is **not** guaranteed to be monotonically **decreasing**. diff --git a/tools/make/lib/git/README.md b/tools/make/lib/git/README.md index 615efa09ab3e..4a5383c8ed5f 100644 --- a/tools/make/lib/git/README.md +++ b/tools/make/lib/git/README.md @@ -64,7 +64,7 @@ Retries a previous commit created using `make commit`. $ make retry-commit ``` -This is particularly useful a commit failed due to lint errors. An example workflow might proceed as follows: +This is particularly useful if a commit failed due to lint errors. An example workflow might proceed as follows: diff --git a/tools/make/lib/lint/editorconfig.mk b/tools/make/lib/lint/editorconfig.mk index 7a7ee04610a2..85cdbe6c67d4 100644 --- a/tools/make/lib/lint/editorconfig.mk +++ b/tools/make/lib/lint/editorconfig.mk @@ -35,9 +35,16 @@ EDITORCONFIG_CHECKER_CONF ?= $(CONFIG_DIR)/editorconfig-checker/.editorconfig_ch # Define the path to the editorconfig-checker configuration file for Markdown files: EDITORCONFIG_CHECKER_MARKDOWN_CONF ?= $(CONFIG_DIR)/editorconfig-checker/.editorconfig_checker.markdown.json +# Define the output format (default is unset, which uses editorconfig-checker's default format) +EDITORCONFIG_FORMAT ?= + +# Add the format flag if EDITORCONFIG_FORMAT is set +EDITORCONFIG_FORMAT_FLAG := $(if $(EDITORCONFIG_FORMAT),--format=$(EDITORCONFIG_FORMAT)) + # Define the command-line options to use when invoking the editorconfig-checker executable: EDITORCONFIG_CHECKER_CONF_FLAGS ?= \ - --ignore-defaults + --ignore-defaults \ + $(EDITORCONFIG_FORMAT_FLAG) # RULES # @@ -57,7 +64,7 @@ lint-editorconfig: $(NODE_MODULES) $(QUIET) $(FIND_PACKAGES_CMD) | grep '^[\/]\|^[a-zA-Z]:[/\]' | while read -r pkg; do \ echo ''; \ echo "Linting package for basic formatting errors: $$pkg"; \ - cd "$$pkg" && ( $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_CONF) && $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_MARKDOWN_CONF) && echo 'Success. No detected EditorConfig lint errors.' && echo '' ) || exit 1; \ + cd "$$pkg" && ( $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_CONF) ./ && $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_MARKDOWN_CONF) ./ && echo 'Success. No detected EditorConfig lint errors.' && echo '' ) || exit 1; \ done .PHONY: lint-editorconfig @@ -81,8 +88,8 @@ lint-editorconfig-files: $(NODE_MODULES) $(QUIET) $(MKDIR_RECURSIVE) "$(BUILD_DIR)/editorconfig-checker" $(QUIET) echo $(FILES) | tr ' ' '\n' | $(TAR) -cf - -T - | $(TAR) -xf - -C "$(BUILD_DIR)/editorconfig-checker/" $(QUIET) cd "$(BUILD_DIR)/editorconfig-checker" && \ - $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_CONF) && \ - $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_MARKDOWN_CONF) && \ + $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_CONF) ./ && \ + $(NODE) $(EDITORCONFIG_CHECKER) $(EDITORCONFIG_CHECKER_CONF_FLAGS) --config $(EDITORCONFIG_CHECKER_MARKDOWN_CONF) ./ && \ echo 'Success. No detected EditorConfig lint errors.' && \ echo '' diff --git a/tools/snippets/README.md b/tools/snippets/README.md index ded745b95c94..93db27a11734 100644 --- a/tools/snippets/README.md +++ b/tools/snippets/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2024 The Stdlib Authors. +Copyright (c) 2025 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/benchmark.async.js b/tools/snippets/benchmark/benchmark.async.js index 688b12040791..d48d05f30de6 100644 --- a/tools/snippets/benchmark/benchmark.async.js +++ b/tools/snippets/benchmark/benchmark.async.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/benchmark.js b/tools/snippets/benchmark/benchmark.js index 767e4a019e1b..0c646ddcf267 100644 --- a/tools/snippets/benchmark/benchmark.js +++ b/tools/snippets/benchmark/benchmark.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/benchmark.length.js b/tools/snippets/benchmark/benchmark.length.js index c20dc91d9af5..813c02f29b45 100644 --- a/tools/snippets/benchmark/benchmark.length.js +++ b/tools/snippets/benchmark/benchmark.length.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/benchmark.native.js b/tools/snippets/benchmark/benchmark.native.js index 2f1daf9c0103..69b035a857c8 100644 --- a/tools/snippets/benchmark/benchmark.native.js +++ b/tools/snippets/benchmark/benchmark.native.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/benchmark.wasm.js b/tools/snippets/benchmark/benchmark.wasm.js index 2c18bfec696f..66165f7620dd 100644 --- a/tools/snippets/benchmark/benchmark.wasm.js +++ b/tools/snippets/benchmark/benchmark.wasm.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/c/Makefile b/tools/snippets/benchmark/c/Makefile index 88cbd1bb8a1b..635d877081d5 100644 --- a/tools/snippets/benchmark/c/Makefile +++ b/tools/snippets/benchmark/c/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/c/benchmark.c b/tools/snippets/benchmark/c/benchmark.c index 0f52b6d27280..9670a2d0bdf1 100644 --- a/tools/snippets/benchmark/c/benchmark.c +++ b/tools/snippets/benchmark/c/benchmark.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/c/cephes/Makefile b/tools/snippets/benchmark/c/cephes/Makefile index 35b7d7c26ebd..c103e646f7a5 100644 --- a/tools/snippets/benchmark/c/cephes/Makefile +++ b/tools/snippets/benchmark/c/cephes/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/c/cephes/benchmark.c b/tools/snippets/benchmark/c/cephes/benchmark.c index c579e9733466..c29256b2a648 100644 --- a/tools/snippets/benchmark/c/cephes/benchmark.c +++ b/tools/snippets/benchmark/c/cephes/benchmark.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/c/native/Makefile b/tools/snippets/benchmark/c/native/Makefile index 5d06a4714f91..100043f4054b 100644 --- a/tools/snippets/benchmark/c/native/Makefile +++ b/tools/snippets/benchmark/c/native/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/c/native/benchmark.c b/tools/snippets/benchmark/c/native/benchmark.c index 9a5435c130b4..07c9ebaf9bc0 100644 --- a/tools/snippets/benchmark/c/native/benchmark.c +++ b/tools/snippets/benchmark/c/native/benchmark.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -16,12 +16,12 @@ * limitations under the License. */ +#include "TODO.h" #include #include #include #include #include -#include "TODO.h" #define NAME "TODO" #define ITERATIONS 1000000 diff --git a/tools/snippets/benchmark/c/native/benchmark.length.c b/tools/snippets/benchmark/c/native/benchmark.length.c index 3cd3cc770c9a..870e23c5d006 100644 --- a/tools/snippets/benchmark/c/native/benchmark.length.c +++ b/tools/snippets/benchmark/c/native/benchmark.length.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -16,12 +16,12 @@ * limitations under the License. */ +#include "TODO.h" #include #include #include #include #include -#include "TODO.h" #define NAME "TODO" #define ITERATIONS 10000000 diff --git a/tools/snippets/benchmark/cpp/boost/Makefile b/tools/snippets/benchmark/cpp/boost/Makefile index eff50bbce3ae..a8582cd67345 100644 --- a/tools/snippets/benchmark/cpp/boost/Makefile +++ b/tools/snippets/benchmark/cpp/boost/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/cpp/boost/benchmark.cpp b/tools/snippets/benchmark/cpp/boost/benchmark.cpp index 5b687c5d7d73..0bdd0a9db2b9 100644 --- a/tools/snippets/benchmark/cpp/boost/benchmark.cpp +++ b/tools/snippets/benchmark/cpp/boost/benchmark.cpp @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/fortran/Makefile b/tools/snippets/benchmark/fortran/Makefile index feb4fdc606fd..fc211b649ce3 100644 --- a/tools/snippets/benchmark/fortran/Makefile +++ b/tools/snippets/benchmark/fortran/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/fortran/benchmark.f b/tools/snippets/benchmark/fortran/benchmark.f index 42a7abd4ff06..f8dedc5357d3 100644 --- a/tools/snippets/benchmark/fortran/benchmark.f +++ b/tools/snippets/benchmark/fortran/benchmark.f @@ -1,7 +1,7 @@ !> ! @license Apache-2.0 ! -! Copyright (c) 2024 The Stdlib Authors. +! Copyright (c) 2025 The Stdlib Authors. ! ! Licensed under the Apache License, Version 2.0 (the "License"); ! you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/fortran/native/Makefile b/tools/snippets/benchmark/fortran/native/Makefile index 85ccfc26080b..56b2cdf9ee54 100644 --- a/tools/snippets/benchmark/fortran/native/Makefile +++ b/tools/snippets/benchmark/fortran/native/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/fortran/native/benchmark.f b/tools/snippets/benchmark/fortran/native/benchmark.f index f4b943f0a3c3..48431d53f97d 100644 --- a/tools/snippets/benchmark/fortran/native/benchmark.f +++ b/tools/snippets/benchmark/fortran/native/benchmark.f @@ -1,7 +1,7 @@ !> ! @license Apache-2.0 ! -! Copyright (c) 2024 The Stdlib Authors. +! Copyright (c) 2025 The Stdlib Authors. ! ! Licensed under the Apache License, Version 2.0 (the "License"); ! you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/fortran/native/benchmark.length.f b/tools/snippets/benchmark/fortran/native/benchmark.length.f index 00e5b68f52f2..df4e16c50a33 100644 --- a/tools/snippets/benchmark/fortran/native/benchmark.length.f +++ b/tools/snippets/benchmark/fortran/native/benchmark.length.f @@ -1,7 +1,7 @@ !> ! @license Apache-2.0 ! -! Copyright (c) 2024 The Stdlib Authors. +! Copyright (c) 2025 The Stdlib Authors. ! ! Licensed under the Apache License, Version 2.0 (the "License"); ! you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/julia/benchmark.jl b/tools/snippets/benchmark/julia/benchmark.jl index c548c9413f41..5187008d5728 100755 --- a/tools/snippets/benchmark/julia/benchmark.jl +++ b/tools/snippets/benchmark/julia/benchmark.jl @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/python/benchmark.py b/tools/snippets/benchmark/python/benchmark.py index eb5cf28fa92d..c7f6e4ec38e8 100644 --- a/tools/snippets/benchmark/python/benchmark.py +++ b/tools/snippets/benchmark/python/benchmark.py @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/python/numpy/benchmark.py b/tools/snippets/benchmark/python/numpy/benchmark.py index 268a0eee08e2..260b5f1c68e9 100755 --- a/tools/snippets/benchmark/python/numpy/benchmark.py +++ b/tools/snippets/benchmark/python/numpy/benchmark.py @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/python/scipy/benchmark.py b/tools/snippets/benchmark/python/scipy/benchmark.py index ade2520d5494..275d4da40e7c 100755 --- a/tools/snippets/benchmark/python/scipy/benchmark.py +++ b/tools/snippets/benchmark/python/scipy/benchmark.py @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/benchmark/r/benchmark.R b/tools/snippets/benchmark/r/benchmark.R index 5940cf1ea4e3..0245788e590d 100755 --- a/tools/snippets/benchmark/r/benchmark.R +++ b/tools/snippets/benchmark/r/benchmark.R @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/bin/cli b/tools/snippets/bin/cli index d737111a54a0..7c1b87fb8167 100755 --- a/tools/snippets/bin/cli +++ b/tools/snippets/bin/cli @@ -3,7 +3,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/bin/cli_stdin b/tools/snippets/bin/cli_stdin index eb98a704ec02..44868f9cab59 100644 --- a/tools/snippets/bin/cli_stdin +++ b/tools/snippets/bin/cli_stdin @@ -3,7 +3,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/examples/index.js b/tools/snippets/examples/index.js index f9c9747b9f6b..a9e69ac28ea0 100644 --- a/tools/snippets/examples/index.js +++ b/tools/snippets/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/include/stdlib/todo.h b/tools/snippets/include/stdlib/todo.h index afbd6e5b3a27..6b834781571c 100644 --- a/tools/snippets/include/stdlib/todo.h +++ b/tools/snippets/include/stdlib/todo.h @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/lib/index.js b/tools/snippets/lib/index.js index d328dae487a2..d553da142c86 100644 --- a/tools/snippets/lib/index.js +++ b/tools/snippets/lib/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/lib/main.js b/tools/snippets/lib/main.js index 19673be4ca8a..be644cf0fca6 100644 --- a/tools/snippets/lib/main.js +++ b/tools/snippets/lib/main.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/lib/validate.js b/tools/snippets/lib/validate.js index 95cd9fbe5d27..6078bd3fb5fe 100644 --- a/tools/snippets/lib/validate.js +++ b/tools/snippets/lib/validate.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/src/Makefile b/tools/snippets/src/Makefile index bcf18aa46655..7733b6180cb4 100644 --- a/tools/snippets/src/Makefile +++ b/tools/snippets/src/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/src/addon.c b/tools/snippets/src/addon.c index 4a2388fb907a..a158f045f84d 100644 --- a/tools/snippets/src/addon.c +++ b/tools/snippets/src/addon.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/src/main.c b/tools/snippets/src/main.c index ace6bc92f41f..24f0765d71e4 100644 --- a/tools/snippets/src/main.c +++ b/tools/snippets/src/main.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/c/cephes/Makefile b/tools/snippets/test/fixtures/c/cephes/Makefile index ee252738689e..fd3f30129594 100644 --- a/tools/snippets/test/fixtures/c/cephes/Makefile +++ b/tools/snippets/test/fixtures/c/cephes/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/c/cephes/runner.c b/tools/snippets/test/fixtures/c/cephes/runner.c index 1b76e91fabb9..2ef820d96629 100644 --- a/tools/snippets/test/fixtures/c/cephes/runner.c +++ b/tools/snippets/test/fixtures/c/cephes/runner.c @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/cpp/boost/Makefile b/tools/snippets/test/fixtures/cpp/boost/Makefile index 8ba5f7c629bd..94874eb7a405 100644 --- a/tools/snippets/test/fixtures/cpp/boost/Makefile +++ b/tools/snippets/test/fixtures/cpp/boost/Makefile @@ -1,7 +1,7 @@ #/ # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/cpp/boost/runner.cpp b/tools/snippets/test/fixtures/cpp/boost/runner.cpp index c32d421a8b36..d91cebe5e6a1 100644 --- a/tools/snippets/test/fixtures/cpp/boost/runner.cpp +++ b/tools/snippets/test/fixtures/cpp/boost/runner.cpp @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/julia/runner.jl b/tools/snippets/test/fixtures/julia/runner.jl index 1025b93a7e4f..74aff7d3c714 100644 --- a/tools/snippets/test/fixtures/julia/runner.jl +++ b/tools/snippets/test/fixtures/julia/runner.jl @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/python/runner.py b/tools/snippets/test/fixtures/python/runner.py index 45119f27f677..5acb4c6d301f 100644 --- a/tools/snippets/test/fixtures/python/runner.py +++ b/tools/snippets/test/fixtures/python/runner.py @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/r/runner.R b/tools/snippets/test/fixtures/r/runner.R index 2cd3bc9136d9..e1e4d755118d 100644 --- a/tools/snippets/test/fixtures/r/runner.R +++ b/tools/snippets/test/fixtures/r/runner.R @@ -2,7 +2,7 @@ # # @license Apache-2.0 # -# Copyright (c) 2024 The Stdlib Authors. +# Copyright (c) 2025 The Stdlib Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/fixtures/stdin_error.js.txt b/tools/snippets/test/fixtures/stdin_error.js.txt index c7e3c506a96b..7b3cc56df0fa 100644 --- a/tools/snippets/test/fixtures/stdin_error.js.txt +++ b/tools/snippets/test/fixtures/stdin_error.js.txt @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/test.cli.js b/tools/snippets/test/test.cli.js index 2f3d7d270a21..61e11e246eee 100644 --- a/tools/snippets/test/test.cli.js +++ b/tools/snippets/test/test.cli.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/test.js b/tools/snippets/test/test.js index 5e23e37197f1..ab6b7d018893 100644 --- a/tools/snippets/test/test.js +++ b/tools/snippets/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/test.native.js b/tools/snippets/test/test.native.js index d51b9c47be00..b46ab66277c6 100644 --- a/tools/snippets/test/test.native.js +++ b/tools/snippets/test/test.native.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/test.stdin_cli.js b/tools/snippets/test/test.stdin_cli.js index 1ec83225f144..c9bd774e929d 100644 --- a/tools/snippets/test/test.stdin_cli.js +++ b/tools/snippets/test/test.stdin_cli.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/tools/snippets/test/test.validate.js b/tools/snippets/test/test.validate.js index 12bd75f8d7ab..c4bedccaee84 100644 --- a/tools/snippets/test/test.validate.js +++ b/tools/snippets/test/test.validate.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2024 The Stdlib Authors. +* Copyright (c) 2025 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License.